Pick GLM 5 for agentic planning and long-horizon coding workflows or complex systems design and backend reasoning. 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 is the value pick.
GLM 5 (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 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. 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
Price: GLM 5 is about 1.5× cheaper on input ($1/$3.2 per 1M tokens vs $1.5/$7.5 per 1M tokens) — modest, but it adds up at steady volume.
Context window: Mistral Medium 3.5 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: Mistral Medium 3.5 is the newer model by about 3 months (released April 29, 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
Mistral Medium 3.5
Provider
Z.ai (China)
Mistral AI (France)
Released
February 11, 2026
April 29, 2026
Context window
200K (~300 pages)
256K (~384 pages)
Price (in/out)
$1/$3.2 per 1M tokens
$1.5/$7.5 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 runs cheaper at $1/$3.2 per 1M tokens.
Complex systems design and backend reasoning: GLM 5 — GLM 5 lists complex systems design and backend reasoning among its strengths; Mistral Medium 3.5 does not.
Iterative self-correction on autonomous tasks: GLM 5 — GLM 5 lists iterative self-correction on autonomous tasks among its strengths; Mistral Medium 3.5 does not.
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 does not.
Lowest cost at scale: GLM 5 — At $1/$3.2 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's 200K, fitting roughly 384 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GLM 5 — At $1/$3.2 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 agentic planning and long-horizon coding workflows: GLM 5 — 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 — 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 11, 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 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 (China) and Mistral Medium 3.5 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. GLM 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.
Frequently asked questions
Is GLM 5 or Mistral Medium 3.5 better for coding?
Public SWE-Bench figures are not available for Mistral Medium 3.5, 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 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 or Mistral Medium 3.5?
GLM 5 is cheaper — $1/$3.2 per 1M tokens vs $1.5/$7.5 per 1M tokens, roughly 1.5× 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 and Mistral Medium 3.5 together?
Yes — a multi-model platform like LumiChats gives you GLM 5, 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 or Mistral Medium 3.5?
Mistral Medium 3.5 — released April 29, 2026, about 3 months after GLM 5.
GLM 5 vs Mistral Medium 3.5
Z.ai · China | Mistral AI · 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 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 is the value pick.
GLM 5 (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 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. 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
▸Price: GLM 5 is about 1.5× cheaper on input ($1/$3.2 per 1M tokens vs $1.5/$7.5 per 1M tokens) — modest, but it adds up at steady volume.
▸Context window: Mistral Medium 3.5 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: Mistral Medium 3.5 is the newer model by about 3 months (released April 29, 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 Medium 3.5
Provider
Z.ai (China)
Mistral AI (France)
Released
February 11, 2026
April 29, 2026
Context window
200K (~300 pages)
256K (~384 pages)
Price (in/out)
$1/$3.2 per 1M tokens
$1.5/$7.5 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 runs cheaper at $1/$3.2 per 1M tokens.
Complex systems design and backend reasoning
GLM 5
GLM 5 lists complex systems design and backend reasoning among its strengths; Mistral Medium 3.5 does not.
Iterative self-correction on autonomous tasks
GLM 5
GLM 5 lists iterative self-correction on autonomous tasks among its strengths; Mistral Medium 3.5 does not.
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 does not.
Lowest cost at scale
GLM 5
At $1/$3.2 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's 200K, fitting roughly 384 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GLM 5
At $1/$3.2 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 agentic planning and long-horizon coding workflows
→ GLM 5
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
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 11, 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 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 (China) and Mistral Medium 3.5 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. GLM 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 GLM 5 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.
Public SWE-Bench figures are not available for Mistral Medium 3.5, 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 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 or Mistral Medium 3.5?
GLM 5 is cheaper — $1/$3.2 per 1M tokens vs $1.5/$7.5 per 1M tokens, roughly 1.5× 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 and Mistral Medium 3.5 together?
Yes — a multi-model platform like LumiChats gives you GLM 5, 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 or Mistral Medium 3.5?
Mistral Medium 3.5 — released April 29, 2026, about 3 months after GLM 5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.