xujfcn
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Crazyrouter-Model-Comparison

@@ -1,221 +1,176 @@
 ---
 license: mit
 tags:
-  - tutorial
-  - crazyrouter
   - model-comparison
   - benchmark
-  - llm
-  - evaluation
 language:
   - en
   - zh
 ---
-# ⚖️ AI Model Comparison with Crazyrouter
-> Compare GPT-4o vs Claude vs Gemini vs DeepSeek — same prompt, same API, side by side.
-One of the biggest advantages of [Crazyrouter](https://crazyrouter.com/?utm_source=huggingface&utm_medium=tutorial&utm_campaign=dev_community) is the ability to test multiple models instantly. No separate accounts, no different SDKs. Just change the model name.
----
-## Quick Comparison Script
-```python
-from openai import OpenAI
-import time
-client = OpenAI(
-    base_url="https://crazyrouter.com/v1",
-    api_key="sk-your-crazyrouter-key"
-)
-MODELS = [
-    "gpt-4o",
-    "gpt-4o-mini",
-    "claude-sonnet-4-20250514",
-    "claude-haiku-3.5",
-    "gemini-2.0-flash",
-    "deepseek-chat",
-    "deepseek-reasoner",
-]
-PROMPT = "Explain the difference between TCP and UDP in exactly 3 sentences."
-print(f"Prompt: {PROMPT}\n")
-print("=" * 60)
-for model in MODELS:
-    try:
-        start = time.time()
-        response = client.chat.completions.create(
-            model=model,
-            messages=[{"role": "user", "content": PROMPT}],
-            max_tokens=200
-        )
-        elapsed = time.time() - start
-        content = response.choices[0].message.content
-        tokens = response.usage.total_tokens
-        print(f"\n🤖 {model}")
-        print(f"⏱️  {elapsed:.2f}s | 📊 {tokens} tokens")
-        print(f"💬 {content}")
-        print("-" * 60)
-    except Exception as e:
-        print(f"\n❌ {model}: {e}")
-        print("-" * 60)
-```
----
-## Benchmark: Speed Test
 ```python
-import time
 from openai import OpenAI
 client = OpenAI(
-    base_url="https://crazyrouter.com/v1",
-    api_key="sk-your-crazyrouter-key"
 )
-def benchmark(model, prompt, runs=3):
-    times = []
-    for _ in range(runs):
-        start = time.time()
-        client.chat.completions.create(
-            model=model,
-            messages=[{"role": "user", "content": prompt}],
-            max_tokens=100
-        )
-        times.append(time.time() - start)
-    avg = sum(times) / len(times)
-    return avg
-models = ["gpt-4o-mini", "claude-haiku-3.5", "gemini-2.0-flash", "deepseek-chat"]
-prompt = "What is 2+2? Reply with just the number."
-print("Speed Benchmark (avg of 3 runs)")
-print("=" * 40)
-for m in models:
-    avg = benchmark(m, prompt)
-    print(f"{m:30s} {avg:.2f}s")
-```
----
-## Coding Comparison
-```python
-CODING_PROMPT = """Write a Python function that:
-1. Takes a list of integers
-2. Returns the longest increasing subsequence
-3. Include type hints and a docstring
-"""
-CODING_MODELS = [
-    "gpt-4o",
     "claude-sonnet-4-20250514",
     "deepseek-chat",
-    "gemini-2.0-flash",
 ]
-for model in CODING_MODELS:
     response = client.chat.completions.create(
         model=model,
-        messages=[{"role": "user", "content": CODING_PROMPT}],
-        max_tokens=500
     )
-    print(f"\n{'='*60}")
-    print(f"🤖 {model}")
-    print(f"{'='*60}")
-    print(response.choices[0].message.content)
 ```
----
-## Reasoning Comparison
-Test models that support chain-of-thought reasoning:
-```python
-REASONING_PROMPT = """A farmer has 17 sheep. All but 9 die. How many sheep are left?
-Think step by step."""
