Gemini 2.5 Pro vs Pareto 26.9
google/gemini-2.5-pro · unbiased/pareto-26.9
As of November 5, 2026, Gemini 2.5 Pro is the cheaper API on UberLLM: $0.3000 per million input tokens and $2.40 per million output, versus $2.48 / $7.42 for Pareto 26.9, about 70% 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 Gemini 2.5 Pro to cut cost; choose Pareto 26.9 when its capabilities fit your task better.
Gemini 2.5 Pro vs Pareto 26.9, side by side
| Spec | Gemini 2.5 Pro | Pareto 26.9 |
|---|---|---|
| Price · input / 1M | $0.3000 | $2.48 |
| Price · output / 1M | $2.40 | $7.42 |
| Context length | 1,048,576 | 262,144 |
| Max output tokens | 65,536 | 131,072 |
| Input modalities | text, image | text, image |
| Output modalities | text | text |
| Tools / functions | Yes | Yes |
| Vision (image input) | Yes | Yes |
| Reasoning | Yes | — |
| % off list | 76% off | 1% off |
| First token, median (7 days) | 20.5 s (140 requests) | — |
Best prices on UberLLM right now. No UberLLM fee on requests; adding credit by card costs 5.5% + $0.50. Updated November 5, 2026. A price more than 70% below list is what buyers were billed, not an error. Why so cheap?
Gemini 2.5 Pro vs Pareto 26.9 — FAQ
Is Gemini 2.5 Pro or Pareto 26.9 cheaper?
Gemini 2.5 Pro is cheaper on a blended token mix, by about 70%. 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 Pareto 26.9?
Gemini 2.5 Pro: $0.3000 in / $2.40 out per 1M tokens. Pareto 26.9: $2.48 in / $7.42 out per 1M tokens. That's roughly a 70% blended difference. Prices are live; UberLLM adds no fee.
Can I use both Gemini 2.5 Pro and Pareto 26.9 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.