model_slug stringlengths 2 39 | model_name stringlengths 2 46 | provider stringclasses 61
values | provider_slug stringclasses 57
values | input_price_per_mtok float64 0 150 ⌀ | output_price_per_mtok float64 0 600 ⌀ | context_window int64 0 2M | is_open_source bool 2
classes | release_date stringdate 2023-05-28 00:00:00 2026-03-27 00:00:00 | model_type stringclasses 4
values | avg_benchmark_score null 3.2 78 ⌀ | num_benchmarks_tested int64 0 23 | price_per_score_point null 0 0.66 ⌀ |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
bodybuilder | Body Builder (beta) | openrouter | openrouter | null | null | 128,000 | false | 2025-12-05 | text | null | 0 | null |
auto | Auto Router | openrouter | openrouter | null | null | 2,000,000 | false | 2023-11-08 | image | null | 0 | null |
lfm2-8b-a1b | LFM2-8B-A1B | liquid | liquid | 0.01 | 0.02 | 32,768 | true | 2025-10-20 | text | null | 0 | null |
lfm-2-2-6b | LFM2-2.6B | liquid | liquid | 0.01 | 0.02 | 32,768 | true | 2025-10-20 | text | null | 0 | null |
granite-4-0-h-micro | Granite 4.0 Micro | ibm-granite | ibm-granite | 0.017 | 0.11 | 131,000 | true | 2025-10-20 | text | null | 0 | null |
mistral-nemo | Mistral Nemo | Mistral AI | mistral | 0.02 | 0.04 | 131,072 | true | 2024-07-19 | text | null | 5 | null |
llama-3-1-8b-instruct | Llama 3.1 8B Instruct | Meta | meta | 0.02 | 0.05 | 16,384 | true | 2024-07-23 | text | null | 8 | null |
gemma-3n-e4b-it | Gemma 3n 4B | Google DeepMind | google | 0.02 | 0.04 | 32,768 | true | 2025-05-20 | text | null | 0 | null |
llama-guard-3-8b | Llama Guard 3 8B | Meta | meta | 0.02 | 0.06 | 131,072 | true | 2025-02-12 | text | null | 0 | null |
llama-3-2-1b-instruct | Llama 3.2 1B Instruct | Meta | meta | 0.027 | 0.2 | 60,000 | true | 2024-09-25 | text | null | 0 | null |
qwen2-5-coder-7b-instruct | Qwen2.5 Coder 7B Instruct | Alibaba Qwen | alibaba | 0.03 | 0.09 | 32,768 | true | 2025-04-15 | text | null | 5 | null |
llama-3-8b-instruct | Llama 3 8B Instruct | Meta | meta | 0.03 | 0.04 | 8,192 | true | 2024-04-18 | text | null | 9 | null |
gemma-2-9b-it | Gemma 2 9B | Google DeepMind | google | 0.03 | 0.09 | 8,192 | true | 2024-06-28 | text | null | 6 | null |
gpt-oss-20b | gpt-oss-20b | OpenAI | openai | 0.03 | 0.11 | 131,072 | true | 2025-08-05 | text | null | 12 | null |
lfm-2-24b-a2b | LFM2-24B-A2B | liquid | liquid | 0.03 | 0.12 | 32,768 | true | 2026-02-25 | text | null | 0 | null |
mistral-small-3-1-24b-instruct | Mistral Small 3.1 24B | Mistral AI | mistral | 0.03 | 0.11 | 131,072 | true | 2025-03-17 | multimodal | null | 0 | null |
qwen-turbo | Qwen-Turbo | Alibaba Qwen | alibaba | 0.0325 | 0.13 | 131,072 | true | 2025-02-01 | text | null | 0 | null |
nova-micro-v1 | Nova Micro 1.0 | Amazon | amazon | 0.035 | 0.14 | 128,000 | false | 2024-12-05 | text | null | 0 | null |
