Stay connected with us on X, Discord, and LinkedIn to stay up to date with future analysis
logo

Replicate: Models Intelligence, Performance & Price

Analysis of Replicate'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 Replicate for your use-case. For more details including relating to our methodology, see our FAQs.
Link:

Replicate Model Comparison Summary

Intelligence:DeepSeek V3 0324 logo DeepSeek V3 0324 and Llama 3.1 405B logo Llama 3.1 405B are the highest intelligence models offered by Replicate, followed by Granite 4.0 H Small logo Granite 4.0 H Small & Granite 3.3 8B logo Granite 3.3 8B.Output Speed (tokens/s):Granite 3.3 8B logo Granite 3.3 8B (497 t/s) and Granite 4.0 H Small logo Granite 4.0 H Small (429 t/s) are the fastest models offered by Replicate, followed by DeepSeek V3 0324 logo DeepSeek V3 0324 & Llama 3.1 405B logo Llama 3.1 405B.Latency (seconds):Llama 3.1 405B logo Llama 3.1 405B (3.53s) and  DeepSeek V3 0324 logo DeepSeek V3 0324 (3.84s) are the lowest latency models offered by Replicate, followed by Granite 3.3 8B logo Granite 3.3 8B & Granite 4.0 H Small logo Granite 4.0 H Small.Blended Price ($/M tokens):Granite 3.3 8B logo Granite 3.3 8B ($0.09) and Granite 4.0 H Small logo Granite 4.0 H Small ($0.11) are the cheapest models offered by Replicate, followed by DeepSeek V3 0324 logo DeepSeek V3 0324 & Llama 3.1 405B logo Llama 3.1 405B.Context Window Size:DeepSeek V3 0324 logo DeepSeek V3 0324 (128k) and Llama 3.1 405B logo Llama 3.1 405B (128k) are the largest context window models offered by Replicate, followed by Granite 4.0 H Small logo Granite 4.0 H Small & Granite 3.3 8B logo Granite 3.3 8B.
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)
Humanity's Last Exam (Reasoning & Knowledge)
GPQA Diamond (Scientific Reasoning)
SciCode (Coding)
IFBench (Instruction Following)
CritPt (Physics Reasoning)
MMMU Pro (Visual Reasoning)
No data available

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
Replicate

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
DeepSeek V3 0324, Replicate logoDeepSeek V3 0324, Replicate
Llama 3.1 405B, Replicate logoLlama 3.1 405B, Replicate
Granite 4.0 H Small, Replicate logoGranite 4.0 H Small, Replicate
Granite 3.3 8B, Replicate logoGranite 3.3 8B, Replicate

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.

Pricing

Intelligence vs. Price

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

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; 10,000 Input Tokens
Most attractive quadrant
Replicate

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; 10,000 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; 10,000 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
Replicate

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.

Frequently Asked Questions

Common questions about Replicate

Replicate offers 4 models that we track: DeepSeek V3 0324, Llama 3.1 405B, Granite 4.0 H Small, and Granite 3.3 8B.

The most intelligent model available on Replicate is DeepSeek V3 0324 with an Intelligence Index score of 22.

The fastest model on Replicate by output speed is Granite 3.3 8B at 497.0 tokens per second.

The model with the lowest time to first token on Replicate is Llama 3.1 405B at 3.53s. Lower latency means faster initial response time.

The most affordable model on Replicate by blended price is Granite 3.3 8B at $0.09 per 1M tokens (3:1 input to output ratio).

Prices on Replicate vary up to 112x across models, from $0.09 per 1M tokens for Granite 3.3 8B to $9.50 per 1M tokens for Llama 3.1 405B.

Yes, Replicate offers an OpenAI-compatible API, making it easy to switch from OpenAI or use existing OpenAI SDK integrations.

Yes, all 4 models on Replicate are open weight models.

Yes, provider performance can vary over time due to infrastructure changes, load balancing, and updates. We continuously benchmark all providers and display historical performance trends in the "Over Time" charts.

When choosing a model on Replicate, consider: intelligence (for quality-sensitive tasks), output speed (for throughput-intensive tasks), latency (for interactive applications requiring quick first responses), pricing (for cost-sensitive workloads), and features like context window size, JSON mode, or function calling support.