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Mistral AI · Official-source model record

Devstral Medium 1.0

Devstral · Version 25.07

DeprecatedChecked Oct 23, 2026
Editorial (0) ↓Download model brief (.md)

Publisher-sourced inventory. Specifications come from official documentation and model cards. “Not documented” means we have no verified value. This inventory is separate from our editorial reviews.

Coverage & sources ↗

Current catalog answers

What to know about Devstral Medium 1.0

AI-compiled from linked model documentation. This is a catalog reference, not an independent performance review. Catalog checked October 23, 2026.

What happened to Devstral Medium 1.0, and what replaces it?

These details come from the linked publisher material for this model. Reported capabilities and training descriptions are publisher statements, not independent test results.

API deprecation
Mistral records deprecation on 2026-02-27. This lifecycle date is distinct from the model release or training cutoff. Source
Recommended migration
Mistral recommends Mistral Medium 3.5 for new integrations. Source
API identifier
devstral-medium-2507 Source
Documented integration features
This exact model page lists Structured Outputs, Function Calling, Batching. For archived models this describes the documented interface, not present API availability. Source

Which Devstral Medium 1.0 does this page describe?

Devstral Medium 1.0 is a model record from Mistral AI in the Devstral family. Source

The recorded model identifier or checkpoint is 25.07. Use that exact identifier when checking documentation or a provider listing. Source

How can you access Devstral Medium 1.0?

The catalog documents API access for Devstral Medium 1.0. Source

As of the catalog check, this version was marked deprecated. Source Check the linked lifecycle information before starting a new integration.

For API use, confirm the exact model identifier, your account and region, and the endpoint's current limits in the linked documentation. An API listing does not establish access through a consumer subscription.

What are Devstral Medium 1.0's context and output limits?

The documented context window is 128,000 tokens. Source

A separate maximum-output value is not established in this record. The context or input figure should not be used as an output allowance.

Context, input and output limits describe different constraints. Do not add the figures together to infer a larger window. Check the endpoint's accounting for conversation history, system instructions, tools, media and generated tokens; a documented maximum is not a guarantee of answer quality or a measured usable capacity.

What dates are documented for Devstral Medium 1.0?

Release date: July 10, 2025. Source This is a release milestone, not a knowledge or training cutoff. The source labels this “Release date on Mistral model specification.”

Neither a knowledge cutoff nor a training-data cutoff is established here. A release date, repository upload or filename cannot supply those missing dates.

Keep the exact version in view

Other Devstral models from Mistral AI.

These are separate records in the same publisher family. A shared family name does not establish equal capabilities or interchangeable licenses.

Devstral-Small-2507

API · Open weights · 128,000 context tokens

Devstral-Small-2505

API · Open weights · 128,000 context tokens

The documented record

Specifications, with their sources.

A missing value remains unknown. Input limits, output limits and the total context window are separate measurements.

Publisher
Mistral AISource ↗
Family
DevstralSource ↗
Version
25.07Source ↗
Availability
DeprecatedSource ↗
Access
APISource ↗
Inputs
Not documented
Outputs
Not documented
Context window
128,000 tokensSource ↗
Maximum input
Not documented
Maximum output
Not documented
Knowledge cutoff
Not documented
Training-data cutoff
Not documented
Training completed
Not documented
Release date
Jul 10, 2025Release date on Mistral model specification · day precisionSource ↗
License
Not documented
Input price / 1M tokens
Not documented
Output price / 1M tokens
Not documented

Read this with the numbers.

Mistral context shorthand 128k is represented in nominal decimal tokens.

Model identifiers and aliases 0

No additional identifier has been verified.

Follow the evidence

Official sources.

  1. devstral medium 1 0 25 07 — official Mistral AI documentation ↗docs.mistral.ai

From the Headless Thrones newsroom

Editorial about Devstral Medium 1.0

No published articles are linked to this exact model yet. New coverage will appear here as it is published.

