Mistral Large 3 vs Mistral Large 4

At a Glance

Compare
Mistral Large 3Mistral AI
Mistral Large 4Mistral AI
Intelligence, Cost, and Efficiency
IntelligenceHigher is better · MM Intelligence v4.4#28 of 5743.0 score · 1/3 sources · single-source provisional · missing LiveBench, ARC-AGI-2 · full-core range 14.3–81.0#21 of 5754.6 score · 1/3 sources · single-source provisional · missing ARC-AGI-2, LMArena Text · full-core range 18.2–84.9
CostLower is better · Published-token output estimateUnrankedNot in the 27-model eligible cohort#9 of 27$0.054 per LiveBench case
EfficiencyHigher is better · MM Efficiency v1.9UnrankedNot in the 27-model eligible cohort#13 of 2749.9 score · 1/3 sources · single-source provisional · missing ARC-AGI-2, LMArena Text · full-core range 31.7–65.0
Pricing and Limits
Input priceFrom · USD / 1M tokens$0.25Openrouter ↗ · Oct 19, 2026$0.68Mistral AI ↗ · Oct 6, 2026
Output priceFrom · USD / 1M tokens$0.75Openrouter ↗ · Oct 19, 2026$2.09Mistral AI ↗ · Oct 6, 2026
Context windowMaximum documented tokens262K1,000K
Model facts checkedAug 29, 2026View model evidence →Oct 8, 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 →

Decision Notes

Workload evidence
There is no protocol-matched publisher benchmark row for Mistral Large 3 and Mistral Large 4. Specifications and prices cannot establish which performs better on your workload. View evidence →
Reference request
For 1,000 uncached input and 1,000 output tokens on Mistral AI (openai; Standard; regions: not specified; quantization: not specified), Mistral Large 3 is USD 0.002000 and Mistral Large 4 is USD 0.002770. Rates observed 2026-08-29 to 2026-10-06. Reference-request estimate v1: (1,000 × input rate + 1,000 × output rate) / 1,000,000. Excludes cache, tool calls, retries, other fees and taxes; this is not measured task cost. View evidence →Published price source 1 ↗ Published price source 2 ↗
Deployment requirements
Mistral Large 3 is documented as self-hostable; Mistral Large 4 is of unknown self-hosting status. Recorded licenses: Mistral Large 3, Apache-2.0; Mistral Large 4, not reported. If you need local deployment, verify the license and hardware requirements; an unknown field does not establish permission or lack of support. View evidence →

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

FieldMistral Large 3Mistral Large 4
DeveloperMistral AIMistral AI
FamilyMistral Large 3Mistral Large 4
ModelMistral Large 3Mistral Large 4
VersionMistral Large 3Mistral Large 4
Lifecycleactivepreview
Released2025-12-022026-10-06
Knowledge cutoffUnknownUnknown
Input modalitiesText, Image, DocumentText, Image, Document
Output modalitiesTextText
Context window262K1,000K
Total parameters675B1.05T
Active parameters41B52B
LicenseApache-2.0Unknown
Open weightsYesUnknown
API availableYesYes
Self-hostableYesUnknown
Provider accessMistral AI (Standard), Openrouter (Standard)Mistral AI (Standard)
Capabilitiesagents, chat, generation, structured_outputs, tools, visionagents, chat, generation, structured_outputs, tools, vision
Publisher versionUnknownv26.10
Vision encoder parametersUnknown1600000000 parameters
WeightsUnknownMistral announced a later October release; no download or license is linked yet

Mistral Large 3 Capabilities

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

Mistral Large 4 Capabilities

agentschatgenerationstructured outputstoolsvision
Serving providers1
Canonical IDmistralai/mistral-large-4

Primary Evidence

Sources and Freshness

Questions

Mistral Large 3 vs Mistral Large 4 FAQs

Is Mistral Large 3 or Mistral Large 4 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Mistral Large 3 and Mistral Large 4, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Mistral Large 3 or Mistral Large 4?+

Mistral Large 3 is $0.25 and Mistral Large 4 is $0.68 per million tokens, so Mistral Large 3 is cheaper on this metric. Mistral Large 3 is $0.75 and Mistral Large 4 is $2.09 per million tokens, so Mistral Large 3 is cheaper on this metric.

Which has a larger context window, Mistral Large 3 or Mistral Large 4?+

Mistral Large 4 has the larger sourced context window. Mistral Large 3 supports 262,144 tokens and Mistral Large 4 supports 1,000,000 tokens.

Which performs better in benchmarks, Mistral Large 3 or Mistral Large 4?+

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

Can Mistral Large 3 or Mistral Large 4 be self-hosted?+

Mistral Large 3's sourced self-hosting status is supported; Mistral Large 4's is unknown. An unknown status does not establish support or lack of support. Mistral Large 3 is open weight; Mistral Large 4 is of unknown open-weight status.

Can Mistral Large 3 and Mistral Large 4 understand images?+

Mistral Large 3 is documented with image input; Mistral Large 4 is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Mistral Large 3 or Mistral Large 4?+

Neither model has a sourced maximum output in this comparison, so a larger limit cannot be determined.

Do Mistral Large 3 and Mistral Large 4 support reasoning and tool use?+

Mistral Large 3: tool calling and image input. Mistral Large 4: tool calling and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Mistral Large 3 or Mistral Large 4?+

Mistral Large 3 has 2 sourced provider routes; Mistral Large 4 has 1, so Mistral Large 3 has broader tracked availability.

Which offers better value, Mistral Large 3 or Mistral Large 4?+

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.

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