Command A vs Kimi K2.5

At a Glance

Compare
Command ACohere
Kimi K2.5Moonshot AI
Pricing and Limits
Input priceFrom · USD / 1M tokens$2.50Cohere · Aug 29, 2026$0.45Deepinfra · Aug 29, 2026
Output priceFrom · USD / 1M tokens$10.00Cohere · Aug 29, 2026$2.25Deepinfra · Aug 29, 2026
Context windowMaximum documented tokens256K262K
Model facts checkedAug 29, 2026View model evidence →Aug 28, 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 →
BenchmarkCommand AKimi-K2.5
LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader1,330.8792% of row best · rating · command-a-03-2025; 95% CI [1327.41159924, 1334.32729730]; votes 55449; rank 2111,445.64100% of row best · rating · kimi-k2.5-thinking; 95% CI [1442.30343195, 1448.97544647]; votes 70513; rank 53
Overall ResultCounted from the protocol-matched rows above0 benchmark winsNo overall winner1 benchmark winNo overall winner

Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.

Side-by-Side Facts

FieldCommand AKimi-K2.5
DeveloperCohereMoonshot AI
FamilyCommand AKimi K2 5
ModelCommand AKimi-K2.5
VersionCommand AKimi-K2.5
Lifecycleactiveactive
ReleasedUnknown2026-01-27
Knowledge cutoff2024-06-01Unknown
Input modalitiesTextText, Image
Output modalitiesTextText
Context window256K262K
Total parameters111B1T
Active parametersUnknown32B
LicenseUnknownother
Open weightsNoYes
API availableYesYes
Self-hostableNoYes
Provider accessCohere (Standard)Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard)
Capabilitiesagents, chat, citations, multilingual, rag, structured_outputs, toolschat, generation, reasoning, tools

Command A Capabilities

agentschatcitationsmultilingualragstructured outputstools
Serving providers1
Canonical IDcoherelabs/command-a-03-2025

Kimi K2.5 Capabilities

chatgenerationreasoningtools
Serving providers3
Canonical IDmoonshotai/Kimi-K2.5

Primary Evidence

Sources and Freshness

Questions

Command A vs Kimi K2.5 FAQs

Is Command A or Kimi K2.5 better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Command A and Kimi K2.5, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Command A or Kimi K2.5?+

Command A is $2.50 and Kimi K2.5 is $0.45 per million tokens, so Kimi K2.5 is cheaper on this metric. Command A is $10.00 and Kimi K2.5 is $2.25 per million tokens, so Kimi K2.5 is cheaper on this metric.

Which has a larger context window, Command A or Kimi K2.5?+

Kimi K2.5 has the larger sourced context window. Command A supports 256K and Kimi K2.5 supports 262K.

Which performs better in benchmarks, Command A or Kimi K2.5?+

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

Can Command A or Kimi K2.5 be self-hosted?+

Kimi K2.5 is the only model in this pair currently marked as self-hostable. Command A is not marked open weight; Kimi K2.5 is open weight.

Can Command A and Kimi K2.5 understand images?+

Command A is not documented with image input; Kimi K2.5 is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Command A or Kimi K2.5?+

Neither has a larger sourced maximum output. Command A is 8K and Kimi K2.5 is —.

Do Command A and Kimi K2.5 support reasoning and tool use?+

Command A: tool calling. Kimi K2.5: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Command A or Kimi K2.5?+

Command A has 1 sourced provider route; Kimi K2.5 has 3, so Kimi K2.5 has broader tracked availability.

Which offers better value, Command A or Kimi K2.5?+

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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