Pick GLM 5.2 for long-horizon agentic coding or project-level software engineering. Pick Mistral Large 3 for european data-residency option or strong multilingual performance. Choose GLM 5.2 if you need self-hosting or data privacy; Mistral Large 3 if you want a managed API.
GLM 5.2 (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 5.2 is an open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. Mistral Large 3 is france's frontier contender — strong multilingual model with European data residency. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: GLM 5.2 is about 2× cheaper on input ($0.98/$3.08 per 1M tokens vs $2/$6 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: GLM 5.2 holds 3.9× more — 1M (~1,500 pages) vs 256K (~384 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 5.2 is the newer model by about 5 months (released June 16, 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.
Specifications
Spec
GLM 5.2
Mistral Large 3
Provider
Z.ai (China)
Mistral (France)
Released
June 16, 2026
February 2026
Context window
1M (~1,500 pages)
256K (~384 pages)
Price (in/out)
$0.98/$3.08 per 1M tokens
$2/$6 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-horizon agentic coding: GLM 5.2 — A core design strength of GLM 5.2.
Project-level software engineering: GLM 5.2 — A core design strength of GLM 5.2.
Tool use across long-running tasks: GLM 5.2 — A core design strength of GLM 5.2.
European data-residency option: Mistral Large 3 — A core design strength of Mistral Large 3.
Strong multilingual performance: Mistral Large 3 — A core design strength of Mistral Large 3.
Efficient inference: Mistral Large 3 — A core design strength of Mistral Large 3.
Lowest cost at scale: GLM 5.2 — At $0.98/$3.08 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: GLM 5.2 — Its 1M window is about 3.9× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GLM 5.2 — At $0.98/$3.08 per 1M tokens it undercuts Mistral Large 3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GLM 5.2 — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: GLM 5.2 — Open weights let you run it on your own hardware; Mistral Large 3 is API-only.
Anyone whose priority is long-horizon agentic coding: GLM 5.2 — It is specifically built for that.
Anyone whose priority is european data-residency option: Mistral Large 3 — That is its strongest area.
An enterprise with regional data-residency rules: Mistral Large 3 or GLM 5.2 — Origin (China vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GLM 5.2: where it fits
An open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. Released June 16, 2026 by Z.ai, it is built for long-horizon agentic coding, project-level software engineering, tool use across long-running tasks, and tops the open-weight intelligence index.
Its trade-offs are real: text-only — no native multimodal input, and new release with a limited third-party track record. At $0.98 in / $3.08 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 February 2026 by Mistral, it is built for european data-residency option, strong multilingual performance, efficient inference, and function calling.
Its trade-offs: smaller context than US/China frontier, and less benchmark coverage. At $2 in / $6 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. GLM 5.2 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Mistral Large 3 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Frequently asked questions
Is GLM 5.2 or Mistral Large 3 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 5.2 leans toward long-horizon agentic coding while Mistral Large 3 leans toward european data-residency option, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5.2 or Mistral Large 3?
GLM 5.2 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Mistral Large 3 is API-metered at $2/$6 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
GLM 5.2 — 1M vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GLM 5.2 and Mistral Large 3 together?
Yes — a multi-model platform like LumiChats gives you GLM 5.2, 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 5.2 or Mistral Large 3?
GLM 5.2 — released June 16, 2026, about 5 months after Mistral Large 3.
GLM 5.2 vs Mistral Large 3
Z.ai · China | Mistral · France · Updated June 2026
Quick verdict
Pick GLM 5.2 for long-horizon agentic coding or project-level software engineering. Pick Mistral Large 3 for european data-residency option or strong multilingual performance. Choose GLM 5.2 if you need self-hosting or data privacy; Mistral Large 3 if you want a managed API.
GLM 5.2 (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 5.2 is an open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. Mistral Large 3 is france's frontier contender — strong multilingual model with European data residency. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: GLM 5.2 is about 2× cheaper on input ($0.98/$3.08 per 1M tokens vs $2/$6 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: GLM 5.2 holds 3.9× more — 1M (~1,500 pages) vs 256K (~384 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 5.2 is the newer model by about 5 months (released June 16, 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 5.2
Mistral Large 3
Provider
Z.ai (China)
Mistral (France)
Released
June 16, 2026
February 2026
Context window
1M (~1,500 pages)
256K (~384 pages)
Price (in/out)
$0.98/$3.08 per 1M tokens
$2/$6 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-horizon agentic coding
GLM 5.2
A core design strength of GLM 5.2.
Project-level software engineering
GLM 5.2
A core design strength of GLM 5.2.
Tool use across long-running tasks
GLM 5.2
A core design strength of GLM 5.2.
European data-residency option
Mistral Large 3
A core design strength of Mistral Large 3.
Strong multilingual performance
Mistral Large 3
A core design strength of Mistral Large 3.
Efficient inference
Mistral Large 3
A core design strength of Mistral Large 3.
Lowest cost at scale
GLM 5.2
At $0.98/$3.08 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
GLM 5.2
Its 1M window is about 3.9× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GLM 5.2
At $0.98/$3.08 per 1M tokens it undercuts Mistral Large 3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GLM 5.2
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ GLM 5.2
Open weights let you run it on your own hardware; Mistral Large 3 is API-only.
Anyone whose priority is long-horizon agentic coding
→ GLM 5.2
It is specifically built for that.
Anyone whose priority is european data-residency option
→ Mistral Large 3
That is its strongest area.
An enterprise with regional data-residency rules
→ Mistral Large 3 or GLM 5.2
Origin (China vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GLM 5.2: where it fits
An open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. Released June 16, 2026 by Z.ai, it is built for long-horizon agentic coding, project-level software engineering, tool use across long-running tasks, and tops the open-weight intelligence index.
Its trade-offs are real: text-only — no native multimodal input, and new release with a limited third-party track record. At $0.98 in / $3.08 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 February 2026 by Mistral, it is built for european data-residency option, strong multilingual performance, efficient inference, and function calling.
Its trade-offs: smaller context than US/China frontier, and less benchmark coverage. At $2 in / $6 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. GLM 5.2 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Mistral Large 3 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both GLM 5.2 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.
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 5.2 leans toward long-horizon agentic coding while Mistral Large 3 leans toward european data-residency option, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5.2 or Mistral Large 3?
GLM 5.2 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Mistral Large 3 is API-metered at $2/$6 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
GLM 5.2 — 1M vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GLM 5.2 and Mistral Large 3 together?
Yes — a multi-model platform like LumiChats gives you GLM 5.2, 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 5.2 or Mistral Large 3?
GLM 5.2 — released June 16, 2026, about 5 months after Mistral Large 3.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.