# Kimi K2.5 vs Llama 4 70B

Llama 4 70B 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

| | Kimi K2.5 | Llama 4 70B |
| --- | --- | --- |
| Lab | Togethercomputer | Meta |
| Access | Open weights | Not served on Allocate |
| Context window | 256K tokens | n/a |
| List price, input | $0.50 / M tokens | Not served |
| List price, output | $2.80 / M tokens | Not served |
| Cached input | n/a | n/a |
| License | Not listed | Not listed |
| Fine-tunable | Yes | Yes |

Specifications and provider list prices from the Allocate catalog, checked 2026-07-21.

## Choose Kimi K2.5 for

- Whole-document reasoning
- Long-context retrieval
- Open-weight fine-tuning

## Choose Llama 4 70B for

- First private fine-tunes
- Classification and extraction
- On-boundary deployments

## Common questions

### Which has the bigger context window?

Kimi K2.5: 262,144 tokens (256K) against an unlisted window for Llama 4 70B.

### Can I fine-tune Kimi K2.5 or Llama 4 70B?

Both publish open weights (Kimi K2.5: Not listed; Llama 4 70B: Not listed), so both can be fine-tuned. On Allocate the trained weights stay inside your boundary and belong to you.

---

[HTML page](https://allocate.network/compare/kimi-k2-5-vs-llama-4-70b) · [Kimi K2.5](https://allocate.network/models/kimi-k2-5.md) · [Llama 4 70B](https://allocate.network/models/llama-4-70b.md) · [Machine-readable catalog](https://allocate.network/catalog.json)