commit

analysis/pricing_analysis.py

@@ -1,259 +0,0 @@
-#!/usr/bin/env python3
-"""
-OpenRouter API Pricing Analysis
-Analyzes context windows, token pricing, and output/input ratios
-"""
-
-import json
-import numpy as np
-from pathlib import Path
-from typing import Dict, List, Any
-import statistics
-
-def load_data(file_path: str) -> List[Dict[str, Any]]:
-    """Load the models data from JSON file"""
-    with open(file_path, 'r') as f:
-        return json.load(f)
-
-def calculate_distribution_stats(values: List[float], name: str) -> Dict[str, Any]:
-    """Calculate comprehensive distribution statistics"""
-    if not values:
-        return {"error": "No data"}
-
-    values = sorted(values)
-    n = len(values)
-
-    stats = {
-        "name": name,
-        "count": n,
-        "min": min(values),
-        "max": max(values),
-        "mean": statistics.mean(values),
-        "median": statistics.median(values),
-        "std_dev": statistics.stdev(values) if n > 1 else 0,
-    }
-
-    # Quartiles
-    stats["q1"] = np.percentile(values, 25)
-    stats["q3"] = np.percentile(values, 75)
-    stats["iqr"] = stats["q3"] - stats["q1"]
-
-    # Additional percentiles
-    stats["p10"] = np.percentile(values, 10)
-    stats["p90"] = np.percentile(values, 90)
-    stats["p95"] = np.percentile(values, 95)
-    stats["p99"] = np.percentile(values, 99)
-
-    return stats
-
-def calculate_stratification(values: List[float], name: str) -> Dict[str, Any]:
-    """Calculate stratification by creating bins/ranges"""
-    if not values:
-        return {"error": "No data"}
-
-    values_array = np.array(values)
-
-    # Determine appropriate bins based on data range
-    min_val = values_array.min()
-    max_val = values_array.max()
-
-    # Create stratification bins
-    if max_val - min_val < 1:
-        # For very small ranges (like some pricing)
-        bins = np.linspace(min_val, max_val, 11)
-    else:
-        # Use log scale for wide ranges
-        if min_val > 0:
-            bins = np.logspace(np.log10(max(min_val, 0.0001)), np.log10(max_val), 11)
-        else:
-            bins = np.linspace(min_val, max_val, 11)
-
-    hist, bin_edges = np.histogram(values_array, bins=bins)
-
-    stratification = {
-        "name": name,
-        "bins": []
-    }
-
-    for i in range(len(hist)):
-        stratification["bins"].append({
-            "range": f"{bin_edges[i]:.6f} - {bin_edges[i+1]:.6f}",
-            "count": int(hist[i]),
-            "percentage": float(hist[i] / len(values) * 100)
-        })
-
-    return stratification
-
-def analyze_context_windows(models: List[Dict[str, Any]]) -> tuple:
-    """Analyze context window distribution"""
-    context_lengths = [
-        m['context_length']
-        for m in models
-        if m.get('context_length') and m['context_length'] > 0
-    ]
-
-    distribution = calculate_distribution_stats(context_lengths, "Context Windows")
-    stratification = calculate_stratification(context_lengths, "Context Windows")
-
-    return distribution, stratification
-
-def analyze_input_pricing(models: List[Dict[str, Any]]) -> tuple:
-    """Analyze input token pricing distribution"""
-    input_prices = [
-        m['prompt_price_per_1m_tokens']
-        for m in models
-        if m.get('prompt_price_per_1m_tokens') is not None and m['prompt_price_per_1m_tokens'] > 0
-    ]
-
-    distribution = calculate_distribution_stats(input_prices, "Input Token Pricing (per 1M tokens)")
-    stratification = calculate_stratification(input_prices, "Input Token Pricing")
-
-    return distribution, stratification
-
-def analyze_output_pricing(models: List[Dict[str, Any]]) -> tuple:
-    """Analyze output token pricing distribution"""
-    output_prices = [
-        m['completion_price_per_1m_tokens']
-        for m in models
-        if m.get('completion_price_per_1m_tokens') is not None and m['completion_price_per_1m_tokens'] > 0
-    ]
-
-    distribution = calculate_distribution_stats(output_prices, "Output Token Pricing (per 1M tokens)")
-    stratification = calculate_stratification(output_prices, "Output Token Pricing")
-
-    return distribution, stratification
-
-def analyze_output_input_ratio(models: List[Dict[str, Any]]) -> tuple:
-    """Analyze output/input token price ratio"""
-    ratios = []
-
-    for m in models:
-        input_price = m.get('prompt_price_per_1m_tokens', 0)
-        output_price = m.get('completion_price_per_1m_tokens', 0)
-
-        # Calculate ratio only for non-free models
-        if input_price > 0 and output_price > 0:
-            ratio = output_price / input_price
-            ratios.append(ratio)
-
-    distribution = calculate_distribution_stats(ratios, "Output/Input Price Ratio")
-    stratification = calculate_stratification(ratios, "Output/Input Price Ratio")
-
-    return distribution, stratification
-
-def format_distribution_report(dist: Dict[str, Any]) -> str:
-    """Format distribution statistics as readable text"""
-    if "error" in dist:
-        return f"Error: {dist['error']}"
-
-    report = f"""
-{dist['name']}
-{'=' * len(dist['name'])}
-
-Sample Size: {dist['count']:,}
-
-Central Tendency:
-  Mean:   {dist['mean']:.6f}
-  Median: {dist['median']:.6f}
-
-Spread:
-  Min:     {dist['min']:.6f}
-  Max:     {dist['max']:.6f}
-  Std Dev: {dist['std_dev']:.6f}
-  IQR:     {dist['iqr']:.6f}
-
-Quartiles:
-  Q1 (25th percentile): {dist['q1']:.6f}
-  Q2 (50th percentile): {dist['median']:.6f}
-  Q3 (75th percentile): {dist['q3']:.6f}
-
-Additional Percentiles:
-  10th: {dist['p10']:.6f}
-  90th: {dist['p90']:.6f}
-  95th: {dist['p95']:.6f}
-  99th: {dist['p99']:.6f}
-"""
-    return report
-
-def format_stratification_report(strat: Dict[str, Any]) -> str:
-    """Format stratification as readable text"""
-    if "error" in strat:
-        return f"Error: {strat['error']}"
-
-    report = f"""
-{strat['name']} - Stratification
-{'=' * (len(strat['name']) + 18)}
-
-Range Distribution:
-"""
-
-    for bin_data in strat['bins']:
-        report += f"  {bin_data['range']:>40s}: {bin_data['count']:>6,} models ({bin_data['percentage']:>5.1f}%)\n"
-
-    return report
-
-def main():
-    # Load data
-    data_file = Path(__file__).parent.parent / 'raw' / 'models.json'
-    models = load_data(data_file)
-
-    print(f"Loaded {len(models)} models\n")
-
-    # Create output directory
-    output_dir = Path(__file__).parent
-    output_dir.mkdir(exist_ok=True)
-
-    # Analyze each metric
-    analyses = {
-        'context_windows': analyze_context_windows(models),
-        'input_pricing': analyze_input_pricing(models),
-        'output_pricing': analyze_output_pricing(models),
-        'output_input_ratio': analyze_output_input_ratio(models)
-    }
-
-    # Generate reports for each analysis
-    for metric_name, (distribution, stratification) in analyses.items():
-        # Create individual report files
-        dist_report = format_distribution_report(distribution)
-        strat_report = format_stratification_report(stratification)
-
-        # Write distribution report
-        dist_file = output_dir / f"{metric_name}_distribution.txt"
-        with open(dist_file, 'w') as f:
-            f.write(dist_report)
-        print(f"Created: {dist_file}")
-
-        # Write stratification report
-        strat_file = output_dir / f"{metric_name}_stratification.txt"
-        with open(strat_file, 'w') as f:
-            f.write(strat_report)
-        print(f"Created: {strat_file}")
-
-        # Also save as JSON for programmatic access
-        json_file = output_dir / f"{metric_name}_stats.json"
-        with open(json_file, 'w') as f:
-            json.dump({
-                'distribution': distribution,
-                'stratification': stratification
-            }, f, indent=2)
-        print(f"Created: {json_file}")
-
-    # Create comprehensive summary report
-    summary_file = output_dir / "summary_report.txt"
-    with open(summary_file, 'w') as f:
-        f.write("OpenRouter API Pricing Analysis - Summary Report\n")
-        f.write("=" * 60 + "\n\n")
-        f.write(f"Dataset: {len(models)} models analyzed\n\n")
-
-        for metric_name, (distribution, stratification) in analyses.items():
-            f.write("\n" + "=" * 60 + "\n")
-            f.write(format_distribution_report(distribution))
-            f.write("\n")
-            f.write(format_stratification_report(stratification))
-            f.write("\n")
-
-    print(f"\nCreated: {summary_file}")
-    print("\nAnalysis complete!")
