command-a-plus-05-2026-bf16 vs Mistral Large 3

Benchmark Performance

Available Benchmarks

No Protocol-Matched Benchmark Yet.Results appear here only when both models share the same benchmark version, metric, evaluation protocol, and evidence class.
FieldAt a Glance
Cohere · activecommand-a-plus-05-2026-bf16Verified Aug 28, 2026
Mistral AI · activeMistral Large 3Verified Aug 29, 2026

Technical Differences

Side-by-Side Facts

Indexable
Fieldcommand-a-plus-05-2026-bf16Mistral Large 3
DeveloperCohereMistral AI
FamilyCommand A Plus 05Mistral Large 3
Modelcommand-a-plus-05-2026-bf16Mistral Large 3
Versioncommand-a-plus-05-2026-bf16Mistral Large 3
Lifecycleactiveactive
ReleasedUnknown2025-12-02
Knowledge cutoffUnknownUnknown
Input modalitiesText, ImageText, Image, Document
Output modalitiesTextText
Context window200,000262,144
Total parameters218,750,277,872675,000,000,000
Active parameters25,000,000,00041,000,000,000
Licenseapache-2.0Apache-2.0
Open weightsYesYes
API availableUnknownYes
Self-hostableYesYes
Provider accessUnknownMistral AI (Standard), Openrouter (Standard)
Capabilitieschat, generation, toolsagents, chat, generation, structured_outputs, tools, vision

14 comparable fields · 10 material differences · Pair passes the primary-source comparison gate

command-a-plus-05-2026-bf16 Capabilities

chatgenerationtools
Input price
Output price
Serving providers0
Canonical IDCohereLabs/command-a-plus-05-2026-bf16

Mistral Large 3 Capabilities

agentschatgenerationstructured outputstoolsvision
Input price$0.50
Output price$1.50
Serving providers2
Canonical IDmistralai/mistral-large-2512

Internal Comparison Graph

Related Comparisons

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Primary Evidence

Sources and Freshness

Questions

command-a-plus-05-2026-bf16 vs Mistral Large 3 FAQs

Is command-a-plus-05-2026-bf16 or Mistral Large 3 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both command-a-plus-05-2026-bf16 and Mistral Large 3, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, command-a-plus-05-2026-bf16 or Mistral Large 3?+

Only Mistral Large 3 has a directly sourced input price: $0.50 per million tokens. Only Mistral Large 3 has a directly sourced output price: $1.50 per million tokens.

Which has a larger context window, command-a-plus-05-2026-bf16 or Mistral Large 3?+

Mistral Large 3 has the larger sourced context window. command-a-plus-05-2026-bf16 supports 200,000 and Mistral Large 3 supports 262,144.

Which performs better in benchmarks, command-a-plus-05-2026-bf16 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 command-a-plus-05-2026-bf16 or Mistral Large 3 be self-hosted?+

Both models have the same recorded self-hosting status: supported. command-a-plus-05-2026-bf16 is open weight; Mistral Large 3 is open weight.

Can command-a-plus-05-2026-bf16 and Mistral Large 3 understand images?+

command-a-plus-05-2026-bf16 is 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, command-a-plus-05-2026-bf16 or Mistral Large 3?+

Neither has a larger sourced maximum output. command-a-plus-05-2026-bf16 is 65,536 and Mistral Large 3 is —.

Do command-a-plus-05-2026-bf16 and Mistral Large 3 support reasoning and tool use?+

command-a-plus-05-2026-bf16: tool calling and image input. Mistral Large 3: tool calling and image input. Feature support does not establish relative quality.

Which is available from more inference providers, command-a-plus-05-2026-bf16 or Mistral Large 3?+

command-a-plus-05-2026-bf16 has 0 sourced provider routes; Mistral Large 3 has 2, so Mistral Large 3 has broader tracked availability.

Which offers better value, command-a-plus-05-2026-bf16 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.

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