command-r7b-12-2024 | Command R7B (12-2024) | Cohere | cohere | 0.0375 | 0.15 | 128,000 | false | 2024-12-14 | text | null | 0 | null |
gpt-oss-120b | gpt-oss-120b | OpenAI | openai | 0.039 | 0.19 | 131,072 | true | 2025-08-05 | text | null | 12 | null |
gemma-3-4b-it | Gemma 3 4B | Google DeepMind | google | 0.04 | 0.08 | 131,072 | true | 2025-03-13 | multimodal | null | 7 | null |
gemma-3-12b-it | Gemma 3 12B | Google DeepMind | google | 0.04 | 0.13 | 131,072 | true | 2025-03-13 | multimodal | null | 7 | null |
nemotron-nano-9b-v2 | Nemotron Nano 9B V2 | NVIDIA | nvidia | 0.04 | 0.16 | 131,072 | true | 2025-09-05 | text | null | 0 | null |
qwen-2-5-7b-instruct | Qwen2.5 7B Instruct | Alibaba Qwen | alibaba | 0.04 | 0.1 | 32,768 | true | 2024-10-16 | text | null | 0 | null |
l3-lunaris-8b | Llama 3 8B Lunaris | sao10k | sao10k | 0.04 | 0.05 | 8,192 | true | 2024-08-13 | text | null | 0 | null |
trinity-mini | Trinity Mini | arcee-ai | arcee-ai | 0.045 | 0.15 | 131,072 | true | 2025-12-01 | text | null | 0 | null |
llama-3-2-11b-vision-instruct | Llama 3.2 11B Vision Instruct | Meta | meta | 0.049 | 0.049 | 131,072 | true | 2024-09-25 | multimodal | null | 0 | null |
gpt-5-nano | GPT-5 Nano | OpenAI | openai | 0.05 | 0.4 | 400,000 | false | 2025-08-07 | multimodal | null | 12 | null |
qwen3-5-9b | Qwen3.5-9B | Alibaba Qwen | alibaba | 0.05 | 0.15 | 256,000 | true | 2026-03-10 | multimodal | null | 0 | null |
nemotron-3-nano-30b-a3b | Nemotron 3 Nano 30B A3B | NVIDIA | nvidia | 0.05 | 0.2 | 262,144 | true | 2025-12-14 | text | null | 0 | null |
qwen3-8b | Qwen3 8B | Alibaba Qwen | alibaba | 0.05 | 0.4 | 40,960 | true | 2025-04-28 | text | null | 0 | null |
olmo-2-0325-32b-instruct | Olmo 2 32B Instruct | allenai | allenai | 0.05 | 0.2 | 128,000 | true | 2025-03-14 | text | null | 0 | null |
mistral-small-24b-instruct-2501 | Mistral Small 3 | Mistral AI | mistral | 0.05 | 0.08 | 32,768 | true | 2025-01-30 | text | null | 0 | null |
llama-3-2-3b-instruct | Llama 3.2 3B Instruct | Meta | meta | 0.051 | 0.34 | 80,000 | true | 2024-09-25 | text | null | 0 | null |
glm-4-7-flash | GLM 4.7 Flash | z-ai | z-ai | 0.06 | 0.4 | 202,752 | true | 2026-01-19 | text | null | 0 | null |
qwen3-14b | Qwen3 14B | Alibaba Qwen | alibaba | 0.06 | 0.24 | 40,960 | true | 2025-04-28 | text | null | 0 | null |
nova-lite-v1 | Nova Lite 1.0 | Amazon | amazon | 0.06 | 0.24 | 300,000 | false | 2024-12-05 | multimodal | null | 0 | null |
mythomax-l2-13b | MythoMax 13B | gryphe | gryphe | 0.06 | 0.06 | 4,096 | true | 2023-07-02 | text | null | 0 | null |
phi-4 | Phi 4 | Microsoft | microsoft | 0.065 | 0.14 | 16,384 | true | 2025-01-10 | text | null | 6 | null |
qwen3-5-flash-02-23 | Qwen3.5-Flash | Alibaba Qwen | alibaba | 0.065 | 0.26 | 1,000,000 | true | 2026-02-25 | multimodal | null | 0 | null |