-
-if __name__ == "__main__":
-    main()

analysis/vendors/vendor_detailed.txt

@@ -0,0 +1,1934 @@
+OpenRouter API - Detailed Vendor Analysis
+======================================================================
+
+
+======================================================================
+Vendor: OpenAI
+======================================================================
+
+Total Models: 47
+  Free Models: 1
+  Paid Models: 46
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 46
+  Min:    $0.030000
+  Max:    $150.000000
+  Mean:   $7.915109
+  Median: $2.000000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 46
+  Min:    $0.140000
+  Max:    $600.000000
+  Mean:   $28.573478
+  Median: $8.000000
+
+Context Lengths:
+  Models with context data: 47
+  Min:    4,095 tokens
+  Max:    1,047,576 tokens
+  Mean:   229,264 tokens
+  Median: 131,072 tokens
+
+Models (showing first 10 of 47):
+  - OpenAI: gpt-oss-safeguard-20b
+  - OpenAI: GPT-5 Image Mini
+  - OpenAI: GPT-5 Image
+  - OpenAI: o3 Deep Research
+  - OpenAI: o4 Mini Deep Research
+  - OpenAI: GPT-5 Pro
+  - OpenAI: GPT-5 Codex
+  - OpenAI: GPT-4o Audio
+  - OpenAI: GPT-5 Chat
+  - OpenAI: GPT-5
+  ... and 37 more
+
+
+======================================================================
+Vendor: Qwen
+======================================================================
+
+Total Models: 46
+  Free Models: 8
+  Paid Models: 38
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 38
+  Min:    $0.030000
+  Max:    $1.600000
+  Mean:   $0.257763
+  Median: $0.150000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 38
+  Min:    $0.090000
+  Max:    $6.400000
+  Mean:   $1.189421
+  Median: $0.575000
+
+Context Lengths:
+  Models with context data: 46
+  Min:    7,500 tokens
+  Max:    1,000,000 tokens
+  Mean:   185,297 tokens
+  Median: 128,000 tokens
+
+Models (showing first 10 of 46):
+  - Qwen: Qwen3 VL 8B Thinking
+  - Qwen: Qwen3 VL 8B Instruct
+  - Qwen: Qwen3 VL 30B A3B Thinking
+  - Qwen: Qwen3 VL 30B A3B Instruct
+  - Qwen: Qwen3 VL 235B A22B Thinking
+  - Qwen: Qwen3 VL 235B A22B Instruct
+  - Qwen: Qwen3 Max
+  - Qwen: Qwen3 Coder Plus
+  - Qwen: Qwen3 Coder Flash
+  - Qwen: Qwen3 Next 80B A3B Thinking
+  ... and 36 more
+
+
+======================================================================
+Vendor: Mistral AI
+======================================================================
+
+Total Models: 36
+  Free Models: 5
+  Paid Models: 31
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 31
+  Min:    $0.020000
+  Max:    $2.000000
+  Mean:   $0.596968
+  Median: $0.200000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 31
+  Min:    $0.040000
+  Max:    $6.000000
+  Mean:   $1.717677
+  Median: $0.540000
+
+Context Lengths:
+  Models with context data: 36
+  Min:    2,824 tokens
+  Max:    262,144 tokens
+  Mean:   91,245 tokens
+  Median: 112,000 tokens
+
+Models (showing first 10 of 36):
+  - Mistral: Voxtral Small 24B 2507
+  - Mistral: Mistral Medium 3.1
+  - Mistral: Codestral 2508
+  - Mistral: Devstral Medium
+  - Mistral: Devstral Small 1.1
+  - Mistral: Mistral Small 3.2 24B (free)
+  - Mistral: Mistral Small 3.2 24B
+  - Mistral: Magistral Small 2506
+  - Mistral: Magistral Medium 2506 (thinking)
+  - Mistral: Magistral Medium 2506
+  ... and 26 more
+
+
+======================================================================
+Vendor: Google
+======================================================================
+
+Total Models: 24
+  Free Models: 6
+  Paid Models: 18
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 18
+  Min:    $0.017030
+  Max:    $1.250000
+  Mean:   $0.347891
+  Median: $0.100000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 18
+  Min:    $0.040000
+  Max:    $10.000000
+  Mean:   $2.389342
+  Median: $0.400000
+
+Context Lengths:
+  Models with context data: 24
+  Min:    8,192 tokens
+  Max:    1,048,576 tokens
+  Mean:   509,173 tokens
+  Median: 131,072 tokens
+
+Models (showing first 10 of 24):
+  - Google: Gemini 2.5 Flash Image (Nano Banana)
+  - Google: Gemini 2.5 Flash Preview 09-2025
+  - Google: Gemini 2.5 Flash Lite Preview 09-2025
+  - Google: Gemini 2.5 Flash Image Preview (Nano Banana)
+  - Google: Gemini 2.5 Flash Lite
+  - Google: Gemma 3n 2B (free)
+  - Google: Gemini 2.5 Flash Lite Preview 06-17
+  - Google: Gemini 2.5 Flash
+  - Google: Gemini 2.5 Pro
+  - Google: Gemini 2.5 Pro Preview 06-05
+  ... and 14 more
+
+
+======================================================================
+Vendor: Meta
+======================================================================
+
+Total Models: 21
+  Free Models: 5
+  Paid Models: 16
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 16
+  Min:    $0.005000
+  Max:    $4.000000
+  Mean:   $0.420875
+  Median: $0.140000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 16
+  Min:    $0.010000
+  Max:    $4.000000
+  Mean:   $0.493062
+  Median: $0.250000
+
+Context Lengths:
+  Models with context data: 21
+  Min:    8,192 tokens
+  Max:    1,048,576 tokens
+  Mean:   153,649 tokens
+  Median: 131,072 tokens
+
+Models (showing first 10 of 21):
+  - Meta: Llama 3.3 8B Instruct (free)
+  - Meta: Llama Guard 4 12B
+  - Meta: Llama 4 Maverick (free)
+  - Meta: Llama 4 Maverick
+  - Meta: Llama 4 Scout (free)
+  - Meta: Llama 4 Scout
+  - Llama Guard 3 8B
+  - Meta: Llama 3.3 70B Instruct (free)
+  - Meta: Llama 3.3 70B Instruct
+  - Meta: Llama 3.2 1B Instruct
+  ... and 11 more
+
+
+======================================================================
+Vendor: DeepSeek
+======================================================================
+
+Total Models: 19
+  Free Models: 6
+  Paid Models: 13
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 13
+  Min:    $0.020000
+  Max:    $0.500000
+  Mean:   $0.244615
+  Median: $0.270000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 13
+  Min:    $0.100000
+  Max:    $2.180000
+  Mean:   $0.840000
+  Median: $0.840000
+
+Context Lengths:
+  Models with context data: 19
+  Min:    8,192 tokens
+  Max:    163,840 tokens
+  Mean:   134,950 tokens
+  Median: 163,840 tokens
+
+Models (showing first 10 of 19):
+  - DeepSeek: DeepSeek V3.2 Exp
+  - DeepSeek: DeepSeek V3.1 Terminus
+  - DeepSeek: DeepSeek V3.1 Terminus (exacto)
+  - DeepSeek: DeepSeek V3.1 (free)
+  - DeepSeek: DeepSeek V3.1
+  - DeepSeek: DeepSeek R1 0528 Qwen3 8B (free)
+  - DeepSeek: DeepSeek R1 0528 Qwen3 8B
+  - DeepSeek: R1 0528 (free)
+  - DeepSeek: R1 0528
+  - DeepSeek: DeepSeek Prover V2
+  ... and 9 more
+
+
+======================================================================
+Vendor: Anthropic
+======================================================================
+
+Total Models: 13
+  Free Models: 0
+  Paid Models: 13
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 13
+  Min:    $0.250000
+  Max:    $15.000000
+  Mean:   $5.065385
+  Median: $3.000000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 13
+  Min:    $1.250000
+  Max:    $75.000000
+  Mean:   $25.326923
+  Median: $15.000000
+
+Context Lengths:
+  Models with context data: 13
+  Min:    200,000 tokens
+  Max:    1,000,000 tokens
+  Mean:   323,077 tokens
+  Median: 200,000 tokens
+
+Models (showing first 10 of 13):
+  - Anthropic: Claude Haiku 4.5
+  - Anthropic: Claude Sonnet 4.5
+  - Anthropic: Claude Opus 4.1
+  - Anthropic: Claude Opus 4
+  - Anthropic: Claude Sonnet 4
+  - Anthropic: Claude 3.7 Sonnet (thinking)
+  - Anthropic: Claude 3.7 Sonnet
+  - Anthropic: Claude 3.5 Haiku
+  - Anthropic: Claude 3.5 Haiku (2024-10-22)
+  - Anthropic: Claude 3.5 Sonnet
+  ... and 3 more
+
+
+======================================================================
+Vendor: Microsoft
+======================================================================
+
+Total Models: 9
+  Free Models: 1
+  Paid Models: 8
