Kimi K2 Thinking vs Llama 4 Scout
Benchmarks, API pricing and specs, head to head. Data updated 2026-06-10.
Kimi K2 Thinking
67.6Moonshot AI · Nov 2025
A trillion-parameter open reasoning agent that can chain 200–300 tool calls — the open-weights agentic standout of late 2025.
Llama 4 Scout
Meta · Apr 2025
A 10M-token context window — still the largest ever shipped — in a 109B MoE that fits on a single H100.
The verdict
Kimi K2 Thinking wins 2 of the 2 benchmarks these models share, against 0 for Llama 4 Scout. On price the gap is dramatic: Llama 4 Scout works out roughly 3.8x cheaper per blended million tokens. Llama 4 Scout also takes 10M of context versus 262K for Kimi K2 Thinking.
Benchmark head-to-head 2–0
Specs & pricing
| Kimi K2 Thinking | Llama 4 Scout | |
|---|---|---|
| modhub Index | 67.6 | — |
| Input price / 1M | $0.6 | $0.18 |
| Output price / 1M | $2.5 | $0.59 |
| Context window | 262K | 10M |
| Max output | — | — |
| Open weights | yes (Modified MIT) | yes (Llama 4 Community License) |
| Reasoning model | yes | no |
| Multimodal input | text | text, image |
| Knowledge cutoff | Apr 2025 | Aug 2024 |
| Released | Nov 2025 | Apr 2025 |
| Example monthly cost* | $9.75 | $2.68 |
* 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 Thinking or Llama 4 Scout?
- Kimi K2 Thinking wins 2 of the 2 benchmarks these models share, against 0 for Llama 4 Scout. On price the gap is dramatic: Llama 4 Scout works out roughly 3.8x cheaper per blended million tokens. Llama 4 Scout also takes 10M of context versus 262K for Kimi K2 Thinking.
- Which is cheaper, Kimi K2 Thinking or Llama 4 Scout?
- Kimi K2 Thinking costs $0.6/$2.5 per million input/output tokens, while Llama 4 Scout costs $0.18/$0.59. For a typical workload of 10M input and 1.5M output tokens per month, that's $9.75 versus $2.68.
- Which model is better for coding, Kimi K2 Thinking or Llama 4 Scout?
- We don't yet track SWE-bench Verified results for both models; check their individual pages for coding-related scores.
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