ernie-4-5-21b-a3b-thinking | ERNIE 4.5 21B A3B Thinking | baidu | baidu | 0.07 | 0.28 | 131,072 | true | 2025-10-09 | text | null | 0 | null |
ernie-4-5-21b-a3b | ERNIE 4.5 21B A3B | baidu | baidu | 0.07 | 0.28 | 120,000 | true | 2025-08-12 | text | null | 0 | null |
qwen3-coder-30b-a3b-instruct | Qwen3 Coder 30B A3B Instruct | Alibaba Qwen | alibaba | 0.07 | 0.27 | 160,000 | true | 2025-07-31 | text | null | 0 | null |
qwen3-235b-a22b-2507 | Qwen3 235B A22B Instruct 2507 | Alibaba Qwen | alibaba | 0.071 | 0.1 | 262,144 | true | 2025-07-21 | text | null | 0 | null |
seed-1-6-flash | Seed 1.6 Flash | bytedance-seed | bytedance-seed | 0.075 | 0.3 | 262,144 | false | 2025-12-23 | multimodal | null | 0 | null |
gpt-oss-safeguard-20b | gpt-oss-safeguard-20b | OpenAI | openai | 0.075 | 0.3 | 131,072 | true | 2025-10-29 | text | null | 0 | null |
mistral-small-3-2-24b-instruct | Mistral Small 3.2 24B | Mistral AI | mistral | 0.075 | 0.2 | 128,000 | true | 2025-06-20 | multimodal | null | 0 | null |
gemini-2-0-flash-lite-001 | Gemini 2.0 Flash Lite | Google DeepMind | google | 0.075 | 0.3 | 1,048,576 | false | 2025-02-25 | multimodal | null | 0 | null |
gemma-3-27b-it | Gemma 3 27B | Google DeepMind | google | 0.08 | 0.16 | 131,072 | true | 2025-03-12 | multimodal | null | 7 | null |
llama-4-scout | Llama 4 Scout | Meta | meta | 0.08 | 0.3 | 327,680 | true | 2025-04-05 | multimodal | null | 8 | null |
qwen3-vl-8b-instruct | Qwen3 VL 8B Instruct | Alibaba Qwen | alibaba | 0.08 | 0.5 | 131,072 | true | 2025-10-14 | multimodal | null | 0 | null |
qwen3-30b-a3b-thinking-2507 | Qwen3 30B A3B Thinking 2507 | Alibaba Qwen | alibaba | 0.08 | 0.4 | 131,072 | true | 2025-08-28 | text | null | 0 | null |
qwen3-30b-a3b | Qwen3 30B A3B | Alibaba Qwen | alibaba | 0.08 | 0.28 | 40,960 | true | 2025-04-28 | text | null | 0 | null |
qwen3-32b | Qwen3 32B | Alibaba Qwen | alibaba | 0.08 | 0.24 | 40,960 | true | 2025-04-28 | text | null | 0 | null |
mimo-v2-flash | MiMo-V2-Flash | xiaomi | xiaomi | 0.09 | 0.29 | 262,144 | true | 2025-12-14 | text | null | 0 | null |
tongyi-deepresearch-30b-a3b | Tongyi DeepResearch 30B A3B | alibaba | alibaba | 0.09 | 0.45 | 131,072 | true | 2025-09-18 | text | null | 0 | null |
qwen3-next-80b-a3b-instruct | Qwen3 Next 80B A3B Instruct | Alibaba Qwen | alibaba | 0.09 | 1.1 | 262,144 | true | 2025-09-11 | text | null | 0 | null |
qwen3-30b-a3b-instruct-2507 | Qwen3 30B A3B Instruct 2507 | Alibaba Qwen | alibaba | 0.09 | 0.3 | 262,144 | true | 2025-07-29 | text | null | 0 | null |
qwen3-next-80b-a3b-thinking | Qwen3 Next 80B A3B Thinking | Alibaba Qwen | alibaba | 0.0975 | 0.78 | 131,072 | true | 2025-09-11 | text | null | 0 | null |
gemini-2-0-flash-001 | Gemini 2.0 Flash | Google DeepMind | google | 0.1 | 0.4 | 1,048,576 | false | 2025-02-05 | multimodal | null | 4 | null |
