AI MODEL PROFILE

Mistral Medium 3.5

A dense 128 billion parameter model designed to run on as few as four GPUs, which makes self hosting realistic rather than theoretical.

Source review Last reviewed August 7, 2026 By Mistral AI

The facts at a glance

ProviderMistral AI
TypeOpen weight model
Current version or tierMistral Medium 3.5, version tag v26.04, released May 2026
ModalityText and vision
AccessOpen weights under a modified MIT licence
Context or limits256,000 token context, 128 billion parameters, dense rather than mixture of experts
Free optionYes, weights on Hugging Face. Also in Le Chat and Mistral Vibe on paid plans
Paid priceUSD 1.50 per million input and USD 7.50 per million output

Pricing last checked August 7, 2026. Prices change and vary by region. Check the official pricing page ↗

Assessment

What it does well

  • Mistral reports 77.6 percent on SWE-Bench Verified and 91.4 on tau3-Telecom
  • Targets self hosting on as few as four GPUs, which is achievable for a small team
  • It replaced Devstral 2 as the default in Mistral's own coding agents, which is a meaningful internal endorsement

Where it falls short

  • A modified MIT licence is not plain MIT and needs reading
  • 256,000 token context is a quarter of what the current flagships offer
  • Mistral's own pages give conflicting release dates, so the exact date is unverified

Privacy and data control

Self hosting keeps data on your own infrastructure. Le Chat and Mistral Vibe are governed by Mistral's own terms, which we have not verified for this profile.

The longer read

Dense models still have a place

Most frontier releases now use mixture of experts designs with enormous total parameter counts. Medium 3.5 is dense and comparatively small, which makes it predictable to serve and realistic to run on hardware a startup can actually buy. That trade, capability ceiling for operational simplicity, is the right one more often than the benchmark tables suggest.

How it performs by outcome

We assess products against a job, not a leaderboard. These are the outcomes this entry is compared under.

Worth comparing against

How this profile was produced

Source review. Every fact here is drawn from the provider documentation linked below and checked on the date shown. We have not yet run this entry through a controlled test, and no scoring is implied.

Read the full review methodology →

Primary sources