Your starting point

Devstral Medium 1.0

Mistral AI · API

Browse all models ↗
Inputs
Not documented
Outputs
Not documented
Context window
128,000 tokensSource ↗
Knowledge cutoff
Not documented

A place to begin comparing

0 models to consider.

Matches must share an access route, support every documented input type of your starting model, and return text. When both publish a context limit in the same field, the candidate must fall between half and twice that limit. Unknown or differently defined limits remain as broader matches, after verified near-context matches. Within each group, recent documented releases appear first. These criteria do not establish equal quality. The full current inventory is considered.

No candidate meets the documented access, input/output and context criteria. You can still choose models manually in the comparison tool.

A record you can follow

The source belongs beside the fact.

Official sources

Model records cite the developer’s documentation, release notes and model cards. A listing alone is not a tested service or a recommendation.

Dates mean different things

Knowledge cutoff, training-data cutoff, training completion and release date are separate fields. A model’s name or repository upload date does not establish any of them.

Limits need context

Some publishers use rounded K/M token figures. Deployment, reasoning settings and regional access can change usable limits. Read the source before choosing.

Coverage and last check

Independent editorial model library assembled from primary vendor documentation and official publisher model cards. This is a dated, auditable inventory of the sources reviewed, not a claim to every model worldwide. First-party language-model inventory for OpenAI, Anthropic, Google Gemini/Gemma, xAI, Meta and Reflection. Includes vendor-listed legacy/retired identities with explicit statuses; official pretrained and instruction-tuned checkpoints remain distinct. Excludes embeddings, moderation/guard models, image/audio/video-only generation, community fine-tunes, speculative draft helpers, format/runtime/quantization duplicates, and PaliGemma dataset-specific benchmark fine-tunes. Availability means documented vendor API or downloadable official weights, not guaranteed account eligibility. Unknown specifications and dates remain null. Rounded K/M limits preserve vendor granularity; exact integers are used only where documented. No OpenRouter facts are used. Primary-source inventory of language-capable models from Alibaba/Qwen, DeepSeek, Moonshot, MiniMax, Z.ai, ByteDance Seed, Tencent, Baidu, Xiaomi, StepFun, 01.AI, Shanghai AI Laboratory, Baichuan and OpenBMB. Includes full reachable official public weight inventories plus documented hosted API models and explicit retirements. Embeddings, reward/classifier/router/tokenizer/draft-head components, standalone OCR/document converters and image/video/audio-only generators are excluded; multimodal language models retained. Official packaging variants are folded into aliases where a canonical listing was identifiable; remaining research/base/SFT variants retain exact identities. Not a guarantee every historical/private/regional model is available. Unknown specifications remain null; K/M API display quantities use decimal normalization where explicitly noted, rather than implying verified exact serving ceilings. Model-name dates and repository creation timestamps are never used as release/training dates. Open weights does not mean unrestricted or OSI-open-source licensing. Some model-card bodies were unreachable; their public inventory metadata is retained and disclosed. Official Mistral, Cohere, AI21, NVIDIA Nemotron, Microsoft Phi/MAI, Amazon Nova, IBM Granite, AllenAI OLMo/Molmo, TII Falcon, Nous Research, Arcee and Essential AI model inventory checked 2026-10-23. Includes base, instruction, reasoning, coding and text-producing multimodal models, including legacy API versions. Excludes embeddings/rerankers/reward and safety classifiers, image/audio/video-only generation, robotics-only models, duplicate quantization/runtime packages, adapters, intermediate checkpoint experiments, and third-party mirrors. Arcee coverage focuses on its named product families rather than exploratory merge repositories. Repository listing means listed, not independently verified API availability. K/M figures are nominal decimal normalizations when the source supplies shorthand; deployment-specific exact token limits may differ. Unverified values remain null. This is a source-backed inventory, not a complete claim-level independent editorial review. Supplemental official Liquid AI, Reka and Inception generative language catalog. Excludes media-only generators and decision/classification-only models. No assumed training dates.

Catalog edition updated . Source links are provided on each model record.

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