Mistral Medium 3.5
Mistral AIfamily · Mistraldocs.mistral.ai/models/mistral-medium-3-5-26-04
Our frontier-class multimodal model optimized for agentic and coding use cases.
Updated 5 h ago · first seen 11 Sept 2026
model_01M2943ZSC4AD206PQPES6YA85
Overview
Identity
- Canonical model
- Yesidentity confidence: mediumOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
- Official checkpoints
- None recordedofficial_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
- Artifacts
- None recordedSeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
- Provider deployments
- 2
- API aliases
- mistral-medium-3-5mistralai/mistral-medium-3-5Identifiers under which providers and evaluators refer to this model.
- Folded evaluation variants
- 0Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.
Openness
Open weights— weights downloadable under MIT-Modified; commercial use allowed; redistribution allowed; derivatives allowed; 4 dimensions unknown.
Weights downloadable under a permissive or Creative Commons licence allowing commercial use; code or data may be missing.
Weights
Yes
Inference code
—
Training code
—
Training data
—
Dataset
—
Commercial use
Yes
Redistribution
Yes
Derivatives
Yes
Licence: Modified MIT License (permissive · stated as “Modified MIT”)
dimensions marked null are unknown, not false
Key facts
- Release date
Source:OpenRouter public model & pricing listingT2observed 16 h agomedium
- Version
Source:Mistral AI docsT1observed 16 h agohigh
- Official page
Source:Mistral AI docsT1observed 16 h agohigh
- Openrouter id
Source:OpenRouter public model & pricing listingT2observed 16 h agomedium
Architecture
- Tokenizer
Source:OpenRouter public model & pricing listingT2observed 16 h agomedium
Capabilities
Modalities
- Modalities
- documentimagetext
- Input
- documentimagetext
- Output
- text
Capabilities
Tool calling
Yes
Mistral AI docs · T1
Structured output
Yes
Mistral AI docs · T1
Reasoning
Yes
OpenRouter public model & pricing listing · T2
Vision
Yes
OpenRouter public model & pricing listing · T2
Audio
Unavailable
Fine-tuning available
Unavailable
- Context window
Source:Mistral AI docsT1observed 16 h agohigh
- Max output
Source:OpenRouter public model & pricing listingT2observed 16 h agomedium
- Tokenizer
Source:OpenRouter public model & pricing listingT2observed 16 h agomedium
Benchmarks20
Compare with another model →Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric
Current rows only, grouped by benchmark → canonical metric → comparability group (task configuration). Effort variants folded into this model appear as rows of the same group. 20 current rows in total. “vs leader” compares with the current leader of the benchmark's primary group only; other groups are not directly comparable. Comparability rules →
Providers & Pricing5
All offers in the price terminal →USD per 1M tokens as published by each provider; native units (per-request fees, flex/priority tiers) are kept verbatim. Rows are append-only — every price change is kept in the history below. Cost of a workload →
Price history
Output price · USD / 1M tokens 2 providers
- Mistral AI La Plateforme
- OpenRouter
- OpenRouter$7.5 → $3.7512 Sept 2026
- OpenRouterfirst observed $7.512 Sept 2026
- Mistral AI La Plateforme$7.5 → $3.7511 Sept 2026
- Mistral AI La Plateformefirst observed $7.511 Sept 2026
Input price · USD / 1M tokens 2 providers
- Mistral AI La Plateforme
- OpenRouter
- OpenRouter$1.5 → $0.7512 Sept 2026
- OpenRouterfirst observed $1.512 Sept 2026
- Mistral AI La Plateforme$1.5 → $0.7511 Sept 2026
- Mistral AI La Plateformefirst observed $1.511 Sept 2026
Versions & Artifacts0
Version history
Context windowfirst observation only
11 Sept 2026current
Licensefirst observation only
11 Sept 2026current
Max outputfirst observation only
11 Sept 2026current
Opennessfirst observation only
11 Sept 2026current
Each hop is a claim: click a value for its source, tier and observation time. Nothing is overwritten — a new observation closes the previous claim.
Artifacts 0
No artifact (checkpoint, quantisation, conversion or packaging) points to this model yet.
Timeline15
Full timeline →OpenRouter lists Mistral Medium 3.5 at $0.75 in / $3.75 out per 1M tokens
openrouterOpenRouter lists Mistral Medium 3.5 at $1.5 in / $7.5 out per 1M tokens
openrouterMistral Medium 3.5: modalities changed from ["image", "text"] to ["document", "image", "text"]
Modalitiesimage, text→document, image, textopenrouterMistral Medium 3.5: modalities input changed from ["image", "text"] to ["document", "image", "text"]
Input modalitiesimage, text→document, image, textopenrouterMistral Medium 3.5 scores 33.33% on Terminal-Bench
artificial_analysisMistral Medium 3.5 scores 50.56% on Terminal-Bench
artificial_analysisMistral Medium 3.5 scores 0% on Terminal-Bench
artificial_analysisMistral Medium 3.5 scores 94.15% on τ²-bench
artificial_analysisMistral Medium 3.5 scores 64.86% on MMMU-Pro
artificial_analysisMistral Medium 3.5 scores 68.78% on IFBench
artificial_analysisMistral Medium 3.5 scores 40.16% on SciCode
artificial_analysisMistral Medium 3.5 scores 13.76% on Humanity's Last Exam
artificial_analysisMistral Medium 3.5 scores 74.85% on GPQA Diamond
artificial_analysisMistral Medium 3.5 scores 14.89 on Artificial Analysis Intelligence Index
artificial_analysisMistral AI La Plateforme lists Mistral Medium 3.5 at $1.5 in / $7.5 out per 1M tokens
mistral
Change history37
Viewing AI Atlas as of 1 Sept 2026 — attributes exactly as the atlas knew them on that day; later corrections are not shown.
Back to today →Mistral Medium 3.5 was not yet in AI Atlas on 1 Sept 2026
Versionversion1
Release daterelease_date1
Opennessopenness1
Licenselicense1
Context windowcontext_length8conflicting claims
Max outputmax_output_tokens1
Modalitiesmodalities2
Input modalitiesmodalities_input2
Output modalitiesmodalities_output1
Tokenizertokenizer1
API aliasapi_alias1
Official pageofficial_url1
Aa context windowaa_context_window1
Aa opennessaa_openness1
Commercial use allowedcommercial_use_allowed1
Derivatives allowedderivatives_allowed1
Descriptiondescription1
File inputfile_input1
Aa median output tokens per secondmetric.aa_median_output_tokens_per_second1
Openrouter idopenrouter_id1
Openrouter listed atopenrouter_listed_at1
Reasoningreasoning1
Redistribution allowedredistribution_allowed1
Structured outputstructured_output1
Supported parameterssupported_parameters1
Tool callingtool_calling1
Visionvision1
Weights availableweights_available1
Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →
Provenance
Attributed facts
30
Source tiers
T1T29 / 21
Freshest observation
5 h ago
Conflicts
7 flagged
Source documents 4
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.
Data quality (74/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →