Grok 4 vs Mistral Large 4

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

Quick verdict

Pick Grok 4 for 256k context with native tool use or real-time data via x integration. 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.

Grok 4 (xAI, 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. Grok 4 is xAI's 2M-context model with live data access and strong reasoning chops. 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

SpecGrok 4Mistral Large 4
ProviderxAI (US) Mistral AI (France)
ReleasedJuly 9, 2025 October 6, 2026
Context window256K (~384 pages) 1M tokens (~1,500 pages)
Price (in/out)$3/$15 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

256K context with native tool use

Grok 4

Grok 4 lists 256K context with native tool use among its strengths; Mistral Large 4 does not.

Real-time data via X integration

Grok 4

Grok 4 lists real-time data via X integration among its strengths; Mistral Large 4 does not.

Strong academic reasoning

Grok 4

Grok 4 lists strong academic reasoning 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 3.9× more than Grok 4's 256K 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 3.9× larger than Grok 4's 256K, 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 Grok 4, 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 256k context with native tool use

→ Grok 4

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

→ Grok 4 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.

Grok 4: where it fits

XAI's 2M-context model with live data access and strong reasoning chops. Released July 9, 2025 by xAI, it is built for 256K context with native tool use, real-time data via X integration, strong academic reasoning, and no long-context surcharge.

Its trade-offs are real: smaller ecosystem than OpenAI/Google, and less independent benchmark coverage. At $3 in / $15 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." Grok 4 (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 Grok 4 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 Grok 4 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, Grok 4 leans toward 256k context with native tool use 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, Grok 4 or Mistral Large 4?

Mistral Large 4 is cheaper — $3/$15 per 1M tokens vs $0.68/$2.09 per 1M tokens, roughly 4.4× apart on input.

Which has the bigger context window?

Mistral Large 4 — 1M tokens 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 Grok 4 and Mistral Large 4 together?

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

Mistral Large 4 — released October 6, 2026, about 15 months after Grok 4.

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.