fal Highlights
Intelligence
Artificial Analysis Intelligence Index; Higher is better
Speed
Output Tokens per Second; Higher is better
Price
USD per 1M Tokens; Lower is better
How do the latest LLMs stack up?
Compare Language Models
How do the latest OpenAI models compare?
OpenAI Models Compared
Where can you get an API for DeepSeek R1?
DeepSeek R1 Providers
Intelligence
Intelligence of leading AI models based on our independent evaluations
Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index v3.0 incorporates 10 evaluations: MMLU-Pro, GPQA Diamond, Humanity's Last Exam, LiveCodeBench, SciCode, AIME 2025, IFBench, AA-LCR, Terminal-Bench Hard, 𝜏²-Bench Telecom
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Artificial Analysis Intelligence Index: Combination metric covering multiple dimensions of intelligence - the simplest way to compare how smart models are. Version 3.0 was released in September 2025 and includes: MMLU-Pro, GPQA Diamond, Humanity's Last Exam, LiveCodeBench, SciCode, AIME 2025, IFBench, AA-LCR, Terminal-Bench Hard, 𝜏²-Bench Telecom. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Frontier Language Model Intelligence, Over Time
Artificial Analysis Intelligence Index v3.0 incorporates 10 evaluations: MMLU-Pro, GPQA Diamond, Humanity's Last Exam, LiveCodeBench, SciCode, AIME 2025, IFBench, AA-LCR, Terminal-Bench Hard, 𝜏²-Bench Telecom
Alibaba
Anthropic
DeepSeek
Google
LG AI Research
Meta
Mistral
Moonshot AI
OpenAI
Upstage
xAI
Z AI
Artificial Analysis Intelligence Index: Combination metric covering multiple dimensions of intelligence - the simplest way to compare how smart models are. Version 3.0 was released in September 2025 and includes: MMLU-Pro, GPQA Diamond, Humanity's Last Exam, LiveCodeBench, SciCode, AIME 2025, IFBench, AA-LCR, Terminal-Bench Hard, 𝜏²-Bench Telecom. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Intelligence Evaluations
Intelligence evaluations measured independently by Artificial Analysis; Higher is better
Results claimed by AI Lab (not yet independently verified)
MMLU-Pro (Reasoning & Knowledge)
GPQA Diamond (Scientific Reasoning)
Humanity's Last Exam (Reasoning & Knowledge)
LiveCodeBench (Coding)
SciCode (Coding)
IFBench (Instruction Following)
AIME 2025 (Competition Math)
AA-LCR (Long Context Reasoning)
Terminal-Bench Hard
𝜏²-Bench Telecom
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Artificial Analysis Intelligence Index: Combination metric covering multiple dimensions of intelligence - the simplest way to compare how smart models are. Version 3.0 was released in September 2025 and includes: MMLU-Pro, GPQA Diamond, Humanity's Last Exam, LiveCodeBench, SciCode, AIME 2025, IFBench, AA-LCR, Terminal-Bench Hard, 𝜏²-Bench Telecom. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Output Tokens Used to Run Artificial Analysis Intelligence Index
Tokens used to run all evaluations in the Artificial Analysis Intelligence Index
Answer Tokens
Reasoning Tokens
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Artificial Analysis Intelligence Index Tokens Use: The number of tokens required to run all evaluations in the Artificial Analysis Intelligence Index (excluding repeats).
Cost to Run Artificial Analysis Intelligence Index
Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index
Input Cost
Output Cost
Reasoning Cost
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Cost to Run Artificial Analysis Intelligence Index: The cost to run the evaluations in the Artificial Analysis Intelligence Index, calculated using the model's input and output token pricing and the number of tokens used across evaluations (excluding repeats).
Intelligence vs. Cost to Run Artificial Analysis Intelligence Index
Artificial Analysis Intelligence Index; Cost to Run Intelligence Index
Most attractive quadrant
Alibaba
Anthropic
DeepSeek
Google
LG AI Research
Meta
Mistral
Moonshot AI
OpenAI
Upstage
xAI
Z AI
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Cost to Run Artificial Analysis Intelligence Index: The cost to run the evaluations in the Artificial Analysis Intelligence Index, calculated using the model's input and output token pricing and the number of tokens used across evaluations (excluding repeats).
Artificial Analysis Intelligence Index: Combination metric covering multiple dimensions of intelligence - the simplest way to compare how smart models are. Version 3.0 was released in September 2025 and includes: MMLU-Pro, GPQA Diamond, Humanity's Last Exam, LiveCodeBench, SciCode, AIME 2025, IFBench, AA-LCR, Terminal-Bench Hard, 𝜏²-Bench Telecom. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Speed & Latency
Comparison of first-party API performance
Output Speed
Output Tokens per Second; Higher is better
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Output Speed: Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
Latency: Time To First Answer Token
Seconds to First Answer Token Received; Accounts for Reasoning Model 'Thinking' time
Input processing
Thinking (reasoning models, when applicable)
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Time To First Answer Token: Time to first answer token received, in seconds, after API request sent. For reasoning models, this includes the 'thinking' time of the model before providing an answer. For models which do not support streaming, this represents time to receive the completion.
