Kimi K2 vs Llama 4 405B for debugging: which is better in 2026?
A head-to-head look at Kimi K2 and Llama 4 405B for debugging. Benchmarks via artificialanalysis.ai, pricing as of May 2026. Compare AI models like these inside Admix.
Quick verdict
For debugging in May 2026, Llama 4 405B edges out Kimi K2 on the codingIndex metric. Best fully open-weights model.
Side-by-side specs
| Spec | Kimi | Llama |
|---|---|---|
| Intelligence index | 70.4 | 71.5 |
| Coding index | 68.9 | 69.0 |
| Context window | 2M tokens | 256K tokens |
| Speed (tok/s) | 110 | 95 |
| Input $/M | $0.60 | $0.90 |
| Output $/M | $2.50 | $2.70 |
| Released | Dec 11, 2025 | Nov 5, 2025 |
How they handle debugging
Kimi K2: Huge context window at low price. The main caveat is coding lags western frontier models.
Llama 4 405B: Best fully open-weights model. The main caveat is trails closed flagships on coding.
Cost per 1,000 queries
Assuming 1,500 input and 800 output tokens per query:
- Kimi K2: $2.90 per 1,000 queries
- Llama 4 405B: $3.51 per 1,000 queries
Verdict by sub-task
- Best raw quality on debugging:
- Best price: Kimi K2
- Longest context: Kimi K2
- Fastest: Kimi K2
FAQ
Is Kimi K2 better than Llama 4 405B for debugging?
On May 2026 benchmarks (artificialanalysis.ai), Llama 4 405B ranks higher than Kimi K2 for debugging on the codingIndex metric. The gap is small enough that the choice often comes down to price, context length, and tone.
Which is cheaper, Kimi K2 or Llama 4 405B?
Kimi K2 costs $0.60 input and $2.50 output per million tokens. Llama 4 405B costs $0.90 input and $2.70 output per million tokens.
Can I use both Kimi and Llama in one app?
Yes. Admix is a multi model AI chat aggregator that lets you run Kimi K2 and Llama 4 405B side by side under one subscription.
Sources
Benchmarks from artificialanalysis.ai (May 2026).
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