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CompactifAI: Models Intelligence, Performance & Price

Analysis of CompactifAI's models across key metrics including quality, price, output speed, latency, context window & more. This analysis is intended to support you in choosing the best model provided by CompactifAI for your use-case. For more details including relating to our methodology, see our FAQs.
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CompactifAI Model Comparison Summary

Intelligence:Llama 3.3 70B logo Llama 3.3 70B and Llama 4 Scout logo Llama 4 Scout are the highest intelligence models offered by CompactifAI, followed by Llama 3.1 8B logo Llama 3.1 8B & Mistral Small 3.1 logo Mistral Small 3.1.Output Speed (tokens/s):Llama 3.1 8B logo Llama 3.1 8B (150 t/s) and Llama 3.3 70B logo Llama 3.3 70B (143 t/s) are the fastest models offered by CompactifAI, followed by Llama 4 Scout logo Llama 4 Scout & Mistral Small 3.1 logo Mistral Small 3.1.Latency (seconds):Llama 3.1 8B logo Llama 3.1 8B (0.20s) and  Llama 4 Scout logo Llama 4 Scout (0.26s) are the lowest latency models offered by CompactifAI, followed by Llama 3.3 70B logo Llama 3.3 70B & Mistral Small 3.1 logo Mistral Small 3.1.Blended Price ($/M tokens):Llama 3.1 8B logo Llama 3.1 8B ($0.07) and Llama 4 Scout logo Llama 4 Scout ($0.11) are the cheapest models offered by CompactifAI, followed by Mistral Small 3.1 logo Mistral Small 3.1 & Llama 3.3 70B logo Llama 3.3 70B.Context Window Size:Llama 4 Scout logo Llama 4 Scout (10m) and Llama 3.3 70B logo Llama 3.3 70B (128k) are the largest context window models offered by CompactifAI, followed by Llama 3.1 8B logo Llama 3.1 8B & Mistral Small 3.1 logo Mistral Small 3.1.

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

Intelligence Evaluations

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index; Higher is better

Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

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 Evaluations

Intelligence evaluations measured independently by Artificial Analysis; Higher is better
Results claimed by AI Lab (not yet independently verified)
GDPval-AA (Agentic Real-World Work Tasks, (ELO-500)/2000)
Terminal-Bench Hard (Agentic Coding & Terminal Use)
𝜏²-Bench Telecom (Agentic Tool Use)
AA-LCR (Long Context Reasoning)
AA-Omniscience Accuracy (Knowledge)
AA-Omniscience Non-Hallucination Rate (1 - Hallucination Rate)
No data available
Humanity's Last Exam (Reasoning & Knowledge)
GPQA Diamond (Scientific Reasoning)
SciCode (Coding)
IFBench (Instruction Following)
CritPt (Physics Reasoning)
MMMU Pro (Visual Reasoning)

Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Intelligence vs. Price

Artificial Analysis Intelligence Index; Price: USD per 1M Tokens
Most attractive quadrant
CompactifAI

Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).

Context Window

Context Window

Context Window: Tokens Limit; Higher is better

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

JSON Mode & Function Calling

Function (Tool) Calling & JSON Mode

ModelsFunction callingJSON Mode
Llama 3.3 70B, CompactifAI logoLlama 3.3 70B, CompactifAI
Llama 4 Scout, CompactifAI logoLlama 4 Scout, CompactifAI
Llama 3.1 8B, CompactifAI logoLlama 3.1 8B, CompactifAI
Mistral Small 3.1, CompactifAI logoMistral Small 3.1, CompactifAI

Indicates whether the provider supports function calling in their API. Function calling is also known as 'Tool Calling'.

Indicates whether the provider supports JSON mode in their API. When JSON mode is enabled, the models will always return a valid JSON object.

Intelligence vs. Price

Artificial Analysis Intelligence Index; Price: USD per 1M Tokens
Most attractive quadrant
CompactifAI

Artificial Analysis Intelligence Index v4.0 includes: GDPval-AA, 𝜏²-Bench Telecom, Terminal-Bench Hard, SciCode, AA-LCR, AA-Omniscience, IFBench, Humanity's Last Exam, GPQA Diamond, CritPt. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

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).

Performance Summary

Output Speed vs. Price

Output Speed: Output Tokens per Second; Price: USD per 1M Tokens; 1,000 Input Tokens
Most attractive quadrant
CompactifAI

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).

Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).

Speed

Measured by Output Speed (tokens per second)

Output Speed

Output Tokens per Second; Higher is better; 1,000 Input Tokens

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

Measured by Time (seconds) to First Token

Time to First Token

Seconds to First Token Received; Lower is better; 1,000 Input Tokens

Time to first token received, in seconds, after API request sent. For reasoning models which share reasoning tokens, this will be the first reasoning token. For models which do not support streaming, this represents time to receive the completion.

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).

End-to-End Response Time

Seconds to output 500 Tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed

End-to-End Response Time vs. Price

End-to-End Response Time: End-to-End Seconds to Output 500 Tokens; Price: USD per 1M Tokens
Most attractive quadrant
CompactifAI

Seconds to receive a 500 token response considering input processing time, 'thinking' time of reasoning models, and output speed.

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).

Key definitions

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

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).

Time to first token received, in seconds, after API request sent. For reasoning models which share reasoning tokens, this will be the first reasoning token. For models which do not support streaming, this represents time to receive the completion.

Price per token, represented as USD per million Tokens. Price is a blend of Input & Output token prices (3:1 ratio).

Price per token generated by the model (received from the API), represented as USD per million Tokens.

Price per token included in the request/message sent to the API, represented as USD per million Tokens.

Metrics are 'live' and are based on the past 72 hours of measurements, measurements are taken 8 times a day for single requests and 2 times per day for parallel requests.