Llama 3.1 405B Instruct vs Mistral Large 3

At a Glance

Compare
Mistral Large 3Mistral AI
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.25Openrouter · Sep 22, 2026
Output priceFrom · USD / 1M tokensNot reported$0.75Openrouter · Sep 22, 2026
Context windowMaximum documented tokens131K262K
Model facts checkedAug 28, 2026View model evidence →Aug 29, 2026View model evidence →

Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →

Available Benchmarks

All benchmark results →
No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.

Side-by-Side Facts

FieldLlama-3.1-405B-InstructMistral Large 3
DeveloperMetaMistral AI
FamilyLlama 3 1 405b InstructMistral Large 3
ModelLlama-3.1-405B-InstructMistral Large 3
VersionLlama-3.1-405B-InstructMistral Large 3
Lifecycleactiveactive
Released2024-07-232025-12-02
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image, Document
Output modalitiesTextText
Context window131K262K
Total parameters405.9B675B
Active parametersUnknown41B
Licensellama3.1Apache-2.0
Open weightsYesYes
API availableYesYes
Self-hostableYesYes
Provider accessTogether Ai (Standard)Mistral AI (Standard), Openrouter (Standard)
Capabilitieschat, generation, toolsagents, chat, generation, structured_outputs, tools, vision

Llama 3.1 405B Instruct Capabilities

chatgenerationtools
Serving providers1
Canonical IDmeta-llama/Llama-3.1-405B-Instruct

Mistral Large 3 Capabilities

agentschatgenerationstructured outputstoolsvision
Serving providers2
Canonical IDmistralai/mistral-large-2512

Primary Evidence

Sources and Freshness

Questions

Llama 3.1 405B Instruct vs Mistral Large 3 FAQs

Is Llama 3.1 405B Instruct or Mistral Large 3 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Llama 3.1 405B Instruct and Mistral Large 3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Llama 3.1 405B Instruct or Mistral Large 3?+

Only Mistral Large 3 has a directly sourced input price: $0.25 per million tokens. Only Mistral Large 3 has a directly sourced output price: $0.75 per million tokens.

Which has a larger context window, Llama 3.1 405B Instruct or Mistral Large 3?+

Mistral Large 3 has the larger sourced context window. Llama 3.1 405B Instruct supports 131K and Mistral Large 3 supports 262K.

Which performs better in benchmarks, Llama 3.1 405B Instruct or Mistral Large 3?+

There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.

Can Llama 3.1 405B Instruct or Mistral Large 3 be self-hosted?+

Both models have the same recorded self-hosting status: supported. Llama 3.1 405B Instruct is open weight; Mistral Large 3 is open weight.

Can Llama 3.1 405B Instruct and Mistral Large 3 understand images?+

Llama 3.1 405B Instruct is not documented with image input; Mistral Large 3 is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Llama 3.1 405B Instruct or Mistral Large 3?+

Neither has a larger sourced maximum output. Llama 3.1 405B Instruct is — and Mistral Large 3 is —.

Do Llama 3.1 405B Instruct and Mistral Large 3 support reasoning and tool use?+

Llama 3.1 405B Instruct: tool calling. Mistral Large 3: tool calling and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Llama 3.1 405B Instruct or Mistral Large 3?+

Llama 3.1 405B Instruct has 1 sourced provider route; Mistral Large 3 has 2, so Mistral Large 3 has broader tracked availability.

Which offers better value, Llama 3.1 405B Instruct or Mistral Large 3?+

There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.

Send Feedback