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 8
+  Min:    $0.050000
+  Max:    $1.000000
+  Mean:   $0.270000
+  Median: $0.100000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 8
+  Min:    $0.100000
+  Max:    $1.200000
+  Mean:   $0.433750
+  Median: $0.245000
+
+Context Lengths:
+  Models with context data: 9
+  Min:    16,384 tokens
+  Max:    163,840 tokens
+  Mean:   106,382 tokens
+  Median: 128,000 tokens
+
+Models:
+  - Microsoft: Phi 4 Reasoning Plus
+  - Microsoft: MAI DS R1 (free)
+  - Microsoft: MAI DS R1
+  - Microsoft: Phi 4 Multimodal Instruct
+  - Microsoft: Phi 4
+  - Microsoft: Phi-3.5 Mini 128K Instruct
+  - Microsoft: Phi-3 Mini 128K Instruct
+  - Microsoft: Phi-3 Medium 128K Instruct
+  - WizardLM-2 8x22B
+
+
+======================================================================
+Vendor: Moonshot AI
+======================================================================
+
+Total Models: 7
+  Free Models: 1
+  Paid Models: 6
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 6
+  Min:    $0.290000
+  Max:    $0.600000
+  Mean:   $0.446667
+  Median: $0.445000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 6
+  Min:    $0.600000
+  Max:    $2.500000
+  Mean:   $1.841667
+  Median: $2.150000
+
+Context Lengths:
+  Models with context data: 7
+  Min:    32,768 tokens
+  Max:    1,048,576 tokens
+  Mean:   304,274 tokens
+  Median: 262,144 tokens
+
+Models:
+  - MoonshotAI: Kimi Linear 48B A3B Instruct
+  - MoonshotAI: Kimi K2 Thinking
+  - MoonshotAI: Kimi K2 0905
+  - MoonshotAI: Kimi K2 0905 (exacto)
+  - MoonshotAI: Kimi K2 0711 (free)
+  - MoonshotAI: Kimi K2 0711
+  - MoonshotAI: Kimi Dev 72B
+
+
+======================================================================
+Vendor: NVIDIA
+======================================================================
+
+Total Models: 7
+  Free Models: 2
+  Paid Models: 5
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 5
+  Min:    $0.040000
+  Max:    $0.600000
+  Mean:   $0.308000
+  Median: $0.200000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 5
+  Min:    $0.160000
+  Max:    $1.800000
+  Mean:   $0.712000
+  Median: $0.600000
+
+Context Lengths:
+  Models with context data: 7
+  Min:    128,000 tokens
+  Max:    131,072 tokens
+  Mean:   130,194 tokens
+  Median: 131,072 tokens
+
+Models:
+  - NVIDIA: Nemotron Nano 12B 2 VL (free)
+  - NVIDIA: Nemotron Nano 12B 2 VL
+  - NVIDIA: Llama 3.3 Nemotron Super 49B V1.5
+  - NVIDIA: Nemotron Nano 9B V2 (free)
+  - NVIDIA: Nemotron Nano 9B V2
+  - NVIDIA: Llama 3.1 Nemotron Ultra 253B v1
+  - NVIDIA: Llama 3.1 Nemotron 70B Instruct
+
+
+======================================================================
+Vendor: Z-AI
+======================================================================
+
+Total Models: 7
+  Free Models: 1
+  Paid Models: 6
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 6
+  Min:    $0.100000
+  Max:    $0.600000
+  Mean:   $0.338333
+  Median: $0.375000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 6
+  Min:    $0.100000
+  Max:    $1.900000
+  Mean:   $1.325000
+  Median: $1.650000
+
+Context Lengths:
+  Models with context data: 7
+  Min:    65,536 tokens
+  Max:    202,752 tokens
+  Mean:   141,751 tokens
+  Median: 131,072 tokens
+
+Models:
+  - Z.AI: GLM 4.6
+  - Z.AI: GLM 4.6 (exacto)
+  - Z.AI: GLM 4.5V
+  - Z.AI: GLM 4.5
+  - Z.AI: GLM 4.5 Air (free)
+  - Z.AI: GLM 4.5 Air
+  - Z.AI: GLM 4 32B 
+
+
+======================================================================
+Vendor: xAI
+======================================================================
+
+Total Models: 7
+  Free Models: 0
+  Paid Models: 7
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 7
+  Min:    $0.200000
+  Max:    $3.000000
+  Mean:   $1.428571
+  Median: $0.300000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 7
+  Min:    $0.500000
+  Max:    $15.000000
+  Mean:   $6.857143
+  Median: $1.500000
+
+Context Lengths:
+  Models with context data: 7
+  Min:    131,072 tokens
+  Max:    2,000,000 tokens
+  Mean:   433,755 tokens
+  Median: 131,072 tokens
+
+Models:
+  - xAI: Grok 4 Fast
+  - xAI: Grok Code Fast 1
+  - xAI: Grok 4
+  - xAI: Grok 3 Mini
+  - xAI: Grok 3
+  - xAI: Grok 3 Mini Beta
+  - xAI: Grok 3 Beta
+
+
+======================================================================
+Vendor: Nous Research
+======================================================================
+
+Total Models: 7
+  Free Models: 1
+  Paid Models: 6
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 6
+  Min:    $0.025000
+  Max:    $1.000000
+  Mean:   $0.314167
+  Median: $0.225000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 6
+  Min:    $0.080000
+  Max:    $1.200000
+  Mean:   $0.591667
+  Median: $0.485000
+
+Context Lengths:
+  Models with context data: 7
+  Min:    32,768 tokens
+  Max:    131,072 tokens
+  Mean:   93,623 tokens
+  Median: 131,072 tokens
+
+Models:
+  - Nous: Hermes 4 70B
+  - Nous: Hermes 4 405B
+  - Nous: DeepHermes 3 Mistral 24B Preview
+  - Nous: Hermes 3 70B Instruct
+  - Nous: Hermes 3 405B Instruct (free)
+  - Nous: Hermes 3 405B Instruct
+  - NousResearch: Hermes 2 Pro - Llama-3 8B
+
+
+======================================================================
+Vendor: Perplexity
+======================================================================
+
+Total Models: 6
+  Free Models: 0
+  Paid Models: 6
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 6
+  Min:    $1.000000
+  Max:    $3.000000
+  Mean:   $2.000000
+  Median: $2.000000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 6
+  Min:    $1.000000
+  Max:    $15.000000
+  Mean:   $8.666667
+  Median: $8.000000
+
+Context Lengths:
+  Models with context data: 6
+  Min:    127,000 tokens
+  Max:    200,000 tokens
+  Mean:   151,679 tokens
+  Median: 128,000 tokens
+
+Models:
+  - Perplexity: Sonar Pro Search
+  - Perplexity: Sonar Reasoning Pro
+  - Perplexity: Sonar Pro
+  - Perplexity: Sonar Deep Research
+  - Perplexity: Sonar Reasoning
+  - Perplexity: Sonar
+
+
+======================================================================
+Vendor: Baidu
+======================================================================
+
+Total Models: 5
+  Free Models: 0
+  Paid Models: 5
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 5
+  Min:    $0.070000
+  Max:    $0.420000
+  Mean:   $0.196000
+  Median: $0.140000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 5
+  Min:    $0.280000
+  Max:    $1.250000
+  Mean:   $0.694000
+  Median: $0.560000
+
+Context Lengths:
+  Models with context data: 5
+  Min:    30,000 tokens
+  Max:    131,072 tokens
+  Mean:   105,414 tokens
+  Median: 123,000 tokens
+
+Models:
+  - Baidu: ERNIE 4.5 21B A3B Thinking
+  - Baidu: ERNIE 4.5 21B A3B
+  - Baidu: ERNIE 4.5 VL 28B A3B
+  - Baidu: ERNIE 4.5 VL 424B A47B 
+  - Baidu: ERNIE 4.5 300B A47B 
+
+
+======================================================================
+Vendor: TheDrummer
+======================================================================
+
+Total Models: 5
+  Free Models: 0
+  Paid Models: 5
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 5
+  Min:    $0.170000
+  Max:    $0.650000
+  Mean:   $0.404000
+  Median: $0.400000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 5
+  Min:    $0.400000
+  Max:    $1.000000
+  Mean:   $0.626000
+  Median: $0.500000
+
+Context Lengths:
+  Models with context data: 5
+  Min:    32,768 tokens
+  Max:    131,072 tokens
+  Mean:   72,090 tokens
+  Median: 32,768 tokens
+
+Models:
+  - TheDrummer: Cydonia 24B V4.1
+  - TheDrummer: Anubis 70B V1.1
+  - TheDrummer: Skyfall 36B V2
+  - TheDrummer: UnslopNemo 12B
+  - TheDrummer: Rocinante 12B
+
+
+======================================================================
+Vendor: Arcee AI
+======================================================================
+