-REASONING_MODELS = [
-    "gpt-4o",
-    "o3-mini",
-    "deepseek-reasoner",
-    "claude-sonnet-4-20250514",
-]
-for model in REASONING_MODELS:
-    response = client.chat.completions.create(
-        model=model,
-        messages=[{"role": "user", "content": REASONING_PROMPT}],
-        max_tokens=300
-    )
-    print(f"\n🤖 {model}: {response.choices[0].message.content[:200]}")
-```
----
-## Cost Comparison
-```python
-# Approximate pricing per 1M tokens (input/output)
-PRICING = {
-    "gpt-4o":           {"input": 2.50, "output": 10.00},
-    "gpt-4o-mini":      {"input": 0.15, "output": 0.60},
-    "claude-sonnet-4-20250514": {"input": 3.00, "output": 15.00},
-    "claude-haiku-3.5": {"input": 0.80, "output": 4.00},
-    "gemini-2.0-flash": {"input": 0.10, "output": 0.40},
-    "deepseek-chat":    {"input": 0.14, "output": 0.28},
-}
-def estimate_cost(model, input_tokens, output_tokens):
-    p = PRICING.get(model, {"input": 0, "output": 0})
-    return (input_tokens * p["input"] + output_tokens * p["output"]) / 1_000_000
-# Example: 1000 requests, avg 500 input + 200 output tokens each
-requests = 1000
-input_tok = 500
-output_tok = 200
-print(f"Cost estimate for {requests} requests ({input_tok} in / {output_tok} out tokens each):\n")
-for model, price in PRICING.items():
-    cost = requests * estimate_cost(model, input_tok, output_tok)
-    print(f"  {model:30s} ${cost:.4f}")
-```
----
-## When to Use Which Model
-| Use Case | Recommended Model | Why |
-|----------|------------------|-----|
-| General chat | `gpt-4o-mini` | Fast, cheap, good quality |
-| Complex analysis | `gpt-4o` or `claude-sonnet-4-20250514` | Best reasoning |
-| Coding | `deepseek-chat` or `claude-sonnet-4-20250514` | Strong code generation |
-| Long documents | `gemini-2.0-flash` | 1M token context |
-| Math/Logic | `deepseek-reasoner` or `o3-mini` | Chain-of-thought |
-| Budget tasks | `deepseek-chat` | $0.14/1M input |
-| Speed critical | `gemini-2.0-flash` | Fastest response |
 ---
-## Try It Live
-👉 [Crazyrouter Demo on Hugging Face](https://huggingface.co/spaces/xujfcn/Crazyrouter-Demo) — switch models in real-time
----
-## Links
-- 🌐 [Crazyrouter](https://crazyrouter.com/?utm_source=huggingface&utm_medium=tutorial&utm_campaign=dev_community)
-- 📖 [Getting Started](https://huggingface.co/xujfcn/Crazyrouter-Getting-Started)
-- 🔗 [LangChain Guide](https://huggingface.co/xujfcn/Crazyrouter-LangChain-Guide)
-- 💰 [Pricing](https://huggingface.co/spaces/xujfcn/Crazyrouter-Pricing)
-- 💬 [Telegram](https://t.me/crazyrouter)
-- 🐦 [Twitter @metaviiii](https://twitter.com/metaviiii)

 ---
 license: mit
 tags:
+  - llm
   - model-comparison
   - benchmark
+  - claude
+  - gpt
+  - gemini
+  - deepseek
+  - ai-models
+  - "2026"
 language:
   - en
   - zh
 ---
+# 🏆 Top AI Models Comparison — May 2026
+A practical, up-to-date comparison of the best large language models available via API as of **May 4, 2026**. Focused on real-world performance, pricing, and use-case fit — not just benchmark scores.
+> **Last updated: 2026-05-04** | Contributions welcome via PR
+## 📊 Model Overview
+| Model | Provider | Context Window | Input Price (per 1M tokens) | Output Price (per 1M tokens) | Strengths |
+|-------|----------|---------------|----------------------------|-----------------------------|-----------|
+| **Claude 4 Sonnet** | Anthropic | 200K | $3.00 | $15.00 | Best overall coding + reasoning, extended thinking |
+| **Claude 3.7 Sonnet** | Anthropic | 200K | $3.00 | $15.00 | Excellent balance of speed and quality |
+| **Claude 3.5 Haiku** | Anthropic | 200K | $0.80 | $4.00 | Fast and cheap, great for high-volume tasks |
+| **GPT-4.1** | OpenAI | 1M | $2.00 | $8.00 | Large context, strong instruction following |
+| **GPT-4.1 mini** | OpenAI | 1M | $0.40 | $1.60 | Budget-friendly, good for simple tasks |
+| **GPT-4o** | OpenAI | 128K | $2.50 | $10.00 | Multimodal (text + image + audio) |
+| **Gemini 2.5 Pro** | Google | 1M | $1.25 / $2.50 | $10.00 | Huge context, strong reasoning + thinking |
+| **Gemini 2.5 Flash** | Google | 1M | $0.15 | $0.60 / $3.50 | Extremely fast and cheap |
+| **DeepSeek V3** | DeepSeek | 128K | $0.27 | $1.10 | Best value for money, strong coding |
+| **DeepSeek R1** | DeepSeek | 128K | $0.55 | $2.19 | Deep reasoning with chain-of-thought |
+| **Llama 4 Maverick** | Meta | 1M | Varies | Varies | Open-weight, self-hostable |
+| **Qwen3 235B** | Alibaba | 128K | Varies | Varies | Top open-source, hybrid thinking |
+> 💡 Prices are official API rates. Third-party providers often offer 20-50% discounts.