End-to-End Response Time
Seconds to Output 500 Tokens, including reasoning model 'thinking' time; Lower is better
'Thinking' time (reasoning models)
Input processing time
Outputting time
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End-to-End Response Time: Seconds to receive a 500 token response. Key components:
- Input time: Time to receive the first response token
- Thinking time (only for reasoning models): Time reasoning models spend outputting tokens to reason prior to providing an answer. Amount of tokens based on the average reasoning tokens across a diverse set of 60 prompts (methodology details).
- Answer time: Time to generate 500 output tokens, based on output speed
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
Intelligence vs. Output Speed
Artificial Analysis Intelligence Index; Output Speed: Output Tokens per Second
Most attractive quadrant
Alibaba
Anthropic
DeepSeek
Google
LG AI Research
Meta
Mistral
Moonshot AI
OpenAI
Upstage
xAI
Z AI
+ Add model from specific provider
Artificial Analysis Intelligence Index: Combination metric covering multiple dimensions of intelligence - the simplest way to compare how smart models are. Version 3.0 was released in September 2025 and includes: MMLU-Pro, GPQA Diamond, Humanity's Last Exam, LiveCodeBench, SciCode, AIME 2025, IFBench, AA-LCR, Terminal-Bench Hard, 𝜏²-Bench Telecom. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Output Speed: Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
Price
Pricing: Input and Output Prices
Price: USD per 1M Tokens
Input price
Output price
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Input Price: Price per token included in the request/message sent to the API, represented as USD per million Tokens.
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
Intelligence vs. Price (Log Scale)
Artificial Analysis Intelligence Index; Price: USD per 1M Tokens; Inspired by prior analysis by Swyx
Most attractive quadrant
Alibaba
Anthropic
DeepSeek
Google
LG AI Research
Meta
Mistral
Moonshot AI
OpenAI
Upstage
xAI
Z AI
+ Add model from specific provider
Artificial Analysis Intelligence Index: Combination metric covering multiple dimensions of intelligence - the simplest way to compare how smart models are. Version 3.0 was released in September 2025 and includes: MMLU-Pro, GPQA Diamond, Humanity's Last Exam, LiveCodeBench, SciCode, AIME 2025, IFBench, AA-LCR, Terminal-Bench Hard, 𝜏²-Bench Telecom. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.
Price: Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
New
Hardware Benchmarking
Comprehensive benchmarking of GPUs for language model inference
Video Arena & Leaderboard
Compare leading Text to Video and Image to Video models
Image Arena & Leaderboard
Compare leading Image Generation and Image Editing models
Speech Arena & Leaderboard
Compare leading Text to Speech models
API Provider Performance
- gpt-oss-120B (high)
- GPT-5 (high)
- gpt-oss-20B (high)
- GPT-4.1
- o3
- GPT-5 (minimal)
- Llama 4 Maverick
- Gemini 2.5 Pro
- Gemini 2.5 Flash
- Claude 4.1 Opus
- Claude 4 Sonnet
- Mistral Medium 3.1
- DeepSeek R1 0528
- DeepSeek V3.1
- DeepSeek V3.1
- Grok 4
- Grok Code Fast 1
- Solar Pro 2
- Llama Nemotron Super 49B v1.5
- Kimi K2 0905
- EXAONE 4.0 32B
- GLM-4.5
- Qwen3 235B 2507
Output Speed vs. Price: gpt-oss-120B
Output Speed: Output Tokens per Second, Price: USD per 1M Tokens; 1,000 Input Tokens
Most attractive quadrant
Amazon Bedrock
Cerebras
Cloudflare
CompactifAI
Deepinfra
Fireworks
GMI
Google Vertex
Groq
Microsoft Azure
Nebius Base
Novita
Parasail
Together.ai
Price: Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).
Output Speed: Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).
Median: Figures represent median (P50) measurement over the past 72 hours to reflect sustained changes in performance.
Pricing (Input and Output Prices): gpt-oss-120B
Price: USD per 1M Tokens; Lower is better; 1,000 Input Tokens
Input price
Output price
Input Price: Price per token included in the request/message sent to the API, represented as USD per million Tokens.
Output Price: Price per token generated by the model (received from the API), represented as USD per million Tokens.
Output Speed: gpt-oss-120B
Output Speed: Output Tokens per Second; 1,000 Input Tokens
Output Speed: Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).
Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).
Output Speed, Over Time: gpt-oss-120B
Output Tokens per Second; Higher is better; 1,000 Input Tokens
Amazon
Azure
Cerebras
Cloudflare
CompactifAI
Deepinfra
Fireworks
GMI
Google Vertex
Groq
Nebius Base
Novita
Parasail
Together.ai
Output Speed: Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).
Over time measurement: Median measurement per day, based on 8 measurements each day at different times. Labels represent start of week's measurements.
See more information on any of our supported models
R1 1776
Nova Premier
Phi-4
LFM2 1.2B
MiniMax-Text-01
Granite 3.3 Instruct 8B
Reka Flash 3
Hermes 4 - Llama-3.1 70B (Reasoning)
Aya Expanse 32B
Jamba 1.7 Mini
DBRX Instruct
Llama 3.1 Tulu3 405B
Arctic Instruct
Yi-Large