+Total Models: 5
+  Free Models: 0
+  Paid Models: 5
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 5
+  Min:    $0.048000
+  Max:    $0.900000
+  Mean:   $0.475600
+  Median: $0.500000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 5
+  Min:    $0.150000
+  Max:    $3.300000
+  Mean:   $1.126000
+  Median: $0.800000
+
+Context Lengths:
+  Models with context data: 5
+  Min:    32,768 tokens
+  Max:    131,072 tokens
+  Mean:   98,304 tokens
+  Median: 131,072 tokens
+
+Models:
+  - Arcee AI: AFM 4.5B
+  - Arcee AI: Spotlight
+  - Arcee AI: Maestro Reasoning
+  - Arcee AI: Virtuoso Large
+  - Arcee AI: Coder Large
+
+
+======================================================================
+Vendor: Sao10k
+======================================================================
+
+Total Models: 5
+  Free Models: 0
+  Paid Models: 5
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 5
+  Min:    $0.040000
+  Max:    $3.000000
+  Mean:   $1.164000
+  Median: $0.650000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 5
+  Min:    $0.050000
+  Max:    $3.000000
+  Mean:   $1.206000
+  Median: $0.750000
+
+Context Lengths:
+  Models with context data: 5
+  Min:    8,192 tokens
+  Max:    131,072 tokens
+  Mean:   39,245 tokens
+  Median: 16,000 tokens
+
+Models:
+  - Sao10K: Llama 3.1 70B Hanami x1
+  - Sao10K: Llama 3.3 Euryale 70B
+  - Sao10K: Llama 3.1 Euryale 70B v2.2
+  - Sao10K: Llama 3 8B Lunaris
+  - Sao10k: Llama 3 Euryale 70B v2.1
+
+
+======================================================================
+Vendor: Amazon
+======================================================================
+
+Total Models: 4
+  Free Models: 0
+  Paid Models: 4
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 4
+  Min:    $0.035000
+  Max:    $2.500000
+  Mean:   $0.848750
+  Median: $0.430000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 4
+  Min:    $0.140000
+  Max:    $12.500000
+  Mean:   $4.020000
+  Median: $1.720000
+
+Context Lengths:
+  Models with context data: 4
+  Min:    128,000 tokens
+  Max:    1,000,000 tokens
+  Mean:   432,000 tokens
+  Median: 300,000 tokens
+
+Models:
+  - Amazon: Nova Premier 1.0
+  - Amazon: Nova Lite 1.0
+  - Amazon: Nova Micro 1.0
+  - Amazon: Nova Pro 1.0
+
+
+======================================================================
+Vendor: Minimax
+======================================================================
+
+Total Models: 4
+  Free Models: 1
+  Paid Models: 3
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 3
+  Min:    $0.200000
+  Max:    $0.400000
+  Mean:   $0.285000
+  Median: $0.255000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 3
+  Min:    $1.020000
+  Max:    $2.200000
+  Mean:   $1.440000
+  Median: $1.100000
+
+Context Lengths:
+  Models with context data: 4
+  Min:    204,800 tokens
+  Max:    1,000,192 tokens
+  Mean:   602,448 tokens
+  Median: 602,400 tokens
+
+Models:
+  - MiniMax: MiniMax M2 (free)
+  - MiniMax: MiniMax M2
+  - MiniMax: MiniMax M1
+  - MiniMax: MiniMax-01
+
+
+======================================================================
+Vendor: DeepCogito
+======================================================================
+
+Total Models: 4
+  Free Models: 0
+  Paid Models: 4
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 4
+  Min:    $0.180000
+  Max:    $3.500000
+  Mean:   $1.452500
+  Median: $1.065000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 4
+  Min:    $0.590000
+  Max:    $3.500000
+  Mean:   $1.555000
+  Median: $1.065000
+
+Context Lengths:
+  Models with context data: 4
+  Min:    32,767 tokens
+  Max:    163,840 tokens
+  Mean:   65,536 tokens
+  Median: 32,768 tokens
+
+Models:
+  - Deep Cogito: Cogito V2 Preview Llama 405B
+  - Deep Cogito: Cogito V2 Preview Llama 70B
+  - Cogito V2 Preview Llama 109B
+  - Deep Cogito: Cogito V2 Preview Deepseek 671B
+
+
+======================================================================
+Vendor: TNG Technology
+======================================================================
+
+Total Models: 4
+  Free Models: 2
+  Paid Models: 2
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $0.300000
+  Max:    $0.300000
+  Mean:   $0.300000
+  Median: $0.300000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $1.200000
+  Max:    $1.200000
+  Mean:   $1.200000
+  Median: $1.200000
+
+Context Lengths:
+  Models with context data: 4
+  Min:    163,840 tokens
+  Max:    163,840 tokens
+  Mean:   163,840 tokens
+  Median: 163,840 tokens
+
+Models:
+  - TNG: DeepSeek R1T2 Chimera (free)
+  - TNG: DeepSeek R1T2 Chimera
+  - TNG: DeepSeek R1T Chimera (free)
+  - TNG: DeepSeek R1T Chimera
+
+
+======================================================================
+Vendor: Cohere
+======================================================================
+
+Total Models: 4
+  Free Models: 0
+  Paid Models: 4
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 4
+  Min:    $0.037500
+  Max:    $2.500000
+  Mean:   $1.296875
+  Median: $1.325000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 4
+  Min:    $0.150000
+  Max:    $10.000000
+  Mean:   $5.187500
+  Median: $5.300000
+
+Context Lengths:
+  Models with context data: 4
+  Min:    128,000 tokens
+  Max:    256,000 tokens
+  Mean:   160,000 tokens
+  Median: 128,000 tokens
+
+Models:
+  - Cohere: Command A
+  - Cohere: Command R7B (12-2024)
+  - Cohere: Command R+ (08-2024)
+  - Cohere: Command R (08-2024)
+
+
+======================================================================
+Vendor: Aion Labs
+======================================================================
+
+Total Models: 3
+  Free Models: 0
+  Paid Models: 3
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 3
+  Min:    $0.200000
+  Max:    $4.000000
+  Mean:   $1.633333
+  Median: $0.700000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 3
+  Min:    $0.200000
+  Max:    $8.000000
+  Mean:   $3.200000
+  Median: $1.400000
+
+Context Lengths:
+  Models with context data: 3
+  Min:    32,768 tokens
+  Max:    131,072 tokens
+  Mean:   98,304 tokens
+  Median: 131,072 tokens
+
+Models:
+  - AionLabs: Aion-1.0
+  - AionLabs: Aion-1.0-Mini
+  - AionLabs: Aion-RP 1.0 (8B)
+
+
+======================================================================
+Vendor: OpenRouter
+======================================================================
+
+Total Models: 2
+  Free Models: 1
+  Paid Models: 1
+
+Context Lengths:
+  Models with context data: 2
+  Min:    256,000 tokens
+  Max:    2,000,000 tokens
+  Mean:   1,128,000 tokens
+  Median: 1,128,000 tokens
+
+Models:
+  - Polaris Alpha
+  - Auto Router
+
+
+======================================================================
+Vendor: Liquid AI
+======================================================================
+
+Total Models: 2
+  Free Models: 0
+  Paid Models: 2
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $0.050000
+  Max:    $0.050000
+  Mean:   $0.050000
+  Median: $0.050000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $0.100000
+  Max:    $0.100000
+  Mean:   $0.100000
+  Median: $0.100000
+
+Context Lengths:
+  Models with context data: 2
+  Min:    32,768 tokens
+  Max:    32,768 tokens
+  Mean:   32,768 tokens
+  Median: 32,768 tokens
+
+Models:
+  - LiquidAI/LFM2-8B-A1B
+  - LiquidAI/LFM2-2.6B
+
+
+======================================================================
+Vendor: Inclusion AI
+======================================================================
+
+Total Models: 2
+  Free Models: 0
+  Paid Models: 2
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $0.570000
+  Max:    $0.570000
+  Mean:   $0.570000
+  Median: $0.570000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $2.280000
+  Max:    $2.280000
+  Mean:   $2.280000
+  Median: $2.280000
+
+Context Lengths:
+  Models with context data: 2
+  Min:    131,072 tokens
