GLM 5 vs Mistral Large 3
Z.ai · China | Mistral · France · Updated June 2026
Quick verdict
Pick GLM 5 for agentic planning and long-horizon coding workflows or complex systems design and backend reasoning. Pick Mistral Large 3 for open-weight (apache 2.0), self-hostable or strong multilingual performance. On a tight budget at scale, Mistral Large 3 is the value pick.
GLM 5 (Z.ai, China) and Mistral Large 3 (Mistral, 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 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Mistral Large 3 is france's frontier contender — strong multilingual model with European data residency. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: Mistral Large 3 is about 2× cheaper on input ($0.5/$1.5 per 1M tokens vs $1/$3.2 per 1M tokens) — meaningful once you are processing millions of tokens a month.
- ▸Context window: Mistral Large 3 holds 1.3× more — 256K (~384 pages) vs 200K (~300 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: GLM 5 is the newer model by about 2 months (released February 12, 2026), usually meaning fresher training data and capabilities.
- ▸Ecosystem: this is a China-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | GLM 5 | Mistral Large 3 |
|---|---|---|
| Provider | Z.ai (China) | Mistral (France) |
| Released | February 12, 2026 | December 2, 2025 |
| Context window | 200K (~300 pages) | 256K (~384 pages) |
| Price (in/out) | $1/$3.2 per 1M tokens | $0.5/$1.5 per 1M tokens |
| Open weight? | Yes — self-hostable | Yes — self-hostable |
| Modalities | text, code | text, image, code |
| SWE-Bench Verified | 77.8% | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Agentic planning and long-horizon coding workflows
GLM 5
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding — and it is the newer of the two.
Complex systems design and backend reasoning
GLM 5
GLM 5 lists complex systems design and backend reasoning among its strengths; Mistral Large 3 does not.
Iterative self-correction on autonomous tasks
GLM 5
GLM 5 lists iterative self-correction on autonomous tasks among its strengths; Mistral Large 3 does not.
Open-weight (Apache 2.0), self-hostable
Mistral Large 3
France's frontier contender — strong multilingual model with European data residency — and it runs cheaper at $0.5/$1.5 per 1M tokens.
Strong multilingual performance
Mistral Large 3
France's frontier contender — strong multilingual model with European data residency — and it carries the larger 256K context.
Efficient inference
Mistral Large 3
Mistral Large 3 lists efficient inference among its strengths; GLM 5 does not.
Lowest cost at scale
Mistral Large 3
At $0.5/$1.5 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Mistral Large 3
Its 256K window is about 1.3× larger than GLM 5's 200K, fitting roughly 384 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Mistral Large 3
At $0.5/$1.5 per 1M tokens it undercuts GLM 5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Mistral Large 3
Larger 256K window fits more in one prompt.
Anyone whose priority is agentic planning and long-horizon coding workflows
→ GLM 5
It is specifically built for that.
Anyone whose priority is open-weight (apache 2.0), self-hostable
→ Mistral Large 3
That is its strongest area.
An enterprise with regional data-residency rules
→ Mistral Large 3 or GLM 5
Origin (China vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GLM 5: where it fits
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Released February 12, 2026 by Z.ai, it is built for agentic planning and long-horizon coding workflows, complex systems design and backend reasoning, iterative self-correction on autonomous tasks, and open weights under the permissive MIT license.
Its trade-offs are real: 200K context trails 1M-context rivals, and quickly superseded by GLM-5.1 and GLM-5.2. At $1 in / $3.2 out per million tokens, it sits in the budget price band.
Mistral Large 3: where it fits
France's frontier contender — strong multilingual model with European data residency. Released December 2, 2025 by Mistral, it is built for open-weight (Apache 2.0), self-hostable, strong multilingual performance, efficient inference, and function calling.
Its trade-offs: smaller context than US/China frontier, and less benchmark coverage. At $0.5 in / $1.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." GLM 5 (China) and Mistral Large 3 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Mistral Large 3 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 and Mistral Large 3 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 pricingFrequently asked questions
Is GLM 5 or Mistral Large 3 better for coding?
Public SWE-Bench figures are not available for Mistral Large 3, so the honest test is your own repository — run an identical real bug through both. By design, GLM 5 leans toward agentic planning and long-horizon coding workflows while Mistral Large 3 leans toward open-weight (apache 2.0), self-hostable, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5 or Mistral Large 3?
Mistral Large 3 is cheaper — $1/$3.2 per 1M tokens vs $0.5/$1.5 per 1M tokens, roughly 2× apart on input.
Which has the bigger context window?
Mistral Large 3 — 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 and Mistral Large 3 together?
Yes — a multi-model platform like LumiChats gives you GLM 5, Mistral Large 3 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 or Mistral Large 3?
GLM 5 — released February 12, 2026, about 2 months after Mistral Large 3.
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.