GPT-6 Astra vs Pareto 26.9
openai/gpt-6-astra · unbiased/pareto-26.9
As of November 5, 2026, GPT-6 Astra is the cheaper API on UberLLM: $0.0685 per million input tokens and $0.3427 per million output, versus $2.48 / $7.42 for Pareto 26.9, about 96% 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 GPT-6 Astra to cut cost; choose Pareto 26.9 when its capabilities fit your task better.
GPT-6 Astra vs Pareto 26.9, side by side
| Spec | GPT-6 Astra | Pareto 26.9 |
|---|---|---|
| Price · input / 1M | $0.0685 | $2.48 |
| Price · output / 1M | $0.3427 | $7.42 |
| Context length | 1,050,000 | 262,144 |
| Max output tokens | 128,000 | 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 | 99.3% off | 1% off |
| First token, median (7 days) | 3.9 s (111 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?
GPT-6 Astra vs Pareto 26.9 — FAQ
Is GPT-6 Astra or Pareto 26.9 cheaper?
GPT-6 Astra is cheaper on a blended token mix, by about 96%. 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 GPT-6 Astra and Pareto 26.9?
GPT-6 Astra: $0.0685 in / $0.3427 out per 1M tokens. Pareto 26.9: $2.48 in / $7.42 out per 1M tokens. That's roughly a 96% blended difference. Prices are live; UberLLM adds no fee.
Can I use both GPT-6 Astra 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.