Pick GPT-5.2 for strong all-round reasoning or reliable structured output. Pick Mistral Large 3 for european data-residency option or strong multilingual performance. On a tight budget at scale, GPT-5.2 is the value pick.
GPT-5.2 (OpenAI, US) 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. GPT-5.2 is a capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. 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
Price: GPT-5.2 is about 1.3× cheaper on input ($1.5/$10 per 1M tokens vs $2/$6 per 1M tokens) — modest, but it adds up at steady volume.
Context window: GPT-5.2 holds 1.6× more — 400K (~600 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: Mistral Large 3 is the newer model by about 17 days (released 2026), usually meaning fresher training data and capabilities.
Ecosystem: this is a US-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
GPT-5.2
Mistral Large 3
Provider
OpenAI (US)
Mistral (France)
Released
2026
2026
Context window
400K (~600 pages)
256K (~384 pages)
Price (in/out)
$1.5/$10 per 1M tokens
$2/$6 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong all-round reasoning: GPT-5.2 — A core design strength of GPT-5.2.
Reliable structured output: GPT-5.2 — A core design strength of GPT-5.2.
Broad ecosystem and tooling: GPT-5.2 — A core design strength of GPT-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: GPT-5.2 — At $1.5/$10 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: GPT-5.2 — Its 400K window is about 1.6× larger, fitting roughly 600 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GPT-5.2 — At $1.5/$10 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: GPT-5.2 — Larger 400K window fits more in one prompt.
Anyone whose priority is strong all-round reasoning: GPT-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: GPT-5.2 or Mistral Large 3 — Origin (US vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GPT-5.2: where it fits
A capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. Released 2026 by OpenAI, it is built for strong all-round reasoning, reliable structured output, broad ecosystem and tooling, and professional workflows.
Its trade-offs are real: superseded by GPT-5.5, and smaller context than flagships. At $1.5 in / $10 out per million tokens, it sits in the mid price band.
Mistral Large 3: where it fits
France's frontier contender — strong multilingual model with European data residency. Released 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
This is less "which is smarter" and more "which ecosystem fits." GPT-5.2 (US) and Mistral Large 3 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. GPT-5.2 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 GPT-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, GPT-5.2 leans toward strong all-round reasoning while Mistral Large 3 leans toward european data-residency option, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.2 or Mistral Large 3?
GPT-5.2 is cheaper — $1.5/$10 per 1M tokens vs $2/$6 per 1M tokens, roughly 1.3× apart on input.
Which has the bigger context window?
GPT-5.2 — 400K vs 256K, about 1.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.2 and Mistral Large 3 together?
Yes — a multi-model platform like LumiChats gives you GPT-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, GPT-5.2 or Mistral Large 3?
Mistral Large 3 — released 2026, about 17 days after GPT-5.2.
GPT-5.2 vs Mistral Large 3
OpenAI · US | Mistral · France · Updated June 2026
Quick verdict
Pick GPT-5.2 for strong all-round reasoning or reliable structured output. Pick Mistral Large 3 for european data-residency option or strong multilingual performance. On a tight budget at scale, GPT-5.2 is the value pick.
GPT-5.2 (OpenAI, US) 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. GPT-5.2 is a capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. 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: GPT-5.2 is about 1.3× cheaper on input ($1.5/$10 per 1M tokens vs $2/$6 per 1M tokens) — modest, but it adds up at steady volume.
▸Context window: GPT-5.2 holds 1.6× more — 400K (~600 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: Mistral Large 3 is the newer model by about 17 days (released 2026), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a US-vs-France matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
GPT-5.2
Mistral Large 3
Provider
OpenAI (US)
Mistral (France)
Released
2026
2026
Context window
400K (~600 pages)
256K (~384 pages)
Price (in/out)
$1.5/$10 per 1M tokens
$2/$6 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong all-round reasoning
GPT-5.2
A core design strength of GPT-5.2.
Reliable structured output
GPT-5.2
A core design strength of GPT-5.2.
Broad ecosystem and tooling
GPT-5.2
A core design strength of GPT-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
GPT-5.2
At $1.5/$10 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
GPT-5.2
Its 400K window is about 1.6× larger, fitting roughly 600 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-5.2
At $1.5/$10 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
→ GPT-5.2
Larger 400K window fits more in one prompt.
Anyone whose priority is strong all-round reasoning
→ GPT-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
→ GPT-5.2 or Mistral Large 3
Origin (US vs France) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GPT-5.2: where it fits
A capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. Released 2026 by OpenAI, it is built for strong all-round reasoning, reliable structured output, broad ecosystem and tooling, and professional workflows.
Its trade-offs are real: superseded by GPT-5.5, and smaller context than flagships. At $1.5 in / $10 out per million tokens, it sits in the mid price band.
Mistral Large 3: where it fits
France's frontier contender — strong multilingual model with European data residency. Released 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
This is less "which is smarter" and more "which ecosystem fits." GPT-5.2 (US) and Mistral Large 3 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. GPT-5.2 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 GPT-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, GPT-5.2 leans toward strong all-round reasoning while Mistral Large 3 leans toward european data-residency option, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.2 or Mistral Large 3?
GPT-5.2 is cheaper — $1.5/$10 per 1M tokens vs $2/$6 per 1M tokens, roughly 1.3× apart on input.
Which has the bigger context window?
GPT-5.2 — 400K vs 256K, about 1.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.2 and Mistral Large 3 together?
Yes — a multi-model platform like LumiChats gives you GPT-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, GPT-5.2 or Mistral Large 3?
Mistral Large 3 — released 2026, about 17 days after GPT-5.2.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.