+  Max:    131,072 tokens
+  Mean:   131,072 tokens
+  Median: 131,072 tokens
+
+Models:
+  - inclusionAI: Ring 1T
+  - inclusionAI: Ling-1T
+
+
+======================================================================
+Vendor: Alibaba
+======================================================================
+
+Total Models: 2
+  Free Models: 1
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.090000
+  Max:    $0.090000
+  Mean:   $0.090000
+  Median: $0.090000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.400000
+  Max:    $0.400000
+  Mean:   $0.400000
+  Median: $0.400000
+
+Context Lengths:
+  Models with context data: 2
+  Min:    131,072 tokens
+  Max:    131,072 tokens
+  Mean:   131,072 tokens
+  Median: 131,072 tokens
+
+Models:
+  - Tongyi DeepResearch 30B A3B (free)
+  - Tongyi DeepResearch 30B A3B
+
+
+======================================================================
+Vendor: Meituan
+======================================================================
+
+Total Models: 2
+  Free Models: 1
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.150000
+  Max:    $0.150000
+  Mean:   $0.150000
+  Median: $0.150000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.750000
+  Max:    $0.750000
+  Mean:   $0.750000
+  Median: $0.750000
+
+Context Lengths:
+  Models with context data: 2
+  Min:    131,072 tokens
+  Max:    131,072 tokens
+  Mean:   131,072 tokens
+  Median: 131,072 tokens
+
+Models:
+  - Meituan: LongCat Flash Chat (free)
+  - Meituan: LongCat Flash Chat
+
+
+======================================================================
+Vendor: AI21 Labs
+======================================================================
+
+Total Models: 2
+  Free Models: 0
+  Paid Models: 2
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $0.200000
+  Max:    $2.000000
+  Mean:   $1.100000
+  Median: $1.100000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $0.400000
+  Max:    $8.000000
+  Mean:   $4.200000
+  Median: $4.200000
+
+Context Lengths:
+  Models with context data: 2
+  Min:    256,000 tokens
+  Max:    256,000 tokens
+  Mean:   256,000 tokens
+  Median: 256,000 tokens
+
+Models:
+  - AI21: Jamba Mini 1.7
+  - AI21: Jamba Large 1.7
+
+
+======================================================================
+Vendor: Morph
+======================================================================
+
+Total Models: 2
+  Free Models: 0
+  Paid Models: 2
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $0.800000
+  Max:    $0.900000
+  Mean:   $0.850000
+  Median: $0.850000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $1.200000
+  Max:    $1.900000
+  Mean:   $1.550000
+  Median: $1.550000
+
+Context Lengths:
+  Models with context data: 2
+  Min:    81,920 tokens
+  Max:    262,144 tokens
+  Mean:   172,032 tokens
+  Median: 172,032 tokens
+
+Models:
+  - Morph: Morph V3 Large
+  - Morph: Morph V3 Fast
+
+
+======================================================================
+Vendor: Inception
+======================================================================
+
+Total Models: 2
+  Free Models: 0
+  Paid Models: 2
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $0.250000
+  Max:    $0.250000
+  Mean:   $0.250000
+  Median: $0.250000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $1.000000
+  Max:    $1.000000
+  Mean:   $1.000000
+  Median: $1.000000
+
+Context Lengths:
+  Models with context data: 2
+  Min:    128,000 tokens
+  Max:    128,000 tokens
+  Mean:   128,000 tokens
+  Median: 128,000 tokens
+
+Models:
+  - Inception: Mercury
+  - Inception: Mercury Coder
+
+
+======================================================================
+Vendor: Arli AI
+======================================================================
+
+Total Models: 2
+  Free Models: 1
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.030000
+  Max:    $0.030000
+  Mean:   $0.030000
+  Median: $0.030000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.110000
+  Max:    $0.110000
+  Mean:   $0.110000
+  Median: $0.110000
+
+Context Lengths:
+  Models with context data: 2
+  Min:    32,768 tokens
+  Max:    32,768 tokens
+  Mean:   32,768 tokens
+  Median: 32,768 tokens
+
+Models:
+  - ArliAI: QwQ 32B RpR v1 (free)
+  - ArliAI: QwQ 32B RpR v1
+
+
+======================================================================
+Vendor: Agentica
+======================================================================
+
+Total Models: 2
+  Free Models: 1
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.015000
+  Max:    $0.015000
+  Mean:   $0.015000
+  Median: $0.015000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.015000
+  Max:    $0.015000
+  Mean:   $0.015000
+  Median: $0.015000
+
+Context Lengths:
+  Models with context data: 2
+  Min:    96,000 tokens
+  Max:    96,000 tokens
+  Mean:   96,000 tokens
+  Median: 96,000 tokens
+
+Models:
+  - Agentica: Deepcoder 14B Preview (free)
+  - Agentica: Deepcoder 14B Preview
+
+
+======================================================================
+Vendor: Inflection AI
+======================================================================
+
+Total Models: 2
+  Free Models: 0
+  Paid Models: 2
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $2.500000
+  Max:    $2.500000
+  Mean:   $2.500000
+  Median: $2.500000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $10.000000
+  Max:    $10.000000
+  Mean:   $10.000000
+  Median: $10.000000
+
+Context Lengths:
+  Models with context data: 2
+  Min:    8,000 tokens
+  Max:    8,000 tokens
+  Mean:   8,000 tokens
+  Median: 8,000 tokens
+
+Models:
+  - Inflection: Inflection 3 Productivity
+  - Inflection: Inflection 3 Pi
+
+
+======================================================================
+Vendor: Neversleep
+======================================================================
+
+Total Models: 2
+  Free Models: 0
+  Paid Models: 2
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $0.090000
+  Max:    $1.000000
+  Mean:   $0.545000
+  Median: $0.545000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 2
+  Min:    $0.600000
+  Max:    $1.750000
+  Mean:   $1.175000
+  Median: $1.175000
+
+Context Lengths:
+  Models with context data: 2
+  Min:    4,096 tokens
+  Max:    32,768 tokens
+  Mean:   18,432 tokens
+  Median: 18,432 tokens
+
+Models:
+  - NeverSleep: Lumimaid v0.2 8B
+  - Noromaid 20B
+
+
+======================================================================
+Vendor: Kwai
+======================================================================
+
+Total Models: 1
+  Free Models: 1
+  Paid Models: 0
+
+Context Lengths:
+  Models with context data: 1
+  Min:    256,000 tokens
+  Max:    256,000 tokens
+  Mean:   256,000 tokens
+  Median: 256,000 tokens
+
+Models:
+  - Kwaipilot: Kat Coder (free)
+
+
+======================================================================
+Vendor: IBM
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.017000
+  Max:    $0.017000
+  Mean:   $0.017000
+  Median: $0.017000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.110000
+  Max:    $0.110000
+  Mean:   $0.110000
+  Median: $0.110000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    131,000 tokens
+  Max:    131,000 tokens
+  Mean:   131,000 tokens
+  Median: 131,000 tokens
+
+Models:
+  - IBM: Granite 4.0 Micro
+
+
+======================================================================
+Vendor: Relace
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.850000
+  Max:    $0.850000
+  Mean:   $0.850000
+  Median: $0.850000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $1.250000
+  Max:    $1.250000
+  Mean:   $1.250000
+  Median: $1.250000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    256,000 tokens
+  Max:    256,000 tokens
+  Mean:   256,000 tokens
+  Median: 256,000 tokens
+
+Models:
+  - Relace: Relace Apply 3
+
+
