Kimi K3 vs Mistral Medium 3.5

Moonshot AI · China  |  Mistral AI · France · Updated June 2026

Quick verdict

Pick Kimi K3 for largest open-weight model at release — 2.8t sparse moe, self-hostable or 1m-token context with native vision (text, image and video). 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. On a tight budget at scale, Mistral Medium 3.5 is the value pick.

Kimi K3 (Moonshot AI, China) and Mistral Medium 3.5 (Mistral AI, France) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Kimi K3 is moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores. 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). 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

SpecKimi K3Mistral Medium 3.5
ProviderMoonshot AI (China) Mistral AI (France)
ReleasedJuly 27, 2026 April 29, 2026
Context window1M (~1,573 pages) 256K (~384 pages)
Price (in/out)$3/$15 per 1M tokens $1.5/$7.5 per 1M tokens
Open weight?Yes — self-hostable Yes — self-hostable
Modalitiestext, image, video, code text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Largest open-weight model at release — 2.8T sparse MoE, self-hostable

Kimi K3

Moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores — and it carries the larger 1M context.

1M-token context with native vision (text, image and video)

Kimi K3

Its 1M window holds about 4.1× more than Mistral Medium 3.5's 256K in a single prompt.

Vendor reports 81.2 FrontierSWE and 88.3 Terminal-Bench 2.1 on its own harness

Kimi K3

Moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores — and it is the newer of the two.

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

Mistral Medium 3.5

At $1.5/$7.5 per 1M tokens it undercuts Kimi K3 ($3/$15 per 1M tokens), and that gap compounds at volume.

128B dense open-weight model — self-hostable

Mistral Medium 3.5

Kimi K3 is comparatively weak here — 2.8T params need serious hardware to self-host — weights are free, running is not

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

Mistral Medium 3.5

Kimi K3 is comparatively weak here — coding scores use Moonshot FrontierSWE, not standard SWE-Bench Verified

Lowest cost at scale

Mistral Medium 3.5

At $1.5/$7.5 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Largest single-prompt input

Kimi K3

Its 1M window is about 4.1× larger than Mistral Medium 3.5's 256K, fitting roughly 1,573 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

Mistral Medium 3.5

At $1.5/$7.5 per 1M tokens it undercuts Kimi K3, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

Kimi K3

Larger 1M window fits more in one prompt.

Anyone whose priority is largest open-weight model at release — 2.8t sparse moe, self-hostable

Kimi K3

It is specifically built for that.

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

Mistral Medium 3.5

That is its strongest area.

An enterprise with regional data-residency rules

Mistral Medium 3.5 or Kimi K3

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

Kimi K3: where it fits

Moonshot's 2.8-trillion-parameter open-weight model — the largest open AI at release, with a 1M context and strong self-reported coding scores. Released July 27, 2026 by Moonshot AI, it is built for largest open-weight model at release — 2.8T sparse MoE, self-hostable, 1M-token context with native vision (text, image and video), vendor reports 81.2 FrontierSWE and 88.3 Terminal-Bench 2.1 on its own harness, and fresh-input pricing of $3/M (cached $0.30/M), flat across the full 1M context.

Its trade-offs are real: coding scores use Moonshot FrontierSWE, not standard SWE-Bench Verified, 2.8T params need serious hardware to self-host — weights are free, running is not, no independent benchmark reproduction yet at release, and image input but no audio or video. At $3 in / $15 out per million tokens, it sits in the mid price band.

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 29, 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: 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.

The bottom line for this matchup

This is less "which is smarter" and more "which ecosystem fits." Kimi K3 (China) and Mistral Medium 3.5 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Mistral Medium 3.5 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 Kimi K3 and Mistral Medium 3.5 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 Kimi K3 or Mistral Medium 3.5 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, Kimi K3 leans toward largest open-weight model at release — 2.8t sparse moe, self-hostable while Mistral Medium 3.5 leans toward strong intelligence-for-size — artificial analysis intelligence index 30, near the top of its price tier, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Kimi K3 or Mistral Medium 3.5?

Mistral Medium 3.5 is cheaper — $3/$15 per 1M tokens vs $1.5/$7.5 per 1M tokens, roughly 2× apart on input.

Which has the bigger context window?

Kimi K3 — 1M vs 256K, about 4.1× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Kimi K3 and Mistral Medium 3.5 together?

Yes — a multi-model platform like LumiChats gives you Kimi K3, Mistral Medium 3.5 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, Kimi K3 or Mistral Medium 3.5?

Kimi K3 — released July 27, 2026, about 3 months after Mistral Medium 3.5.

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.