GLM 5.1 vs Mistral Medium 3.5

Z.ai · China  |  Mistral AI · France · Updated June 2026

Quick verdict

Pick GLM 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs) or state-of-the-art open-weight coding (topped swe-bench pro at launch). 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, GLM 5.1 is the value pick.

GLM 5.1 (Z.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. GLM 5.1 is an open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. 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

SpecGLM 5.1Mistral Medium 3.5
ProviderZ.ai (China) Mistral AI (France)
ReleasedApril 7, 2026 April 29, 2026
Context window200K (~300 pages) 256K (~384 pages)
Price (in/out)$1.4/$4.4 per 1M tokens $1.5/$7.5 per 1M tokens
Open weight?Yes — self-hostable Yes — self-hostable
Modalitiestext, code text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Long-horizon autonomous agentic engineering (up to 8-hour runs)

GLM 5.1

An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours — and it runs cheaper at $1.4/$4.4 per 1M tokens.

State-of-the-art open-weight coding (topped SWE-Bench Pro at launch)

GLM 5.1

GLM 5.1 lists state-of-the-art open-weight coding (topped SWE-Bench Pro at launch) among its strengths; Mistral Medium 3.5 does not.

Sustained tool use across thousands of calls

GLM 5.1

Mistral Medium 3.5 is comparatively weak here — license framing ('open' vs enterprise) varies across sources — confirm terms for commercial use

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

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.

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

Mistral Medium 3.5

Mistral Medium 3.5 lists unifies reasoning and coding into one model with an adjustable reasoning effort among its strengths; GLM 5.1 does not.

Lowest cost at scale

GLM 5.1

At $1.4/$4.4 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Largest single-prompt input

Mistral Medium 3.5

Its 256K window is about 1.3× larger than GLM 5.1's 200K, fitting roughly 384 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

GLM 5.1

At $1.4/$4.4 per 1M tokens 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 long-horizon autonomous agentic engineering (up to 8-hour runs)

GLM 5.1

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 GLM 5.1

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

GLM 5.1: where it fits

An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. Released April 7, 2026 by Z.ai, it is built for long-horizon autonomous agentic engineering (up to 8-hour runs), state-of-the-art open-weight coding (topped SWE-Bench Pro at launch), sustained tool use across thousands of calls, and self-hostable under a permissive MIT license.

Its trade-offs are real: text-only, with no image, audio, or video input, and 754B-parameter MoE demands heavy GPU resources to self-host. At $1.4 in / $4.4 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." GLM 5.1 (China) and Mistral Medium 3.5 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. GLM 5.1 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 GLM 5.1 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 GLM 5.1 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, GLM 5.1 leans toward long-horizon autonomous agentic engineering (up to 8-hour runs) 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, GLM 5.1 or Mistral Medium 3.5?

GLM 5.1 is cheaper — $1.4/$4.4 per 1M tokens vs $1.5/$7.5 per 1M tokens, roughly 1.1× apart on input.

Which has the bigger context window?

Mistral Medium 3.5 — 256K vs 200K, about 1.3× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both GLM 5.1 and Mistral Medium 3.5 together?

Yes — a multi-model platform like LumiChats gives you GLM 5.1, 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, GLM 5.1 or Mistral Medium 3.5?

Mistral Medium 3.5 — released April 29, 2026, about 22 days after GLM 5.1.

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.