Mistral Medium 3.5 vs OLMo 3 32B Think

Mistral AI · France  |  Allen Institute for AI · US · Updated June 2026

Quick verdict

Pick Mistral Medium 3.5 for strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier or 128b dense open-weight model — self-hostable. Pick OLMo 3 32B Think for the most fully transparent open release available - ai2 publishes the complete weights, full dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/rl code, not just final weights or a genuine 32b reasoning ('think') model that generates explicit chain-of-thought. On a tight budget at scale, OLMo 3 32B Think is the value pick.

Mistral Medium 3.5 (Mistral AI, France) and OLMo 3 32B Think (Allen Institute for AI, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Mistral Medium 3.5 is mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). OLMo 3 32B Think is allen Institute for AI's fully-open 32B reasoning model - the rare release that ships the complete training data and process, not just the weights. They diverge most on price and context window — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecMistral Medium 3.5OLMo 3 32B Think
ProviderMistral AI (France) Allen Institute for AI (US)
ReleasedApril 28, 2026 November 20, 2025
Context window256K (~384 pages) 65K (~98 pages)
Price (in/out)$1.5/$7.5 per 1M tokens Open weight (self-host / free)
Open weight?Yes — self-hostable Yes — self-hostable
Modalitiestext, image, code text, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier

Mistral Medium 3.5

Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30) — and it carries the larger 256K context.

128B dense open-weight model — self-hostable

Mistral Medium 3.5

OLMo 3 32B Think is comparatively weak here — a 65K context window is modest next to million-token frontier models

Unifies reasoning and coding into one model with an adjustable reasoning effort

Mistral Medium 3.5

Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30) — and it is the newer of the two.

The most fully transparent open release available - Ai2 publishes the complete weights, full Dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/RL code, not just final weights

OLMo 3 32B Think

OLMo 3 32B Think lists the most fully transparent open release available - Ai2 publishes the complete weights, full Dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/RL code, not just final weights among its strengths; Mistral Medium 3.5 does not.

A genuine 32B reasoning ('Think') model that generates explicit chain-of-thought

OLMo 3 32B Think

OLMo 3 32B Think lists a genuine 32B reasoning ('Think') model that generates explicit chain-of-thought among its strengths; Mistral Medium 3.5 does not.

Fully open under Apache 2.0 - free to self-host

OLMo 3 32B Think

OLMo 3 32B Think lists fully open under Apache 2.0 - free to self-host among its strengths; Mistral Medium 3.5 does not.

Lowest cost at scale

OLMo 3 32B Think

Its weights are open, so at volume you pay for your own hardware instead of Mistral Medium 3.5's $1.5/$7.5 per 1M tokens.

Largest single-prompt input

Mistral Medium 3.5

Its 256K window is about 3.9× larger than OLMo 3 32B Think's 65K, fitting roughly 384 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

OLMo 3 32B Think

At Open weight (self-host / free) it undercuts Mistral Medium 3.5, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

Mistral Medium 3.5

Larger 256K window fits more in one prompt.

Anyone whose priority is strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier

Mistral Medium 3.5

It is specifically built for that.

Anyone whose priority is the most fully transparent open release available - ai2 publishes the complete weights, full dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/rl code, not just final weights

OLMo 3 32B Think

That is its strongest area.

An enterprise with regional data-residency rules

OLMo 3 32B Think or Mistral Medium 3.5

Origin (France vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.

Mistral Medium 3.5: where it fits

Mistral's efficient 128B open-weight model — a single dense model unifying reasoning and coding that punches above its size on independent tests (AA Index 30). Released April 28, 2026 by Mistral AI, it is built for strong intelligence-for-size — Artificial Analysis Intelligence Index 30, near the top of its price tier, 128B dense open-weight model — self-hostable, unifies reasoning and coding into one model with an adjustable reasoning effort, and 256K context with text and image input.

Its trade-offs are real: below the absolute frontier — a value/efficiency pick, not a flagship-beater, output pricing ($7.50/M) is higher than the cheapest Chinese rivals, license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use, and no native video or audio. At $1.5 in / $7.5 out per million tokens, it sits in the mid price band.

OLMo 3 32B Think: where it fits

Allen Institute for AI's fully-open 32B reasoning model - the rare release that ships the complete training data and process, not just the weights. Released November 20, 2025 by Allen Institute for AI, it is built for the most fully transparent open release available - Ai2 publishes the complete weights, full Dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/RL code, not just final weights, a genuine 32B reasoning ('Think') model that generates explicit chain-of-thought, fully open under Apache 2.0 - free to self-host, and built specifically to let researchers reproduce and audit exactly how the model was trained.

Its trade-offs: a 65K context window is modest next to million-token frontier models, prioritizes full openness and reproducibility over topping raw capability leaderboards, and 32B scale trails much larger frontier and open MoE models on general benchmarks. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

The bottom line for this matchup

This is less "which is smarter" and more "which ecosystem fits." Mistral Medium 3.5 (France) and OLMo 3 32B Think (US) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. OLMo 3 32B Think is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.

Want both Mistral Medium 3.5 and OLMo 3 32B Think without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.

See pricing

Frequently asked questions

Is Mistral Medium 3.5 or OLMo 3 32B Think better for coding?

Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Mistral Medium 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier while OLMo 3 32B Think leans toward the most fully transparent open release available - ai2 publishes the complete weights, full dolma training dataset, every training checkpoint, training logs, and pretraining/instruction-tuning/rl code, not just final weights, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Mistral Medium 3.5 or OLMo 3 32B Think?

OLMo 3 32B Think is cheaper — $1.5/$7.5 per 1M tokens vs Open weight (self-host / free).

Which has the bigger context window?

Mistral Medium 3.5 — 256K vs 65K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Mistral Medium 3.5 and OLMo 3 32B Think together?

Yes — a multi-model platform like LumiChats gives you Mistral Medium 3.5, OLMo 3 32B Think and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.

Which is newer, Mistral Medium 3.5 or OLMo 3 32B Think?

Mistral Medium 3.5 — released April 28, 2026, about 5 months after OLMo 3 32B Think.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.