llama-3-3-70b-instruct | Llama 3.3 70B Instruct | Meta | meta | 0.1 | 0.32 | 131,072 | true | 2024-12-06 | text | null | 8 | null |
gpt-4-1-nano | GPT-4.1 Nano | OpenAI | openai | 0.1 | 0.4 | 1,047,576 | false | 2025-04-14 | multimodal | null | 9 | null |
reka-edge | Reka Edge | reka | reka | 0.1 | 0.1 | 16,384 | true | 2026-03-20 | multimodal | null | 0 | null |
nemotron-3-super-120b-a12b | Nemotron 3 Super | NVIDIA | nvidia | 0.1 | 0.5 | 262,144 | true | 2026-03-11 | text | null | 0 | null |
seed-2-0-mini | Seed-2.0-Mini | bytedance-seed | bytedance-seed | 0.1 | 0.4 | 262,144 | false | 2026-02-26 | multimodal | null | 0 | null |
step-3-5-flash | Step 3.5 Flash | stepfun | stepfun | 0.1 | 0.3 | 262,144 | true | 2026-01-29 | text | null | 0 | null |
mistral-small-creative | Mistral Small Creative | Mistral AI | mistral | 0.1 | 0.3 | 32,768 | true | 2025-12-16 | text | null | 0 | null |
ministral-3b-2512 | Ministral 3 3B 2512 | Mistral AI | mistral | 0.1 | 0.1 | 131,072 | true | 2025-12-02 | multimodal | null | 0 | null |
voxtral-small-24b-2507 | Voxtral Small 24B 2507 | Mistral AI | mistral | 0.1 | 0.3 | 32,000 | true | 2025-10-30 | multimodal | null | 0 | null |
llama-3-3-nemotron-super-49b-v1-5 | Llama 3.3 Nemotron Super 49B V1.5 | NVIDIA | nvidia | 0.1 | 0.4 | 131,072 | true | 2025-10-10 | text | null | 0 | null |
gemini-2-5-flash-lite-preview-09-2025 | Gemini 2.5 Flash Lite Preview 09-2025 | Google DeepMind | google | 0.1 | 0.4 | 1,048,576 | false | 2025-09-25 | multimodal | null | 0 | null |
glm-4-32b | GLM 4 32B | z-ai | z-ai | 0.1 | 0.1 | 128,000 | false | 2025-07-24 | text | null | 0 | null |
ui-tars-1-5-7b | UI-TARS 7B | bytedance | bytedance | 0.1 | 0.2 | 128,000 | true | 2025-07-22 | multimodal | null | 0 | null |
gemini-2-5-flash-lite | Gemini 2.5 Flash Lite | Google DeepMind | google | 0.1 | 0.4 | 1,048,576 | false | 2025-07-22 | multimodal | null | 0 | null |
devstral-small | Devstral Small 1.1 | Mistral AI | mistral | 0.1 | 0.3 | 131,072 | true | 2025-07-10 | text | null | 0 | null |
qwen3-vl-32b-instruct | Qwen3 VL 32B Instruct | Alibaba Qwen | alibaba | 0.104 | 0.416 | 131,072 | true | 2025-10-23 | multimodal | null | 0 | null |
mistral-7b-instruct-v0-1 | Mistral 7B Instruct v0.1 | Mistral AI | mistral | 0.11 | 0.19 | 2,824 | true | 2023-09-28 | text | null | 0 | null |
qwen3-vl-8b-thinking | Qwen3 VL 8B Thinking | Alibaba Qwen | alibaba | 0.117 | 1.365 | 131,072 | true | 2025-10-14 | multimodal | null | 0 | null |
qwen-2-5-72b-instruct | Qwen2.5 72B Instruct | Alibaba Qwen | alibaba | 0.12 | 0.39 | 32,768 | true | 2024-09-19 | text | null | 15 | null |
qwen3-coder-next | Qwen3 Coder Next | Alibaba Qwen | alibaba | 0.12 | 0.75 | 262,144 | true | 2026-02-04 | text | null | 0 | null |
qwen3-vl-30b-a3b-thinking | Qwen3 VL 30B A3B Thinking | Alibaba Qwen | alibaba | 0.13 | 1.56 | 131,072 | true | 2025-10-06 | multimodal | null | 0 | null |
