Llama 4 Maverick vs Mistral Large 3

Meta · US  |  Mistral · France · Updated June 2026

Quick verdict

Pick Llama 4 Maverick for open weights, 1m context or strong image + text understanding. Pick Mistral Large 3 for open-weight (apache 2.0), self-hostable or strong multilingual performance. On a tight budget at scale, Llama 4 Maverick is the value pick.

Llama 4 Maverick (Meta, 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. Llama 4 Maverick is meta's open-weight 1M-context multimodal model for self-hosted deployments. 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

Side-by-side specs

SpecLlama 4 MaverickMistral Large 3
ProviderMeta (US) Mistral (France)
ReleasedApril 2025 December 2, 2025
Context window1M (~1,500 pages) 256K (~384 pages)
Price (in/out)Open weight (self-host / free) $0.5/$1.5 per 1M tokens
Open weight?Yes — self-hostable Yes — self-hostable
Modalitiestext, image, code text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Open weights, 1M context

Llama 4 Maverick

Its 1M window holds about 3.9× more than Mistral Large 3's 256K in a single prompt.

Strong image + text understanding

Llama 4 Maverick

Meta's open-weight 1M-context multimodal model for self-hosted deployments — and it carries the larger 1M context.

Self-hostable

Llama 4 Maverick

Llama 4 Maverick lists self-hostable among its strengths; Mistral Large 3 does not.

Open-weight (Apache 2.0), self-hostable

Mistral Large 3

France's frontier contender — strong multilingual model with European data residency — and it is the newer of the two.

Strong multilingual performance

Mistral Large 3

Mistral Large 3 lists strong multilingual performance among its strengths; Llama 4 Maverick does not.

Efficient inference

Mistral Large 3

Mistral Large 3 lists efficient inference among its strengths; Llama 4 Maverick does not.

Lowest cost at scale

Llama 4 Maverick

Its weights are open, so at volume you pay for your own hardware instead of Mistral Large 3's $0.5/$1.5 per 1M tokens.

Largest single-prompt input

Llama 4 Maverick

Its 1M window is about 3.9× larger than Mistral Large 3's 256K, fitting roughly 1,500 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

Llama 4 Maverick

At Open weight (self-host / free) it undercuts Mistral Large 3, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

Llama 4 Maverick

Larger 1M window fits more in one prompt.

Anyone whose priority is open weights, 1m context

Llama 4 Maverick

It is specifically built for that.

Anyone whose priority is open-weight (apache 2.0), self-hostable

Mistral Large 3

That is its strongest area.

An enterprise with regional data-residency rules

Llama 4 Maverick 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.

Llama 4 Maverick: where it fits

Meta's open-weight 1M-context multimodal model for self-hosted deployments. Released April 2025 by Meta, it is built for open weights, 1M context, strong image + text understanding, self-hostable, and 400B MoE, 17B active.

Its trade-offs are real: needs serious hardware to self-host, and trails closed frontier on reasoning. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

Mistral Large 3: where it fits

France's frontier contender — strong multilingual model with European data residency. Released December 2, 2025 by Mistral, it is built for open-weight (Apache 2.0), self-hostable, strong multilingual performance, efficient inference, and function calling.

Its trade-offs: smaller context than US/China frontier, and less benchmark coverage. At $0.5 in / $1.5 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." Llama 4 Maverick (US) and Mistral Large 3 (France) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Llama 4 Maverick 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 Llama 4 Maverick 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.

See pricing

Frequently asked questions

Is Llama 4 Maverick 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, Llama 4 Maverick leans toward open weights, 1m context while Mistral Large 3 leans toward open-weight (apache 2.0), self-hostable, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Llama 4 Maverick or Mistral Large 3?

Llama 4 Maverick is cheaper — Open weight (self-host / free) vs $0.5/$1.5 per 1M tokens.

Which has the bigger context window?

Llama 4 Maverick — 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 Llama 4 Maverick and Mistral Large 3 together?

Yes — a multi-model platform like LumiChats gives you Llama 4 Maverick, 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, Llama 4 Maverick or Mistral Large 3?

Mistral Large 3 — released December 2, 2025, about 8 months after Llama 4 Maverick.

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.