Compare · Llama 4 (Maverick / Scout) vs Mistral Large 2

Llama 4 (Maverick / Scout) vs Mistral Large 2: run the same prompt through both.

Meta's Llama 4 and Mistral's Large 2 are the two most-deployed open-weight frontier models. Both can run on your own infrastructure — but they behave quite differently on real prompts.

Head-to-head
Llama 4 (Maverick / Scout)Mistral Large 2
MakerMeta AIMistral AI (Paris)
LicenseOpen weights (Llama 4 community license)Open weights (Mistral Research / commercial)
Flagship modelsLlama 4 Maverick, Llama 4 ScoutMistral Large 2, Codestral, Pixtral
HostingSelf-host, hyperscaler-hosted, or via BackplainSelf-host, EU-hosted, or via Backplain
StrengthsStrong general reasoning, huge community fine-tune ecosystem, cheapest at scaleEfficient reasoning, excellent code (Codestral), EU data residency
Trade-offsSlightly behind Mistral on code; guardrails vary by deploymentSmaller ecosystem; fewer fine-tunes available
MultimodalText + image (Maverick)Text + image (Pixtral)
Best fitTeams wanting maximum model portability and low per-token costTeams wanting EU-hosted inference and strong code reasoning
Available in BackplainYes — Maverick and ScoutYes — Large 2, Codestral, Pixtral

Open-weight doesn't mean "worse than closed" — Llama 4 and Mistral Large 2 both compete with the frontier closed models on many tasks, and win outright on cost-per-token and on the ability to run inside your own network.

The choice between them is usually about ecosystem and geography. Llama 4 has the larger fine-tune community and the widest hosting availability. Mistral has EU data residency, cleaner licensing for commercial use, and Codestral — one of the strongest specialized coding models available at any price.

Backplain runs both, either through hyperscaler endpoints or on our own infrastructure for Sovereign Compute customers. Compare them next to GPT-5 and Claude on the same prompt to see where "good enough" actually is.

The honest answer

Benchmarks are a starting point, not an answer. The only way to know which model is right for your use case is to run your prompt through both and read the responses side by side. That's the entire premise of Backplain.

In one workspace you can send the same prompt to Llama 4 (Maverick / Scout), Mistral Large 2, and up to eight more frontier models simultaneously — with the same attached files, the same system prompt, and the AI Firewall redacting PII before either model sees it. See how model comparison works →

Compare Llama 4 (Maverick / Scout) and Mistral Large 2 on your own prompt.

Three free multi-model prompts. No signup.