GPT-5.2 vs Mistral Large 4

OpenAI · US  |  Mistral AI · France · Updated June 2026

Quick verdict

Pick GPT-5.2 for strong all-round reasoning or reliable structured output. Pick Mistral Large 4 for mistral's largest model to date — 1.05t total parameters, 49b active per token (granular moe), plus a 1.6b-parameter vision encoder or trained from scratch on 3,800 nvidia grace blackwell gpus in mistral's own european data centers, across 160+ languages. On a tight budget at scale, Mistral Large 4 is the value pick.

GPT-5.2 (OpenAI, US) and Mistral Large 4 (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. GPT-5.2 is a capable GPT-5-generation all-rounder, now succeeded by GPT-5.5. Mistral Large 4 is mistral's October 6, 2026 public preview of 'Le Chonk' — a 1.05T-parameter, natively multimodal MoE model with open weights planned by month's end. 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

SpecGPT-5.2Mistral Large 4
ProviderOpenAI (US) Mistral AI (France)
ReleasedDecember 11, 2025 October 6, 2026
Context window400K (~600 pages) 1M tokens (~1,500 pages)
Price (in/out)$1.75/$14 per 1M tokens $0.68/$2.09 per 1M tokens
Open weight?No — API only No — API only
Modalitiestext, image, code text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Strong all-round reasoning

GPT-5.2

GPT-5.2 lists strong all-round reasoning among its strengths; Mistral Large 4 does not.

Reliable structured output

GPT-5.2

GPT-5.2 lists reliable structured output among its strengths; Mistral Large 4 does not.

Broad ecosystem and tooling

GPT-5.2

GPT-5.2 lists broad ecosystem and tooling among its strengths; Mistral Large 4 does not.

Mistral's largest model to date — 1.05T total parameters, 49B active per token (granular MoE), plus a 1.6B-parameter vision encoder

Mistral Large 4

Its 1M tokens window holds about 2.5× more than GPT-5.2's 400K in a single prompt.

Trained from scratch on 3,800 Nvidia Grace Blackwell GPUs in Mistral's own European data centers, across 160+ languages

Mistral Large 4

Mistral's October 6, 2026 public preview of 'Le Chonk' — a 1.05T-parameter, natively multimodal MoE model with open weights planned by month's end — and it runs cheaper at $0.68/$2.09 per 1M tokens.

Hybrid instruct/reasoning design — answers quickly by default or switches into step-by-step reasoning

Mistral Large 4

Mistral's October 6, 2026 public preview of 'Le Chonk' — a 1.05T-parameter, natively multimodal MoE model with open weights planned by month's end — and it carries the larger 1M tokens context.

Lowest cost at scale

Mistral Large 4

At $0.68/$2.09 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 4

Its 1M tokens window is about 2.5× larger than GPT-5.2's 400K, fitting roughly 1,500 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Mistral Large 4

At $0.68/$2.09 per 1M tokens it undercuts GPT-5.2, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ Mistral Large 4

Larger 1M tokens 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 mistral's largest model to date — 1.05t total parameters, 49b active per token (granular moe), plus a 1.6b-parameter vision encoder

→ Mistral Large 4

That is its strongest area.

An enterprise with regional data-residency rules

→ GPT-5.2 or Mistral Large 4

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 December 11, 2025 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 $1.75 in / $14 out per million tokens, it sits in the mid price band.

Mistral Large 4: where it fits

Mistral's October 6, 2026 public preview of 'Le Chonk' — a 1.05T-parameter, natively multimodal MoE model with open weights planned by month's end. Released October 6, 2026 by Mistral AI, it is built for mistral's largest model to date — 1.05T total parameters, 49B active per token (granular MoE), plus a 1.6B-parameter vision encoder, trained from scratch on 3,800 Nvidia Grace Blackwell GPUs in Mistral's own European data centers, across 160+ languages, hybrid instruct/reasoning design — answers quickly by default or switches into step-by-step reasoning, and open weights planned by end of October 2026, which would make it among the largest open-weight models available.

Its trade-offs: still a public preview, not a finished release — Mistral says training is ongoing with 'no signs of saturation', weights not yet shipped as of mid-October 2026 — API-only for now despite the open-weight framing, launch pricing ($0.68/$2.09 per million) is a preview discount — Mistral's own model page lists a $1.36/$4.18 list price once the promotion ends, and scores 61.7% on DeepSWE v1.1, trailing DeepSeek V4.1 Flash (74.2%) and Kimi K3 (68.0%) on that coding benchmark. At $0.68 in / $2.09 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." GPT-5.2 (US) and Mistral Large 4 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Mistral Large 4 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 4 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 GPT-5.2 or Mistral Large 4 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 4 leans toward mistral's largest model to date — 1.05t total parameters, 49b active per token (granular moe), plus a 1.6b-parameter vision encoder, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, GPT-5.2 or Mistral Large 4?

Mistral Large 4 is cheaper — $1.75/$14 per 1M tokens vs $0.68/$2.09 per 1M tokens, roughly 2.6× apart on input.

Which has the bigger context window?

Mistral Large 4 — 1M tokens vs 400K, about 2.5× 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 4 together?

Yes — a multi-model platform like LumiChats gives you GPT-5.2, Mistral Large 4 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 4?

Mistral Large 4 — released October 6, 2026, about 10 months after GPT-5.2.

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.