qwen3-vl-30b-a3b-instruct | Qwen3 VL 30B A3B Instruct | Alibaba Qwen | alibaba | 0.13 | 0.52 | 131,072 | true | 2025-10-06 | multimodal | null | 0 | null |
hermes-4-70b | Hermes 4 70B | nousresearch | nousresearch | 0.13 | 0.4 | 131,072 | true | 2025-08-26 | text | null | 0 | null |
glm-4-5-air | GLM 4.5 Air | z-ai | z-ai | 0.13 | 0.85 | 131,072 | true | 2025-07-25 | text | null | 0 | null |
deepseek-v3-1-nex-n1 | DeepSeek V3.1 Nex N1 | nex-agi | nex-agi | 0.135 | 0.5 | 131,072 | true | 2025-12-08 | text | null | 0 | null |
qwen-vl-plus | Qwen VL Plus | Alibaba Qwen | alibaba | 0.1365 | 0.4095 | 131,072 | true | 2025-02-05 | multimodal | null | 0 | null |
ernie-4-5-vl-28b-a3b | ERNIE 4.5 VL 28B A3B | baidu | baidu | 0.14 | 0.56 | 30,000 | true | 2025-08-12 | multimodal | null | 0 | null |
hunyuan-a13b-instruct | Hunyuan A13B Instruct | tencent | tencent | 0.14 | 0.57 | 131,072 | true | 2025-07-08 | text | null | 0 | null |
hermes-2-pro-llama-3-8b | Hermes 2 Pro - Llama-3 8B | nousresearch | nousresearch | 0.14 | 0.14 | 8,192 | true | 2024-05-27 | text | null | 0 | null |
qwen3-235b-a22b-thinking-2507 | Qwen3 235B A22B Thinking 2507 | Alibaba Qwen | alibaba | 0.1495 | 1.495 | 131,072 | true | 2025-07-25 | text | null | 9 | null |
deepseek-chat-v3-1 | DeepSeek V3.1 | DeepSeek | deepseek | 0.15 | 0.75 | 32,768 | true | 2025-08-21 | text | null | 4 | null |
gpt-4o-mini-2024-07-18 | GPT-4o-mini (2024-07-18) | OpenAI | openai | 0.15 | 0.6 | 128,000 | false | 2024-07-18 | multimodal | null | 14 | null |
gpt-4o-mini | GPT-4o-mini | OpenAI | openai | 0.15 | 0.6 | 128,000 | false | 2024-07-18 | multimodal | null | 14 | null |
llama-4-maverick | Llama 4 Maverick | Meta | meta | 0.15 | 0.6 | 1,048,576 | true | 2025-04-05 | multimodal | null | 14 | null |
mistral-small-2603 | Mistral Small 4 | Mistral AI | mistral | 0.15 | 0.6 | 262,144 | true | 2026-03-16 | multimodal | null | 0 | null |
solar-pro-3 | Solar Pro 3 | upstage | upstage | 0.15 | 0.6 | 128,000 | false | 2026-01-27 | text | null | 0 | null |
olmo-3-1-32b-think | Olmo 3.1 32B Think | allenai | allenai | 0.15 | 0.5 | 65,536 | true | 2025-12-16 | text | null | 0 | null |
rnj-1-instruct | Rnj 1 Instruct | essentialai | essentialai | 0.15 | 0.15 | 32,768 | true | 2025-12-07 | text | null | 0 | null |
ministral-8b-2512 | Ministral 3 8B 2512 | Mistral AI | mistral | 0.15 | 0.15 | 262,144 | true | 2025-12-02 | multimodal | null | 0 | null |
olmo-3-32b-think | Olmo 3 32B Think | allenai | allenai | 0.15 | 0.5 | 65,536 | true | 2025-11-21 | text | null | 0 | null |
End of preview. Expand in Data Studio
BenchGecko AI Model Pricing 2026
Current pricing data for 413 AI models across 57 providers, with benchmark performance scores for cost-efficiency analysis. Sourced from BenchGecko.