+======================================================================
+Vendor: OpenGVLab
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.070000
+  Max:    $0.070000
+  Mean:   $0.070000
+  Median: $0.070000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.260000
+  Max:    $0.260000
+  Mean:   $0.260000
+  Median: $0.260000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    32,768 tokens
+  Max:    32,768 tokens
+  Mean:   32,768 tokens
+  Median: 32,768 tokens
+
+Models:
+  - OpenGVLab: InternVL3 78B
+
+
+======================================================================
+Vendor: Stepfun AI
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.570000
+  Max:    $0.570000
+  Mean:   $0.570000
+  Median: $0.570000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $1.420000
+  Max:    $1.420000
+  Mean:   $1.420000
+  Median: $1.420000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    65,536 tokens
+  Max:    65,536 tokens
+  Mean:   65,536 tokens
+  Median: 65,536 tokens
+
+Models:
+  - StepFun: Step3
+
+
+======================================================================
+Vendor: ByteDance
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.100000
+  Max:    $0.100000
+  Mean:   $0.100000
+  Median: $0.100000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.200000
+  Max:    $0.200000
+  Mean:   $0.200000
+  Median: $0.200000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    128,000 tokens
+  Max:    128,000 tokens
+  Mean:   128,000 tokens
+  Median: 128,000 tokens
+
+Models:
+  - ByteDance: UI-TARS 7B 
+
+
+======================================================================
+Vendor: Switchpoint
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.850000
+  Max:    $0.850000
+  Mean:   $0.850000
+  Median: $0.850000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $3.400000
+  Max:    $3.400000
+  Mean:   $3.400000
+  Median: $3.400000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    131,072 tokens
+  Max:    131,072 tokens
+  Mean:   131,072 tokens
+  Median: 131,072 tokens
+
+Models:
+  - Switchpoint Router
+
+
+======================================================================
+Vendor: THUDM
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.035000
+  Max:    $0.035000
+  Mean:   $0.035000
+  Median: $0.035000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.138000
+  Max:    $0.138000
+  Mean:   $0.138000
+  Median: $0.138000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    65,536 tokens
+  Max:    65,536 tokens
+  Mean:   65,536 tokens
+  Median: 65,536 tokens
+
+Models:
+  - THUDM: GLM 4.1V 9B Thinking
+
+
+======================================================================
+Vendor: Cognitive Computations
+======================================================================
+
+Total Models: 1
+  Free Models: 1
+  Paid Models: 0
+
+Context Lengths:
+  Models with context data: 1
+  Min:    32,768 tokens
+  Max:    32,768 tokens
+  Mean:   32,768 tokens
+  Median: 32,768 tokens
+
+Models:
+  - Venice: Uncensored (free)
+
+
+======================================================================
+Vendor: Tencent
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.140000
+  Max:    $0.140000
+  Mean:   $0.140000
+  Median: $0.140000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.570000
+  Max:    $0.570000
+  Mean:   $0.570000
+  Median: $0.570000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    131,072 tokens
+  Max:    131,072 tokens
+  Mean:   131,072 tokens
+  Median: 131,072 tokens
+
+Models:
+  - Tencent: Hunyuan A13B Instruct
+
+
+======================================================================
+Vendor: EleutherAI
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.800000
+  Max:    $0.800000
+  Mean:   $0.800000
+  Median: $0.800000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $1.200000
+  Max:    $1.200000
+  Mean:   $1.200000
+  Median: $1.200000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    4,096 tokens
+  Max:    4,096 tokens
+  Mean:   4,096 tokens
+  Median: 4,096 tokens
+
+Models:
+  - EleutherAI: Llemma 7b
+
+
+======================================================================
+Vendor: AlfredPros
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.800000
+  Max:    $0.800000
+  Mean:   $0.800000
+  Median: $0.800000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $1.200000
+  Max:    $1.200000
+  Mean:   $1.200000
+  Median: $1.200000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    4,096 tokens
+  Max:    4,096 tokens
+  Mean:   4,096 tokens
+  Median: 4,096 tokens
+
+Models:
+  - AlfredPros: CodeLLaMa 7B Instruct Solidity
+
+
+======================================================================
+Vendor: Allen Institute for AI
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.200000
+  Max:    $0.200000
+  Mean:   $0.200000
+  Median: $0.200000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.350000
+  Max:    $0.350000
+  Mean:   $0.350000
+  Median: $0.350000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    4,096 tokens
+  Max:    4,096 tokens
+  Mean:   4,096 tokens
+  Median: 4,096 tokens
+
+Models:
+  - AllenAI: Olmo 2 32B Instruct
+
+
+======================================================================
+Vendor: Raifle
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $4.500000
+  Max:    $4.500000
+  Mean:   $4.500000
+  Median: $4.500000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $4.500000
+  Max:    $4.500000
+  Mean:   $4.500000
+  Median: $4.500000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    16,000 tokens
+  Max:    16,000 tokens
+  Mean:   16,000 tokens
+  Median: 16,000 tokens
+
+Models:
+  - SorcererLM 8x22B
+
+
+======================================================================
+Vendor: Anthracite
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $3.000000
+  Max:    $3.000000
+  Mean:   $3.000000
+  Median: $3.000000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $5.000000
+  Max:    $5.000000
+  Mean:   $5.000000
+  Median: $5.000000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    16,384 tokens
+  Max:    16,384 tokens
+  Mean:   16,384 tokens
+  Median: 16,384 tokens
+
+Models:
+  - Magnum v4 72B
+
+
+======================================================================
+Vendor: Alpindale
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $4.000000
+  Max:    $4.000000
+  Mean:   $4.000000
+  Median: $4.000000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $5.500000
+  Max:    $5.500000
+  Mean:   $5.500000
+  Median: $5.500000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    6,144 tokens
+  Max:    6,144 tokens
+  Mean:   6,144 tokens
+  Median: 6,144 tokens
+
+Models:
+  - Goliath 120B
+
+
+======================================================================
+Vendor: Mancer
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $1.125000
+  Max:    $1.125000
+  Mean:   $1.125000
+  Median: $1.125000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $1.125000
+  Max:    $1.125000
+  Mean:   $1.125000
+  Median: $1.125000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    8,000 tokens
+  Max:    8,000 tokens
+  Mean:   8,000 tokens
+  Median: 8,000 tokens
+
+Models:
+  - Mancer: Weaver (alpha)
+
+
+======================================================================
+Vendor: Undi95
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.450000
+  Max:    $0.450000
+  Mean:   $0.450000
+  Median: $0.450000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.650000
+  Max:    $0.650000
+  Mean:   $0.650000
+  Median: $0.650000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    6,144 tokens
+  Max:    6,144 tokens
+  Mean:   6,144 tokens
+  Median: 6,144 tokens
+
+Models:
+  - ReMM SLERP 13B
+
+
+======================================================================
+Vendor: Gryphe
