AllocateCogito v2.1 671B vs Kimi K2.7 Code
Cogito v2.1 671B is not currently in the Allocate serving catalog, so this page lists no prices for it: every price on this site comes from the live catalog.
C Cogito v2.1 671B
Kimi K2.7 Code
Kimi K2.7 CodeLabDeep CogitoMoonshot AI
AccessNot served on AllocateOpen weights
Context windown/a256K tokens
List price, inputNot served$0.95 / M tokens
List price, outputNot served$4 / M tokens
Cached inputn/a$0.19 / M tokens
LicenseNot listedNot listed
Fine-tunableYesYes
Specifications and provider list prices from the Allocate catalog, checked 2026-09-12.
Choose Cogito v2.1 671B for
- Long reasoning chains
- Open-weight agents
- Self-hosted reasoning
Choose Kimi K2.7 Code for
- Published cached-input pricing ($0.19 per M tokens)
Common questions
Which has the bigger context window?
Kimi K2.7 Code: 262,144 tokens (256K) against an unlisted window for Cogito v2.1 671B.
Can I fine-tune Cogito v2.1 671B or Kimi K2.7 Code?
Both publish open weights (Cogito v2.1 671B: Not listed; Kimi K2.7 Code: Not listed), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.
Related comparisons
Cogito v2.1 671B vs GLM 4.7 FP8Kimi K2.7 Code vs GLM 4.7 FP8Cogito v2.1 671B vs Deepseek V3.1 NVFP4Kimi K2.7 Code vs Deepseek V3.1 NVFP4Cogito v2.1 671B vs Meta Llama 3.3 70B Instruct TurboKimi K2.7 Code vs Meta Llama 3.3 70B Instruct Turbo
Run the numbers on your workload
Or do not choose. On Allocate a route name is the contract: point yours at one model today, swap to the other tomorrow, and compare them on your live traffic with per-token metering.