+## 🎯 Best Model by Use Case
+### Coding & Development
+| Task | Recommended | Why |
+|------|------------|-----|
+| Complex refactoring | Claude 4 Sonnet | Best code understanding and generation |
+| Quick code completion | Claude 3.5 Haiku | Fast, accurate, low cost |
+| Debugging | Claude 4 Sonnet / GPT-4.1 | Strong reasoning about code logic |
+| Code review | Claude 3.7 Sonnet | Good balance of depth and speed |
+### Writing & Content
+| Task | Recommended | Why |
+|------|------------|-----|
+| Long-form articles | Claude 4 Sonnet | Natural writing style, follows instructions well |
+| Translation | Gemini 2.5 Pro | Strong multilingual capabilities |
+| Summarization | Gemini 2.5 Flash | Fast, cheap, handles long docs |
+| Creative writing | Claude 4 Sonnet | Most natural and nuanced output |
+### Data & Analysis
+| Task | Recommended | Why |
+|------|------------|-----|
+| Data extraction | GPT-4.1 | Reliable structured output, large context |
+| Math / Logic | DeepSeek R1 | Deep chain-of-thought reasoning |
+| Research analysis | Gemini 2.5 Pro | 1M context for large document sets |
+| Classification | Gemini 2.5 Flash / GPT-4.1 mini | Cheap and fast for high volume |
+### Multimodal
+| Task | Recommended | Why |
+|------|------------|-----|
+| Image understanding | GPT-4o / Gemini 2.5 Pro | Native vision capabilities |
+| Document OCR | Gemini 2.5 Pro | Handles PDFs and scanned docs well |
+| Audio transcription | GPT-4o | Native audio input support |
+## ⚡ Speed vs Quality Tiers
+```
+Tier 1 — Maximum Quality (slower, higher cost)
+├── Claude 4 Sonnet (extended thinking)
+├── Gemini 2.5 Pro (thinking mode)
+└── DeepSeek R1
+Tier 2 — Balanced (good quality, reasonable speed)
+├── Claude 3.7 Sonnet
+├── GPT-4.1
+└── GPT-4o
+Tier 3 — Fast & Cheap (high throughput)
+├── Claude 3.5 Haiku
+├── Gemini 2.5 Flash
+├── GPT-4.1 mini
+└── DeepSeek V3
+```
+## 💰 Cost Efficiency Ranking
+For typical workloads (mixed input/output), approximate cost per 1M total tokens:
+| Rank | Model | ~Cost per 1M tokens | Quality |
+|------|-------|---------------------|---------|
+| 1 | Gemini 2.5 Flash | ~$0.40 | Good |
+| 2 | GPT-4.1 mini | ~$1.00 | Good |
+| 3 | DeepSeek V3 | ~$0.70 | Very Good |
+| 4 | Claude 3.5 Haiku | ~$2.40 | Very Good |
+| 5 | DeepSeek R1 | ~$1.40 | Excellent (reasoning) |
+| 6 | GPT-4.1 | ~$5.00 | Excellent |
+| 7 | Gemini 2.5 Pro | ~$6.00 | Excellent |
+| 8 | Claude 4 Sonnet | ~$9.00 | Top tier |
+## 🔧 Quick Start: Access All Models with One API
+Instead of managing separate API keys for each provider, you can use an API gateway to access all models through a single OpenAI-compatible endpoint.
+**Example with Python (OpenAI SDK):**
 ```python
 from openai import OpenAI
+# Works with any OpenAI-compatible gateway
 client = OpenAI(
+    api_key="your-api-key",
+    base_url="https://your-gateway.com/v1"
 )
+# Switch models by just changing the model name
+models = [
     "claude-sonnet-4-20250514",
+    "gpt-4.1",
+    "gemini-2.5-pro-preview-05-06",
     "deepseek-chat",
 ]
+for model in models:
     response = client.chat.completions.create(
         model=model,
+        messages=[{"role": "user", "content": "Explain quicksort in 3 sentences"}],
     )
+    print(f"{model}: {response.choices[0].message.content[:100]}...")
 ```
+**Popular API gateways:** [Crazyrouter](https://crazyrouter.com), [OpenRouter](https://openrouter.ai), [AIHubMix](https://aihubmix.com)
+## 📈 Key Trends — May 2026
+1. **Extended thinking is mainstream** — Claude 4 Sonnet, Gemini 2.5 Pro, and DeepSeek R1 all support chain-of-thought reasoning modes
+2. **1M+ context is the new normal** — GPT-4.1, Gemini 2.5, and Llama 4 all support 1M tokens
+3. **Open-source closing the gap** — Qwen3, Llama 4, and DeepSeek V3 rival proprietary models
+4. **Prices keep dropping** — Flash/mini tiers make AI accessible for high-volume production use
+5. **Multimodal expanding** — Vision, audio, and video understanding becoming standard features
+## 📚 Methodology
+This comparison is based on:
+- Official API documentation and pricing pages
+- Public benchmarks (LMSYS Chatbot Arena, LiveBench, SWE-bench)
+- Community feedback and real-world usage reports
+- Our own testing across coding, writing, and analysis tasks
+We update this guide monthly. Prices and capabilities change frequently — always check the provider's official docs for the latest info.
+## 🤝 Contributing
+Found outdated info or want to add a model? PRs are welcome! Please include:
+- Source link for any pricing or capability claims
+- Date of verification
+## 📖 Related Resources
+- [LMSYS Chatbot Arena](https://chat.lmsys.org/) — Live model rankings by human preference
+- [LiveBench](https://livebench.ai/) — Contamination-free LLM benchmark
+- [Artificial Analysis](https://artificialanalysis.ai/) — Speed and pricing tracker
 ---
+⭐ Star this repo if you find it useful — it helps others discover it!