MiniMax: Models Intelligence, Performance & Price

Name: Intelligence
Creator: Artificial Analysis
License: https://artificialanalysis.ai/docs/legal/Terms-of-Use.pdf

MiniMax

This analysis is intended to support you in choosing the best model provided by MiniMax for your use-case.

Most Intelligent

Updated

MiniMax-M3

MiniMax-M2.7

MiniMax-M2.5

MiniMax-M2.1

MiniMax-M2

Intelligence index

Total 5 models

Fastest

MiniMax-M3

95 t/s

MiniMax-M2

90 t/s

MiniMax-M2.1

89 t/s

MiniMax-M2.5

87 t/s

MiniMax-M2.7

61 t/s

Output speed

Total 5 models

Lowest Price

MiniMax-M2.5

$0.20

MiniMax-M3

$0.22

MiniMax-M2.7

$0.22

MiniMax-M2.1

$0.39

MiniMax-M2

$0.39

Blended price (per 1M tokens)

Total 5 models

MiniMax offers 5 models, each with different intelligence, performance, and pricing characteristics. Below is a comparison of the key metrics across models.

For intelligence, the top models on MiniMax are MiniMax-M3 (30), MiniMax-M2.7 (23), and MiniMax-M2.5 (23).
For output speed, the fastest models are MiniMax-M3 (95 t/s), MiniMax-M2 (90 t/s), and MiniMax-M2.1 (89 t/s). Speed varies significantly across models, with a 56% difference between the fastest and slowest.
For latency, MiniMax-M3 (22.36s), MiniMax-M2 (23.85s), and MiniMax-M2.1 (24.30s) offer the lowest time to first answer token.
For pricing, MiniMax-M2.5 ($0.20), MiniMax-M3 ($0.22), and MiniMax-M2.7 ($0.22) offer the lowest blended prices per 1M tokens.
For context window size, MiniMax-M3 (512k), MiniMax-M2.7 (205k), and MiniMax-M2.5 (205k) support the largest context windows on MiniMax.
MiniMax-M3 offers the best combination of intelligence and speed. For cost optimization, MiniMax-M2.5 provides the most competitive pricing.

Highlights

Updated

Intelligence

Artificial Analysis Intelligence Index · Higher is better

Speed

Output tokens per second · Higher is better

Price

USD per 1M tokens (blended) · Lower is better

Intelligence Evaluations

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.3 incorporates 10 evaluations: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1

Estimate (independent evaluation forthcoming)

Artificial Analysis Intelligence Index v4.3 includes: AA-Briefcase, GDPval-AA v2, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. 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

AA-Briefcase

Agentic knowledge work, (Elo-500)/2000

GDPval-AA v2

Agentic real-world work tasks, (Elo-500)/2000

AutomationBench-AAUpdated

Agentic SaaS workflows

Terminal-Bench 4.0New

Agentic coding & terminal use

SciCode

Coding

Humanity's Last Exam

Reasoning & knowledge

GDP.pdfNew

Professional document reasoning, All-pass

CritPt

Physics reasoning

AA-Omniscience Accuracy

Knowledge

AA-Omniscience Non-Hallucination Rate

1 - hallucination rate

AA-LCR v1.1

Long context reasoning

Harvey LAB-AA

Legal agentic work, criterion pass rate

EnterpriseOps-Gym-AA

Agentic business operations

AA-AnalystAgent

Quantitative analysis on spreadsheets & documents

IFBench

Instruction following

𝜏³-Banking

Agentic tool use

APEX-Agents-AA

Long-horizon agentic tasks

ITBench-AA

Kubernetes incident root-cause analysis

MMMU-Pro

Visual reasoning

While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.

Intelligence Index vs. Price

Blended at 7:2:1 (cache-input-output) · USD per 1M tokens (blended)

Most attractive quadrant

Pareto line

While higher intelligence models are typically more expensive, they do not all follow the same price-quality curve.

Context Window

Context window: tokens limit · Higher is better

Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.

