Which is cheaper, Gemini 3.1 Pro or Kimi K3?
As of August 20, 2026, Gemini 3.1 Pro is 3% cheaper on blended LLM API pricing. Gemini 3.1 Pro costs $2.50 per million input tokens and $15.00 per million output tokens ($17.50 blended 1M-in + 1M-out). Kimi K3 costs $3.00 / $15.00 per million tokens ($18.00 blended). Sources: https://ai.google.dev/gemini-api/docs/pricing and https://platform.kimi.com/docs/pricing/chat. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does Gemini 3.1 Pro vs Kimi K3 cost per million tokens?
Gemini 3.1 Pro Gemini API pricing is $2.50 input and $15.00 output per million tokens via Google. Kimi K3 Moonshot AI API pricing is $3.00 input and $15.00 output per million tokens via Moonshot AI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, Gemini 3.1 Pro or Kimi K3?
Kimi K3 leads on SWE-bench Verified: Gemini 3.1 Pro at 80.6% vs Kimi K3 at 93.4%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.
What is the context window for Gemini 3.1 Pro vs Kimi K3?
Gemini 3.1 Pro supports a 1M token context window, while Kimi K3 supports 1M tokens. Both models have the same context window size. 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, Gemini 3.1 Pro or Kimi K3?
Kimi K3 leads on 24 of 36 shared benchmarks versus Gemini 3.1 Pro's 12 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 Gemini 3.1 Pro or Kimi K3 better for production use?
Both Gemini 3.1 Pro and Kimi K3 are production API models. For cost-sensitive production traffic, Gemini 3.1 Pro 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 Gemini 3.1 Pro and Kimi K3 in my app?
Yes. Call Gemini 3.1 Pro through Google and Kimi K3 through Moonshot 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 Gemini 3.1 Pro vs Kimi K3 pricing data?
List rates are the latest published Gemini API pricing and Moonshot AI API pricing, quoted per million tokens. Official rate sheets: https://ai.google.dev/gemini-api/docs/pricing and https://platform.kimi.com/docs/pricing/chat. 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 Gemini 3.1 Pro and Kimi K3?
Gemini 3.1 Pro supports up to 66K output tokens per request, while Kimi K3 supports up to 1M 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, Gemini 3.1 Pro or Kimi K3?
Gemini 3.1 Pro runs at approximately 90 tokens/second while Kimi K3 runs at 8.253358168863906 tokens/second. Gemini 3.1 Pro is faster in raw throughput. 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 Gemini 3.1 Pro vs Kimi K3 comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Gemini 3.1 Pro or Kimi K3 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
