How much does Mistral Medium 3.1 cost?

Mistral Medium 3.1 costs $0.40/M input tokens and $2.00/M output tokens, with separate rates for Cache Read at $0.04/M tokens.

What is the context length of Mistral Medium 3.1?

Mistral Medium 3.1 has a 131,072 token context window. It supports up to 131,072 completion tokens.

Does Mistral Medium 3.1 support tool calling and structured outputs?

Yes. Mistral Medium 3.1 accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.

What inputs and outputs does Mistral Medium 3.1 support?

Mistral Medium 3.1 accepts text, images, and files such as PDFs as input and returns text.

Which providers serve Mistral Medium 3.1?

Mistral Medium 3.1 is served by 1 provider on OpenRouter: Mistral.

What other text models does Mistral have?

Mistral Large 4, Mistral Medium 3.5, Mistral Small 4 and 16 more are other text models from Mistral.

When was Mistral Medium 3.1 released?

Mistral Medium 3.1 was released on August 13, 2025. Its knowledge cutoff is June 30, 2025.

Mistral: Mistral Medium 3.1

mistralai/mistral-medium-3.1

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Mistral Medium 3.1 is an updated version of Mistral Medium 3, which is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances state-of-the-art reasoning and multimodal performance with 8× lower cost compared to traditional large models, making it suitable for scalable deployments across professional and industrial use cases.

The model excels in domains such as coding, STEM reasoning, and enterprise adaptation. It supports hybrid, on-prem, and in-VPC deployments and is optimized for integration into custom workflows. Mistral Medium 3.1 offers competitive accuracy relative to larger models like Claude Sonnet 3.5/3.7, Llama 4 Maverick, and Command R+, while maintaining broad compatibility across cloud environments.

Modalities

In / out price

$0.40 / $2per 1M

Context

131K

Released

Aug 13, 2025

Knowledge cutoff

Jun 2025

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).

Latency / throughput


	$0.40	$2.00	$0.04	0.59s	67 tok/s	100.00%
Not used in Standard routing:Why these endpoints are not used
	$0.44	$2.20	$0.044	0.63s	119 tok/s	100.00%

Input $0.40Output $2.00
67 tok/s100.00% uptime
Not used in Standard routing:Why these endpoints are not used
Input $0.44Output $2.20
119 tok/s100.00% uptime

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Weighted average

Input

$0.1207/M tokens

Output

$2.012/M tokens

Mistral Medium 3.1 — Price history

Price history

No effective price data for this selection

	$0.119	$2.00	78.2%	98.7%
Not used in Standard routing:Why these endpoints are not used
	$0.300	$2.20	35.4%	1.3%

Effective in $0.119Effective out $2.00
Token share
98.7%
Not used in Standard routing:Why these endpoints are not used
Effective in $0.300Effective out $2.20
Token share
1.3%

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Uptime (3d)

100.00%

Availability (3d)

