Trinity Large Thinking vs Pareto 26.9
arcee-ai/trinity-large-thinking · unbiased/pareto-26.9
As of November 6, 2026, Trinity Large Thinking is the cheaper API on UberLLM: $0.1975 per million input tokens and $0.6320 per million output, versus $2.48 / $7.42 for Pareto 26.9, about 92% 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 Trinity Large Thinking to cut cost; choose Pareto 26.9 when context size wins. Pareto 26.9 carries the larger context window (262,144 vs 256,000 tokens), which can matter for long-document work.
Trinity Large Thinking vs Pareto 26.9, side by side
| Spec | Trinity Large Thinking | Pareto 26.9 |
|---|---|---|
| Price · input / 1M | $0.1975 | $2.48 |
| Price · output / 1M | $0.6320 | $7.42 |
| Context length | 256,000 | 262,144 |
| Max output tokens | 32,768 | 131,072 |
| Input modalities | text | text, image |
| Output modalities | text | text |
| Tools / functions | Yes | Yes |
| Vision (image input) | — | Yes |
| Reasoning | Yes | — |
| % off list | 34.3% off | 1% off |
Best prices on UberLLM right now. No UberLLM fee on requests; adding credit by card costs 5.5% + $0.50. Updated November 6, 2026.
Trinity Large Thinking vs Pareto 26.9 — FAQ
Is Trinity Large Thinking or Pareto 26.9 cheaper?
Trinity Large Thinking is cheaper on a blended token mix, by about 92%. 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 Trinity Large Thinking and Pareto 26.9?
Trinity Large Thinking: $0.1975 in / $0.6320 out per 1M tokens. Pareto 26.9: $2.48 in / $7.42 out per 1M tokens. That's roughly a 92% blended difference. Prices are live; UberLLM adds no fee.
Can I use both Trinity Large Thinking 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.