Codestral 22B v0.1 vs Kimi K2.7 Code

At a Glance

Compare
Kimi K2.7 CodeMoonshot AI
Intelligence, Cost, and Efficiency
CostLower is better · Published-token output estimateUnrankedNot in the 44-model eligible cohort#9 of 44$0.042 per LiveBench case
Pricing and Limits
Input priceFrom · USD / 1M tokensNot reported$0.68Deepinfra · Sep 22, 2026
Output priceFrom · USD / 1M tokensNot reported$3.21Openrouter · Sep 22, 2026
Context windowMaximum documented tokens33K262K
Model facts checkedAug 28, 2026View model evidence →Sep 3, 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

FieldCodestral-22B-v0.1Kimi K2.7 Code
DeveloperMistral AIMoonshot AI
FamilyCodestral 22b V0 1Kimi K2 7
ModelCodestral-22B-v0.1Kimi K2.7 Code
VersionCodestral-22B-v0.1Kimi K2.7 Code
Lifecycleactiveactive
ReleasedUnknown2026-06-11
Knowledge cutoffUnknownUnknown
Input modalitiesTextText, Image, Video
Output modalitiesTextText
Context window33K262K
Total parameters22.2B1T
Active parametersUnknown32B
Licenseothermodified-mit
Open weightsYesYes
API availableUnknownYes
Self-hostableYesYes
Provider accessUnknownDeepinfra (Standard), Fireworks Ai (Standard), Openrouter (Standard), Together Ai (Standard)
Capabilitiesgenerationagents, chat, coding, reasoning, tools, vision

Codestral 22B v0.1 Capabilities

generation
Serving providers0
Canonical IDmistralai/Codestral-22B-v0.1

Kimi K2.7 Code Capabilities

agentschatcodingreasoningtoolsvision
Serving providers4
Canonical IDmoonshotai/Kimi-K2.7-Code

Primary Evidence

Sources and Freshness

Questions

Codestral 22B v0.1 vs Kimi K2.7 Code FAQs

Is Codestral 22B v0.1 or Kimi K2.7 Code better for coding?+

This comparison does not currently contain a protocol-matched coding benchmark for both Codestral 22B v0.1 and Kimi K2.7 Code, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.

Which is cheaper, Codestral 22B v0.1 or Kimi K2.7 Code?+

Only Kimi K2.7 Code has a directly sourced input price: $0.68 per million tokens. Only Kimi K2.7 Code has a directly sourced output price: $3.21 per million tokens.

Which has a larger context window, Codestral 22B v0.1 or Kimi K2.7 Code?+

Kimi K2.7 Code has the larger sourced context window. Codestral 22B v0.1 supports 33K and Kimi K2.7 Code supports 262K.

Which performs better in benchmarks, Codestral 22B v0.1 or Kimi K2.7 Code?+

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

Can Codestral 22B v0.1 or Kimi K2.7 Code be self-hosted?+

Both models have the same recorded self-hosting status: supported. Codestral 22B v0.1 is open weight; Kimi K2.7 Code is open weight.

Can Codestral 22B v0.1 and Kimi K2.7 Code understand images?+

Codestral 22B v0.1 is not documented with image input; Kimi K2.7 Code is documented with image input. This reflects supported input modalities, not vision quality.

Which can generate longer answers, Codestral 22B v0.1 or Kimi K2.7 Code?+

Neither has a larger sourced maximum output. Codestral 22B v0.1 is — and Kimi K2.7 Code is —.

Do Codestral 22B v0.1 and Kimi K2.7 Code support reasoning and tool use?+

Codestral 22B v0.1: none of these features are definitively sourced. Kimi K2.7 Code: reasoning, tool calling, and image input. Feature support does not establish relative quality.

Which is available from more inference providers, Codestral 22B v0.1 or Kimi K2.7 Code?+

Codestral 22B v0.1 has 0 sourced provider routes; Kimi K2.7 Code has 4, so Kimi K2.7 Code has broader tracked availability.

Which offers better value, Codestral 22B v0.1 or Kimi K2.7 Code?+

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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