+======================================================================
+
+Total Models: 1
+  Free Models: 0
+  Paid Models: 1
+
+Input Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.060000
+  Max:    $0.060000
+  Mean:   $0.060000
+  Median: $0.060000
+
+Output Pricing (per 1M tokens):
+  Models with pricing: 1
+  Min:    $0.060000
+  Max:    $0.060000
+  Mean:   $0.060000
+  Median: $0.060000
+
+Context Lengths:
+  Models with context data: 1
+  Min:    4,096 tokens
+  Max:    4,096 tokens
+  Mean:   4,096 tokens
+  Median: 4,096 tokens
+
+Models:
+  - MythoMax 13B
+

analysis/vendors/vendor_distribution.txt

@@ -0,0 +1,66 @@
+OpenRouter API - Vendor Distribution
+======================================================================
+
+Total Models: 342
+Total Vendors: 55
+
+Market Share by Model Count:
+----------------------------------------------------------------------
+Vendor                                Models      Share
+----------------------------------------------------------------------
+OpenAI                                    47     13.74%
+Qwen                                      46     13.45%
+Mistral AI                                36     10.53%
+Google                                    24      7.02%
+Meta                                      21      6.14%
+DeepSeek                                  19      5.56%
+Anthropic                                 13      3.80%
+Microsoft                                  9      2.63%
+Moonshot AI                                7      2.05%
+NVIDIA                                     7      2.05%
+Z-AI                                       7      2.05%
+xAI                                        7      2.05%
+Nous Research                              7      2.05%
+Perplexity                                 6      1.75%
+Baidu                                      5      1.46%
+TheDrummer                                 5      1.46%
+Arcee AI                                   5      1.46%
+Sao10k                                     5      1.46%
+Amazon                                     4      1.17%
+Minimax                                    4      1.17%
+DeepCogito                                 4      1.17%
+TNG Technology                             4      1.17%
+Cohere                                     4      1.17%
+Aion Labs                                  3      0.88%
+OpenRouter                                 2      0.58%
+Liquid AI                                  2      0.58%
+Inclusion AI                               2      0.58%
+Alibaba                                    2      0.58%
+Meituan                                    2      0.58%
+AI21 Labs                                  2      0.58%
+Morph                                      2      0.58%
+Inception                                  2      0.58%
+Arli AI                                    2      0.58%
+Agentica                                   2      0.58%
+Inflection AI                              2      0.58%
+Neversleep                                 2      0.58%
+Kwai                                       1      0.29%
+IBM                                        1      0.29%
+Relace                                     1      0.29%
+OpenGVLab                                  1      0.29%
+Stepfun AI                                 1      0.29%
+ByteDance                                  1      0.29%
+Switchpoint                                1      0.29%
+THUDM                                      1      0.29%
+Cognitive Computations                     1      0.29%
+Tencent                                    1      0.29%
+EleutherAI                                 1      0.29%
+AlfredPros                                 1      0.29%
+Allen Institute for AI                     1      0.29%
+Raifle                                     1      0.29%
+Anthracite                                 1      0.29%
+Alpindale                                  1      0.29%
+Mancer                                     1      0.29%
+Undi95                                     1      0.29%
+Gryphe                                     1      0.29%
+

analysis/vendors/vendor_stats.json

@@ -0,0 +1,1903 @@
+{
+  "Kwai": {
+    "vendor": "Kwai",
+    "total_models": 1,
+    "free_models": 1,
+    "paid_models": 0,
+    "model_names": [
+      "Kwaipilot: Kat Coder (free)"
+    ],
+    "input_pricing": null,
+    "output_pricing": null,
+    "context_lengths": {
+      "count": 1,
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+      "max": 256000,
+      "mean": 256000,
+      "median": 256000
+    }
+  },
+  "Moonshot AI": {
+    "vendor": "Moonshot AI",
+    "total_models": 7,
+    "free_models": 1,
+    "paid_models": 6,
+    "model_names": [
+      "MoonshotAI: Kimi Linear 48B A3B Instruct",
+      "MoonshotAI: Kimi K2 Thinking",
+      "MoonshotAI: Kimi K2 0905",
+      "MoonshotAI: Kimi K2 0905 (exacto)",
+      "MoonshotAI: Kimi K2 0711 (free)",
+      "MoonshotAI: Kimi K2 0711",
+      "MoonshotAI: Kimi Dev 72B"
+    ],
+    "input_pricing": {
+      "count": 6,
+      "min": 0.29,
+      "max": 0.6,
+      "mean": 0.44666666666666666,
+      "median": 0.445
+    },
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+      "min": 0.6,
+      "max": 2.5,
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+      "median": 2.15
+    },
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+      "count": 7,
+      "min": 32768,
+      "max": 1048576,
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+    }
+  },
+  "OpenRouter": {
+    "vendor": "OpenRouter",
+    "total_models": 2,
+    "free_models": 1,
+    "paid_models": 1,
+    "model_names": [
+      "Polaris Alpha",
+      "Auto Router"
+    ],
+    "input_pricing": null,
+    "output_pricing": null,
+    "context_lengths": {
+      "count": 2,
+      "min": 256000,
+      "max": 2000000,
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+      "median": 1128000.0
+    }
+  },
+  "Amazon": {
+    "vendor": "Amazon",
+    "total_models": 4,
+    "free_models": 0,
+    "paid_models": 4,
+    "model_names": [
+      "Amazon: Nova Premier 1.0",
+      "Amazon: Nova Lite 1.0",
+      "Amazon: Nova Micro 1.0",
+      "Amazon: Nova Pro 1.0"
+    ],
+    "input_pricing": {
+      "count": 4,
+      "min": 0.035,
+      "max": 2.5,
+      "mean": 0.84875,
+      "median": 0.42999999999999994
+    },
+    "output_pricing": {
+      "count": 4,
+      "min": 0.14,
+      "max": 12.5,
+      "mean": 4.02,
+      "median": 1.7199999999999998
+    },
+    "context_lengths": {
+      "count": 4,
+      "min": 128000,
+      "max": 1000000,
+      "mean": 432000,
+      "median": 300000.0
+    }
+  },
+  "Perplexity": {
+    "vendor": "Perplexity",
+    "total_models": 6,
+    "free_models": 0,
+    "paid_models": 6,
+    "model_names": [
+      "Perplexity: Sonar Pro Search",
+      "Perplexity: Sonar Reasoning Pro",
+      "Perplexity: Sonar Pro",
+      "Perplexity: Sonar Deep Research",
+      "Perplexity: Sonar Reasoning",
+      "Perplexity: Sonar"
+    ],
+    "input_pricing": {
+      "count": 6,
+      "min": 1.0,
+      "max": 3.0,
+      "mean": 2.0,
+      "median": 2.0
+    },
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+      "mean": 8.666666666666666,
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+      "min": 127000,
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+    }
+  },
+  "Mistral AI": {
+    "vendor": "Mistral AI",
+    "total_models": 36,
+    "free_models": 5,
+    "paid_models": 31,
+    "model_names": [
+      "Mistral: Voxtral Small 24B 2507",
+      "Mistral: Mistral Medium 3.1",
+      "Mistral: Codestral 2508",
+      "Mistral: Devstral Medium",
+      "Mistral: Devstral Small 1.1",
+      "Mistral: Mistral Small 3.2 24B (free)",
+      "Mistral: Mistral Small 3.2 24B",
