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Gemini 2.5 Pro vs Kimi K2 Thinking

google/gemini-2.5-pro · moonshotai/kimi-k2-thinking

As of November 2, 2026, Kimi K2 Thinking is the cheaper API on UberLLM: $0.0059 per million input tokens and $0.0248 per million output, versus $0.3000 / $2.40 for Gemini 2.5 Pro, about 99% less when output is 3 tokens for every input token. These are the best prices on the market right now. Both work with one OpenAI-compatible key and UberLLM adds no fee. Choose Kimi K2 Thinking to cut cost; choose Gemini 2.5 Pro when context size wins. Gemini 2.5 Pro carries the larger context window (1,048,576 vs 262,144 tokens), which can matter for long-document work.

Gemini 2.5 Pro vs Kimi K2 Thinking, side by side

SpecGemini 2.5 ProKimi K2 Thinking
Price · input / 1M$0.3000$0.0059
Price · output / 1M$2.40$0.0248
Context length1,048,576262,144
Max output tokens65,53632,768
Input modalitiestext, imagetext
Output modalitiestexttext
Tools / functionsYesYes
Vision (image input)Yes—
ReasoningYesYes
% off list76% off99% off

Best prices on UberLLM right now. No UberLLM fee on requests; adding credit by card costs 5.5% + $0.50. Updated November 2, 2026. A price more than 70% below list is what buyers were billed, not an error. Why so cheap?

Gemini 2.5 Pro vs Kimi K2 Thinking — FAQ

Is Gemini 2.5 Pro or Kimi K2 Thinking cheaper?

Kimi K2 Thinking is cheaper on a blended token mix, by about 99%. A request costs what its provider charged, UberLLM adds no fee, and every request is listed with its cost in Activity.

What's the price difference between Gemini 2.5 Pro and Kimi K2 Thinking?

Gemini 2.5 Pro: $0.3000 in / $2.40 out per 1M tokens. Kimi K2 Thinking: $0.0059 in / $0.0248 out per 1M tokens. That's roughly a 99% blended difference. Prices are live; UberLLM adds no fee.

Can I use both Gemini 2.5 Pro and Kimi K2 Thinking with one API?

Yes. Both are served through a single OpenAI-compatible endpoint — set the base URL to https://api.uberllm.dev/v1 and your UberLLM key, then switch between them by changing the model id. Anthropic SDKs work via https://api.uberllm.dev/v1/messages.

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