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

Pricing

Intelligence Index vs. Price

Blended at 7:2:1 (cache-input-output) · USD per 1M tokens (blended)

Most attractive quadrant

Pareto line

While higher intelligence models are typically more expensive, they do not all follow the same price-quality curve.

Performance Summary

Output Speed vs. Price

Output speed: output tokens per second · USD per 1M tokens (blended)

Most attractive quadrant

Pareto line

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, shown in USD per million tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio (default 7:2:1 cache-input-output).

Speed

Measured by Output Speed (tokens per second)

Output Speed

Output tokens per second · Higher is better

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

Latency: Time To First Answer Token

Seconds to first answer token received · Accounts for reasoning model 'thinking' time

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, 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 · USD per 1M tokens (blended)

Most attractive quadrant

Pareto line

Price per token, shown in USD per million tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio (default 7:2:1 cache-input-output).


									Further Analysis
MiniMax-M3	512k	Open	30	$0.51	95	1.35	27.61	21.01	Model Provider
MiniMax-M2.7	205k	Open	23	$0.10	61	1.69	50.21	40.33	Model Provider
MiniMax-M2.5	205k	Open	23*	--	87	1.66	30.32	22.93	Model Provider
MiniMax-M2.1	205k	Open	21*	--	89	1.80	29.93	22.51	Model Provider
MiniMax-M2	205k	Open	19*	--	90	1.75	29.37	22.10	Model Provider

Key definitions

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

Frequently Asked Questions

Common questions about MiniMax

MiniMax offers 5 models that we track: MiniMax-M3, MiniMax-M2.7, MiniMax-M2.5, MiniMax-M2.1, and MiniMax-M2.

The most intelligent model available on MiniMax is MiniMax-M3 with an Intelligence Index score of 30.

The fastest model on MiniMax by output speed is MiniMax-M3 at 95.2 tokens per second.

The model with the lowest time to first answer token on MiniMax is MiniMax-M3 at 22.36s. Lower latency means faster initial response time.

The most affordable model on MiniMax by blended price is MiniMax-M2.5 at $0.20 per 1M tokens (7:2:1 cache hit/input/output ratio).

Prices on MiniMax vary up to 2x across models, from $0.20 per 1M tokens for MiniMax-M2.5 to $0.39 per 1M tokens for MiniMax-M2.

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

Yes, all 5 models on MiniMax support JSON mode for structured output.

Yes, all 5 models on MiniMax support function calling (tool use).

Yes, MiniMax offers 5 reasoning models: MiniMax-M3, MiniMax-M2.7, MiniMax-M2.5, MiniMax-M2.1, and MiniMax-M2. Reasoning models use extended thinking to work through complex problems before providing an answer.

Yes, all 5 models on MiniMax 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 MiniMax, 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.

MiniMax: Models Intelligence, Performance & Price

Most Intelligent

Fastest

Lowest Price

Intelligence

Speed

Price

Intelligence Evaluations

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index

Intelligence Evaluations

Intelligence Evaluation Relevance

Artificial Analysis Intelligence Index

Intelligence Index vs. Price

Price-Quality Variance

Context Window

Context Window

Context Window for RAG

Context Window

Pricing

Intelligence Index vs. Price

Price-Quality Variance

Performance Summary

Output Speed vs. Price

Output Speed

Price

Speed

Output Speed

Output Speed

Model Performance Representation

Latency

Latency: Time To First Answer Token

Time to First Answer Token

End-to-End Response Time

End-to-End Response Time vs. Price

Price

Key definitions

Context Window

Frequently Asked Questions

What models does MiniMax offer?

What is the most intelligent model on MiniMax?

What is the fastest model on MiniMax?

Which model has the lowest latency on MiniMax?

What is the cheapest model on MiniMax?

How much do prices vary across models on MiniMax?

Is MiniMax OpenAI compatible?

Does MiniMax support JSON mode?

Does MiniMax support function calling?

Does MiniMax offer reasoning models?

Does MiniMax offer open weight models?

Does MiniMax's performance change over time?

How do I choose a model on MiniMax?