# Cogito 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.

## Specifications

| | Cogito v2.1 671B | Meta Llama 3.3 70B Instruct Turbo |
| --- | --- | --- |
| Lab | Deep Cogito | Meta |
| Access | Not served on Allocate | Open weights |
| Context window | n/a | 128K tokens |
| List price, input | Not served | $1.04 / M tokens |
| List price, output | Not served | $1.04 / M tokens |
| Cached input | n/a | n/a |
| License | Not listed | Llama community |
| Fine-tunable | Yes | Yes |

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.

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[HTML page](https://allocate.network/compare/deepcogito-cogito-v2-1-671b-vs-meta-llama-3-3-70b-instruct-turbo) · [Cogito v2.1 671B](https://allocate.network/models/deepcogito-cogito-v2-1-671b.md) · [Meta Llama 3.3 70B Instruct Turbo](https://allocate.network/models/meta-llama-3-3-70b-instruct-turbo.md) · [Machine-readable catalog](https://allocate.network/catalog.json)