99.99%

Availability over the last 3 days

Last 72 hours

Availability 99.99%

3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability

99.99%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for Mistral: Mistral Medium 3.1 (Artificial Analysis and Design Arena)
Source	Benchmark	Score
Artificial Analysis	Mistral Medium 3.1 Coding Index	20.5
Artificial Analysis	Mistral Medium 3.1 Agentic Index	1.9
Artificial Analysis	Mistral Medium 3.1 GPQA Diamond	58.8%
Artificial Analysis	Mistral Medium 3.1 HLE	4.7%
Artificial Analysis	Mistral Medium 3.1 IFBench	39.8%
Artificial Analysis	Mistral Medium 3.1 τ²-Bench Telecom	40.6%
Artificial Analysis	Mistral Medium 3.1 AA-LCR	42.7%
Artificial Analysis	Mistral Medium 3.1 τ-Bench Banking	8.2%
Artificial Analysis	Mistral Medium 3.1 GDPval-AA	0.0%
Artificial Analysis	Mistral Medium 3.1 CritPt	0.0%
Artificial Analysis	Mistral Medium 3.1 LiveCodeBench	40.6%
Artificial Analysis	Mistral Medium 3.1 SciCode	32.4%
Artificial Analysis	Mistral Medium 3.1 Terminal-Bench Hard	10.6%
Artificial Analysis	Mistral Medium 3.1 Terminal-Bench 4.0	0.0%
Artificial Analysis	Mistral Medium 3.1 Terminal-Bench 2.1	13.9%
Artificial Analysis	Mistral Medium 3.1 MMLU-Pro	68.3%
Artificial Analysis	Mistral Medium 3.1 AIME 2025	38.3%
Design Arena	Mistral Medium 3.1 (2508) Models Arena 3D Elo	1060
Design Arena	Mistral Medium 3.1 (2508) Models Arena Asciiart Elo	992
Design Arena	Mistral Medium 3.1 (2508) Models Arena Code Categories Elo	1109
Design Arena	Mistral Medium 3.1 (2508) Models Arena Data Visualization Elo	1142
Design Arena	Mistral Medium 3.1 (2508) Models Arena Game Development Elo	1063
Design Arena	Mistral Medium 3.1 (2508) Models Arena SVG Elo	983
Design Arena	Mistral Medium 3.1 (2508) Models Arena UI Component Elo	1091
Design Arena	Mistral Medium 3.1 (2508) Models Arena Website Elo	1124

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

A4 Finanz-Bot

new

2.72Btokens

Reality Fabricator

new

769Mtokens

Hermes Agent

Hermes Agent is an open-source, self-improving AI agent by Nous Research that runs persistently with memory across sessions, and builds reusable skills from experience. It comes with 40+ built-in tools, including web search, browser automation, and vision, plus scheduled automations and subagents.

750Mtokens

Calla

new

725Mtokens

Jailbreak Chat

new

345Mtokens

Rest of OpenRouter

626M

Top 5 Apps

188M

Available through EU in-region routing

Mistral: Mistral Medium 3.1 is available through EU in-region routing. Requests sent to eu.openrouter.ai are decrypted in the EU and routed only to shared provider endpoints in Europe (the EU/EEA, the UK, and Switzerland).

Providers in Europe

Mistral

Prices in Europe

Mistral: $0.44/M tokens input, $2.20/M tokens output

Base URL

https://eu.openrouter.ai/api/v1

Plan

Requires Business or Enterprise. Self-serve on Business: no contract, no monthly minimum. OpenRouter Business for EU in-region routing

Fails closed: if no shared provider endpoint in Europe is available, the request errors instead of leaving the region. Requests served by your own BYOK key go to your deployment’s region, which you control. In-region routing docs

More models from Mistral

Voxtral TTS 3

Voxtral TTS 3 is Mistral's text-to-speech model. It converts text into natural-sounding speech, offers a library of preset voices, supports zero-shot voice cloning, and accepts emotion and pace tags in the input to control delivery. It streams audio with low time-to-first-audio and suits voice agents, narration, and multilingual assistants.

Speech$13/M characters

Voxtral Small Transcribe 3

Voxtral Small Transcribe 3 is Mistral's flagship speech-to-text model. It takes audio input and returns a transcript with timestamps and speaker diarization, and supports context biasing for domain-specific vocabulary. Suited for high-accuracy multilingual transcription of meetings, interviews, media, and support calls.

Transcription$0.000067/second

Voxtral Mini Transcribe 3

Voxtral Mini Transcribe 3 is Mistral's compact speech-to-text model. It takes audio input and returns a transcript with timestamps and speaker diarization. It also supports context biasing for domain terms. It is small enough to self-deploy in resource-constrained environments, and fits meeting notes, call analytics, and voice-agent pipelines where cost matters.

Transcription$0.000058/second

Mistral Large 4

Mistral Large 4 is a frontier multimodal (text and image input) model from Mistral AI built for reasoning, coding, and agentic workloads. It offers a 1M-token context window with up to 256K output tokens, and supports tool calling and structured outputs.

