Which is cheaper, Kimi K2 0905 or Mistral Large 2?
As of August 25, 2026, Kimi K2 0905 is 61% cheaper on blended LLM API pricing. Kimi K2 0905 costs $0.60 per million input tokens and $2.50 per million output tokens ($3.10 blended 1M-in + 1M-out). Mistral Large 2 costs $2.00 / $6.00 per million tokens ($8.00 blended). Sources: https://platform.kimi.com/docs/pricing/chat and https://docs.mistral.ai/platform/pricing/. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does Kimi K2 0905 vs Mistral Large 2 cost per million tokens?
Kimi K2 0905 Moonshot AI API pricing is $0.60 input and $2.50 output per million tokens via Moonshot AI. Mistral Large 2 Mistral API pricing is $2.00 input and $6.00 output per million tokens via Mistral AI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, Kimi K2 0905 or Mistral Large 2?
Kimi K2 0905 leads on HumanEval: Kimi K2 0905 at 94.5% vs Mistral Large 2 at 92%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
What is the context window for Kimi K2 0905 vs Mistral Large 2?
Kimi K2 0905 supports a 262K token context window, while Mistral Large 2 supports 128K tokens. Kimi K2 0905 offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
Which model performs better on benchmarks, Kimi K2 0905 or Mistral Large 2?
Kimi K2 0905 leads on 2 of 2 shared benchmarks versus Mistral Large 2's 0 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Is Kimi K2 0905 or Mistral Large 2 better for production use?
Both Kimi K2 0905 and Mistral Large 2 are production API models. For cost-sensitive production traffic, Kimi K2 0905 has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Can I switch between Kimi K2 0905 and Mistral Large 2 in my app?
Yes. Call Kimi K2 0905 through Moonshot AI and Mistral Large 2 through Mistral AI with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
How accurate is this Kimi K2 0905 vs Mistral Large 2 pricing data?
List rates are the latest published Moonshot AI API pricing and Mistral API pricing, quoted per million tokens. Official rate sheets: https://platform.kimi.com/docs/pricing/chat and https://docs.mistral.ai/platform/pricing/. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
What is the output token limit for Kimi K2 0905 and Mistral Large 2?
Kimi K2 0905 supports up to 262K output tokens per request, while Mistral Large 2 supports up to 128K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Which model has better throughput, Kimi K2 0905 or Mistral Large 2?
Mistral Large 2 has a measured throughput of approximately 42 tokens/second. Throughput data for Kimi K2 0905 is not yet available. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
How do I switch the models in this Kimi K2 0905 vs Mistral Large 2 comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Kimi K2 0905 or Mistral Large 2 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
