Kimi K2 vs Llama 4 405B for summarizing pdfs: which is better in 2026?
A head-to-head look at Kimi K2 and Llama 4 405B for summarizing pdfs. Benchmarks via artificialanalysis.ai, pricing as of May 2026. Compare AI models like these inside Admix.
Quick verdict
For summarizing pdfs in May 2026, Kimi K2 edges out Llama 4 405B on the contextWindow metric. Matches Gemini context at a much lower price.
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 summarizing pdfs
Kimi K2: Matches Gemini context at a much lower price.
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 summarizing pdfs:
- Best price: Kimi K2
- Longest context: Kimi K2
- Fastest: Kimi K2
FAQ
Is Kimi K2 better than Llama 4 405B for summarizing pdfs?
On May 2026 benchmarks (artificialanalysis.ai), Kimi K2 ranks higher than Llama 4 405B for summarizing pdfs on the contextWindow 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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