AllocateCogito v2.1 671B vs Meta Llama 3.3 70B Instruct Turbo
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
Meta Llama 3.3 70B Instruct Turbo
Meta Llama 3.3 70B Instruct TurboLabDeep CogitoMeta
AccessNot served on AllocateOpen weights
Context windown/a128K tokens
List price, inputNot served$1.04 / M tokens
List price, outputNot served$1.04 / M tokens
Cached inputn/an/a
LicenseNot listedLlama community
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 Meta Llama 3.3 70B Instruct Turbo for
- Training toward a model you own
Common questions
Which has the bigger context window?
Meta Llama 3.3 70B Instruct Turbo: 131,072 tokens (128K) against an unlisted window for Cogito v2.1 671B.
Can I fine-tune Cogito v2.1 671B or Meta Llama 3.3 70B Instruct Turbo?
Both publish open weights (Cogito v2.1 671B: Not listed; Meta Llama 3.3 70B Instruct Turbo: Llama community), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.
Related comparisons
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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.