+      "Mistral: Magistral Small 2506",
+      "Mistral: Magistral Medium 2506 (thinking)",
+      "Mistral: Magistral Medium 2506",
+      "Mistral: Devstral Small 2505",
+      "Mistral: Mistral Medium 3",
+      "Mistral: Mistral Small 3.1 24B (free)",
+      "Mistral: Mistral Small 3.1 24B",
+      "Mistral: Saba",
+      "Mistral: Mistral Small 3 (free)",
+      "Mistral: Mistral Small 3",
+      "Mistral: Codestral 2501",
+      "Mistral Large 2411",
+      "Mistral Large 2407",
+      "Mistral: Pixtral Large 2411",
+      "Mistral: Ministral 3B",
+      "Mistral: Ministral 8B",
+      "Mistral: Pixtral 12B",
+      "Mistral: Mistral Nemo (free)",
+      "Mistral: Mistral Nemo",
+      "Mistral: Mistral 7B Instruct (free)",
+      "Mistral: Mistral 7B Instruct",
+      "Mistral: Mistral 7B Instruct v0.3",
+      "Mistral: Mixtral 8x22B Instruct",
+      "Mistral Large",
+      "Mistral Tiny",
+      "Mistral Small",
+      "Mistral: Mistral 7B Instruct v0.2",
+      "Mistral: Mixtral 8x7B Instruct",
+      "Mistral: Mistral 7B Instruct v0.1"
+    ],
+    "input_pricing": {
+      "count": 31,
+      "min": 0.02,
+      "max": 2.0,
+      "mean": 0.5969677419354839,
+      "median": 0.19999999999999998
+    },
+    "output_pricing": {
+      "count": 31,
+      "min": 0.04,
+      "max": 6.0,
+      "mean": 1.7176774193548388,
+      "median": 0.54
+    },
+    "context_lengths": {
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+      "min": 2824,
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+      "mean": 91244.66666666667,
+      "median": 112000.0
+    }
+  },
+  "OpenAI": {
+    "vendor": "OpenAI",
+    "total_models": 47,
+    "free_models": 1,
+    "paid_models": 46,
+    "model_names": [
+      "OpenAI: gpt-oss-safeguard-20b",
+      "OpenAI: GPT-5 Image Mini",
+      "OpenAI: GPT-5 Image",
+      "OpenAI: o3 Deep Research",
+      "OpenAI: o4 Mini Deep Research",
+      "OpenAI: GPT-5 Pro",
+      "OpenAI: GPT-5 Codex",
+      "OpenAI: GPT-4o Audio",
+      "OpenAI: GPT-5 Chat",
+      "OpenAI: GPT-5",
+      "OpenAI: GPT-5 Mini",
+      "OpenAI: GPT-5 Nano",
+      "OpenAI: gpt-oss-120b",
+      "OpenAI: gpt-oss-120b (exacto)",
+      "OpenAI: gpt-oss-20b (free)",
+      "OpenAI: gpt-oss-20b",
+      "OpenAI: o3 Pro",
+      "OpenAI: Codex Mini",
+      "OpenAI: o4 Mini High",
+      "OpenAI: o3",
+      "OpenAI: o4 Mini",
+      "OpenAI: GPT-4.1",
+      "OpenAI: GPT-4.1 Mini",
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+      "median": 5.0
+    },
+    "context_lengths": {
+      "count": 1,
+      "min": 16384,
+      "max": 16384,
+      "mean": 16384,
+      "median": 16384
+    }
+  },
+  "Inflection AI": {
+    "vendor": "Inflection AI",
+    "total_models": 2,
+    "free_models": 0,
+    "paid_models": 2,
+    "model_names": [
+      "Inflection: Inflection 3 Productivity",
+      "Inflection: Inflection 3 Pi"
+    ],
+    "input_pricing": {
+      "count": 2,
+      "min": 2.5,
+      "max": 2.5,
+      "mean": 2.5,
+      "median": 2.5
+    },
+    "output_pricing": {
+      "count": 2,
+      "min": 10.0,
+      "max": 10.0,
+      "mean": 10.0,
+      "median": 10.0
+    },
+    "context_lengths": {
+      "count": 2,
+      "min": 8000,
+      "max": 8000,
+      "mean": 8000,
+      "median": 8000.0
+    }
+  },
+  "Neversleep": {
+    "vendor": "Neversleep",
+    "total_models": 2,
+    "free_models": 0,
+    "paid_models": 2,
+    "model_names": [
+      "NeverSleep: Lumimaid v0.2 8B",
+      "Noromaid 20B"
+    ],
+    "input_pricing": {
+      "count": 2,
+      "min": 0.09,
+      "max": 1.0,
+      "mean": 0.545,
+      "median": 0.545
+    },
+    "output_pricing": {
+      "count": 2,
+      "min": 0.6,
+      "max": 1.75,
+      "mean": 1.175,
+      "median": 1.175
+    },
+    "context_lengths": {
+      "count": 2,
+      "min": 4096,
+      "max": 32768,
+      "mean": 18432,
+      "median": 18432.0
+    }
+  },
+  "Alpindale": {
+    "vendor": "Alpindale",
+    "total_models": 1,
+    "free_models": 0,
+    "paid_models": 1,
+    "model_names": [
+      "Goliath 120B"
+    ],
+    "input_pricing": {
+      "count": 1,
+      "min": 4.0,
+      "max": 4.0,
+      "mean": 4.0,
+      "median": 4.0
+    },
+    "output_pricing": {
+      "count": 1,
+      "min": 5.5,
+      "max": 5.5,
+      "mean": 5.5,
+      "median": 5.5
+    },
+    "context_lengths": {
+      "count": 1,
+      "min": 6144,
+      "max": 6144,
+      "mean": 6144,
+      "median": 6144
+    }
+  },
+  "Mancer": {
+    "vendor": "Mancer",
+    "total_models": 1,
+    "free_models": 0,
+    "paid_models": 1,
+    "model_names": [
+      "Mancer: Weaver (alpha)"
+    ],
+    "input_pricing": {
+      "count": 1,
+      "min": 1.125,
+      "max": 1.125,
+      "mean": 1.125,
+      "median": 1.125
+    },
+    "output_pricing": {
+      "count": 1,
+      "min": 1.125,
+      "max": 1.125,
+      "mean": 1.125,
+      "median": 1.125
+    },
+    "context_lengths": {
+      "count": 1,
+      "min": 8000,
+      "max": 8000,
+      "mean": 8000,
+      "median": 8000
+    }
+  },
+  "Undi95": {
+    "vendor": "Undi95",
+    "total_models": 1,
+    "free_models": 0,
+    "paid_models": 1,
+    "model_names": [
+      "ReMM SLERP 13B"
+    ],
+    "input_pricing": {
+      "count": 1,
+      "min": 0.44999999999999996,
+      "max": 0.44999999999999996,
+      "mean": 0.44999999999999996,
+      "median": 0.44999999999999996
+    },
+    "output_pricing": {
+      "count": 1,
+      "min": 0.65,
+      "max": 0.65,
+      "mean": 0.65,
+      "median": 0.65
+    },
+    "context_lengths": {
+      "count": 1,
+      "min": 6144,
+      "max": 6144,
+      "mean": 6144,
+      "median": 6144
+    }
+  },
+  "Gryphe": {
+    "vendor": "Gryphe",
+    "total_models": 1,
+    "free_models": 0,
+    "paid_models": 1,
+    "model_names": [
+      "MythoMax 13B"
+    ],
+    "input_pricing": {
+      "count": 1,
+      "min": 0.06,
+      "max": 0.06,
+      "mean": 0.06,
+      "median": 0.06
+    },
+    "output_pricing": {
+      "count": 1,
+      "min": 0.06,
+      "max": 0.06,
+      "mean": 0.06,
+      "median": 0.06
+    },
+    "context_lengths": {
+      "count": 1,
+      "min": 4096,
+      "max": 4096,
+      "mean": 4096,
+      "median": 4096
+    }
+  }
+}

analysis/vendors/vendor_summary.txt

@@ -0,0 +1,31 @@
+OpenRouter API - Models by Vendor Summary
+======================================================================
+
+Total Vendors: 55
+Total Models: 342
+
+Top Vendors by Model Count:
+----------------------------------------------------------------------
+Vendor                           Models   Free   Paid
+----------------------------------------------------------------------
+OpenAI                               47      1     46
+Qwen                                 46      8     38
+Mistral AI                           36      5     31
+Google                               24      6     18
+Meta                                 21      5     16
+DeepSeek                             19      6     13
+Anthropic                            13      0     13
+Microsoft                             9      1      8
+Moonshot AI                           7      1      6
+NVIDIA                                7      2      5
+Z-AI                                  7      1      6
+xAI                                   7      0      7
+Nous Research                         7      1      6
+Perplexity                            6      0      6
+Baidu                                 5      0      5
+TheDrummer                            5      0      5
+Arcee AI                              5      0      5
+Sao10k                                5      0      5
+Amazon                                4      0      4
+Minimax                               4      1      3
+