Text1.0M context$0.70 / $2.10

Voxtral Small 24B 2507 STT

Voxtral Small 24B 2507 STT is a speech transcription model from Mistral AI. It is suited for transcription, translation, and audio understanding workloads that benefit from its larger model capacity.

Transcription$0.00005/second

Voxtral Mini 3B 2507

Voxtral Mini 3B 2507 is a speech and audio understanding model from Mistral AI. It is suited for transcription, translation, and compact audio processing workloads.

Transcription$0.000017/second

Voxtral Mini Transcribe

Voxtral Mini Transcribe is Mistral's speech-to-text model, derived from the Voxtral Mini family. It accepts audio input and returns transcribed text via the standard transcription API. Suited for transcribing meetings, voice notes, podcasts, and other spoken content.

Transcription$0.00005/second

Mistral Medium 3.5

Mistral Medium 3.5 is a dense 128B instruction-following model from Mistral AI. It supports text and image inputs with text output, and is designed for agentic workflows, coding, and complex multi-step reasoning. It is particularly strong at reliable multi-tool calling and long-horizon tasks, with a 256K context window, configurable reasoning effort per request, and a custom vision encoder that handles variable image sizes and aspect ratios. Self-hostable on as few as four GPUs and available under open weights.

Text262K context$1.50 / $7.50

Mistral Medium 3.5 (batch)

Text262K context$0.75 / $3.75

Voxtral Mini TTS

Voxtral Mini TTS is Mistral's text-to-speech model featuring zero-shot voice cloning and multilingual support. It converts text input into natural-sounding audio output.

Speech$16/M characters

Mistral Small 4

Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into a single system. It combines strong reasoning from Magistral, multimodal understanding from Pixtral, and agentic coding capabilities from Devstral, enabling one model to handle complex analysis, software development, and visual tasks within the same workflow.

Text262K context$0.15 / $0.60

Mistral Small Creative

Mistral Small Creative is an experimental small model designed for creative writing, narrative generation, roleplay and character-driven dialogue, general-purpose instruction following, and conversational agents.

Text33K context

Devstral 2 2512

Devstral 2 is a state-of-the-art open-source model by Mistral AI specializing in agentic coding. It is a 123B-parameter dense transformer model supporting a 256K context window.

Devstral 2 supports exploring codebases and orchestrating changes across multiple files while maintaining architecture-level context. It tracks framework dependencies, detects failures, and retries with corrections—solving challenges like bug fixing and modernizing legacy systems. The model can be fine-tuned to prioritize specific languages or optimize for large enterprise codebases. It is available under a modified MIT license.

Text262K context$0.40 / $2

Ministral 3 14B 2512

The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart. A powerful and efficient language model with vision capabilities.

Text262K context$0.20 / $0.20

Ministral 3 8B 2512

A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.

Text262K context$0.15 / $0.15

Ministral 3 3B 2512

The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.

Text131K context$0.10 / $0.10

Mistral Large 3 2512

Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.

Text262K context$0.50 / $1.50

Mistral Embed 2312

Mistral Embed is a specialized embedding model for text data, optimized for semantic search and RAG applications. Developed by Mistral AI in late 2023, it produces 1024-dimensional vectors that effectively capture semantic relationships in text.

Embeddings$0.10/M tokens

Codestral Embed 2505

Mistral Codestral Embed is specially designed for code, perfect for embedding code databases, repositories, and powering coding assistants with state-of-the-art retrieval.

Embeddings$0.15/M tokens

Voxtral Small 24B 2507

Voxtral Small is an enhancement of Mistral Small 3, incorporating state-of-the-art audio input capabilities while retaining best-in-class text performance. It excels at speech transcription, translation and audio understanding. Input audio is priced at $100 per million seconds.

Text33K context$0.10 / $0.30

Mistral: Mistral Medium 3.1

Providers