Kimi K2.6 vs Llama 4 Maverick
Benchmarks, API pricing and specs, head to head. Data updated 2026-06-10.
Moonshot AI · Apr 2026
Moonshot's multimodal flagship that ties GPT-5.5 on several coding evaluations at a fraction of the price, with open weights.
Meta · Apr 2025
Meta's natively multimodal 400B MoE — the largest openly downloadable US-made model, served cheaply across many hosts.
The verdict
These two models don't yet share verified results on the benchmarks we track, so judge them on specs, pricing and intended use. On price the gap is dramatic: Llama 4 Maverick works out roughly 4.1x cheaper per blended million tokens. Llama 4 Maverick also takes 1M of context versus 262K for Kimi K2.6.
Specs & pricing
| Kimi K2.6 | Llama 4 Maverick | |
|---|---|---|
| modhub Index | — | — |
| Input price / 1M | $0.95 | $0.27 |
| Output price / 1M | $4 | $0.85 |
| Context window | 262K | 1M |
| Max output | 262K | — |
| Open weights | yes (Modified MIT) | yes (Llama 4 Community License) |
| Reasoning model | yes | no |
| Multimodal input | text, image | text, image |
| Knowledge cutoff | Feb 2026 | Aug 2024 |
| Released | Apr 2026 | Apr 2025 |
| Example monthly cost* | $15.50 | $3.98 |
* 10M input + 1.5M output tokens per month at list prices, no caching. Green = better value on that row.
Frequently asked questions
- Which is better, Kimi K2.6 or Llama 4 Maverick?
- These two models don't yet share verified results on the benchmarks we track, so judge them on specs, pricing and intended use. On price the gap is dramatic: Llama 4 Maverick works out roughly 4.1x cheaper per blended million tokens. Llama 4 Maverick also takes 1M of context versus 262K for Kimi K2.6.
- Which is cheaper, Kimi K2.6 or Llama 4 Maverick?
- Kimi K2.6 costs $0.95/$4 per million input/output tokens, while Llama 4 Maverick costs $0.27/$0.85. For a typical workload of 10M input and 1.5M output tokens per month, that's $15.50 versus $3.98.
- Which model is better for coding, Kimi K2.6 or Llama 4 Maverick?
- We don't yet track SWE-bench Verified results for both models; check their individual pages for coding-related scores.