Why This Dataset
Choosing an AI model is a price-performance tradeoff. This dataset enables:
- Cost-efficiency rankings (score per dollar)
- Provider pricing comparisons
- Open source vs proprietary cost analysis
- Budget optimization for production deployments
Dataset Summary
| Metric | Value |
|---|---|
| Total models | 413 |
| Models with pricing | 344 |
| Open source models | 235 |
| Providers | 57 |
| Price range (input) | $0.01 - $150 per Mtok |
Columns
| Column | Type | Description |
|---|---|---|
model_slug |
string | Unique identifier |
model_name |
string | Display name |
provider |
string | Company (OpenAI, Anthropic, Google, etc.) |
provider_slug |
string | Provider identifier |
input_price_per_mtok |
float | Input cost in USD per million tokens |
output_price_per_mtok |
float | Output cost in USD per million tokens |
context_window |
int | Maximum context length in tokens |
is_open_source |
bool | Whether weights are publicly available |
release_date |
date | Release date |
model_type |
string | text, multimodal, etc. |
avg_benchmark_score |
float | Average across all benchmarks (0-100) |
num_benchmarks_tested |
int | How many benchmarks this model was tested on |
price_per_score_point |
float | Input price / avg score (lower = more efficient) |
Usage
import pandas as pd
df = pd.read_csv("hf://datasets/DropTheHQ/benchgecko-ai-pricing/pricing.csv")
# Most cost-efficient models
efficient = df[df["input_price_per_mtok"].notna() & (df["input_price_per_mtok"] > 0)]
efficient = efficient.sort_values("price_per_score_point")
print(efficient[["model_name", "provider", "avg_benchmark_score", "input_price_per_mtok", "price_per_score_point"]].head(15))
# Cheapest models with score > 70
good_cheap = df[(df["avg_benchmark_score"] > 70) & (df["input_price_per_mtok"] > 0)]
print(good_cheap.nsmallest(10, "input_price_per_mtok")[["model_name", "provider", "avg_benchmark_score", "input_price_per_mtok"]])
# Average pricing by provider
by_provider = df[df["input_price_per_mtok"].notna()].groupby("provider").agg(
models=("model_name", "count"),
avg_input_price=("input_price_per_mtok", "mean"),
avg_score=("avg_benchmark_score", "mean")
).round(2).sort_values("avg_input_price")
print(by_provider.head(15))
Source
Data from BenchGecko -- an independent AI tracking platform. Explore the full pricing calculator at benchgecko.ai/pricing.
License
CC BY 4.0
Citation
@dataset{benchgecko_pricing_2026,
title={BenchGecko AI Model Pricing 2026},
author={BenchGecko},
year={2026},
url={https://benchgecko.ai},
publisher={Hugging Face},
license={CC BY 4.0}
}
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