--- title: "OpenAI: o1 — price, capability and what beats it · Undominated.ai" canonical: https://undominated.ai/models/openai__o1/ description: "OpenAI: o1: $15.00/M in, $60.00/M out. Independent capability scores, and alternatives compared under recorded workload and capability requirements." --- # OpenAI: o1 — price, capability and what beats it · Undominated.ai > OpenAI: o1: $15.00/M in, $60.00/M out. Independent capability scores, and alternatives compared under recorded workload and capability requirements. [Check base rates for this workload](/check/openai__o1/) [Cheaper alternatives](/alternatives/openai__o1/) [Family](/families/openai-o/) [Compare models](https://undominated.ai/compare/?models=openai%2Fo1) Comparison context Choose up to three standard models in Compare. Requirements and prompt length apply in Compare. This page keeps its stated price basis and workload controls. MODEL PROOF # o1 OpenAI · 17 Dec 2024 Balanced Summarise Chat Code gen Agentic BETTER VALUE OPTION ## A stored alternative has an equal-or-higher measured score and an equal-or-lower price. **$26.25** / 1M tokens Balanced · 3 tokens in per 1 out [Claude Opus 5.5](/models/anthropic__claude-opus-5.5/) · Δ score 145.9 points · 70% lower measured price · $8.00 / 1M tokens [Gemini 3.8 Flash](/models/google__gemini-3.8-flash/) is a further stored option with these losses: 100K → 66K max output Evidence as of 06 Oct 2026 [openrouter/models](https://openrouter.ai/api/v1/models) [LMArena · cc-by-4.0](https://huggingface.co/datasets/lmarena-ai/leaderboard-dataset) Independent LMArena score 1,365.8 ± 4.48 · 27,807 votes Context window 200K Maximum output 100K Input modalities text, image, file Output modalities text Published input price $15.00 / 1M tokens Published output price $60.00 / 1M tokens Pricing kind fixed Inspect [complete billing conditions](#billing-details) and endpoint terms below. Price from OpenAI: the cheapest offer that is serving, at standard delivery and at the maker’s precision or better, at its standard rate. Every price dimension · USD per million tokens | Input | $15.00 /M | | --- | --- | | Output | $60.00 /M | | Cached input | $7.50 /M | | Cache write | Unknown /M | | Cache write 1h | Unknown /M | | Reasoning | Unknown /M | | Web search | $0.01 /call | ### Who sells it The same weights, different shops. Cheapest is not like-for-like when serving precision differs. 1 provider offers · rates, limits and conditions Rates are USD per million tokens. Endpoint terms can differ even when the quoted price and precision match. A listed parameter is a provider declaration, not a task-success test. | Seller | Input | Output | Precision | Uptime (1d) | | --- | --- | --- | --- | --- | | Seller OpenAI openai Endpoint terms Cached input /M $7.50 Context limit 200,000 tokens Output limit 100,000 tokens Tools Listed by endpoint Reasoning Listed by endpoint Promotional discount None reported Uptime · last 30 minutes Unknown | Input $15.00 | Output $60.00 | Precision undeclared | Uptime (1d) 100.00% | ### Independent scores | LMArena Elo | 1365.8 default | | --- | --- | LMArena Elo under CC BY 4.0. Absence of another board is not a score of zero. ### Capability | Context window | 200K | | --- | --- | | Max output | 100K | | Input modes | text, image, file | | Tool use | yes | | Reasoning | optional | | Knowledge cutoff | 2023-10-31 | | Open weights | no | ### Provenance | Price source | [openrouter.ai](https://openrouter.ai/api/v1/models) | | --- | --- | | Fetched | 2026-10-06 | | Quality data | verified | The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason... ## Questions this page answers What does o1 cost? $15.00/M in, $60.00/M out in this catalogue, as of the fetch date on this page. That is the API row, not a subscription. Does o1 have an independent quality score? o1 has an LMArena score in this catalogue. What beats o1? Claude Opus 5.5 has an equal-or-higher measured score and an equal-or-lower price. Does this page use Artificial Analysis scores for o1? No. Artificial Analysis figures are not published here. Quality on this page is LMArena Elo where a score exists; otherwise the row is unrated. MODEL MONUMENT ## Save or share this proof Download proof card · 1200 × 630 Preview and more sharing options OpenAI: o1. Balanced workload. Better value option available. Evidence as of 06 Oct 2026. Copy model link Download square card · 1080 × 1080 Copy landscape image Share landscape card ## Related - Both better and cheaper [Claude Opus 5.5](/models/anthropic__claude-opus-5.5/) - Higher score and cheaper, with a named trade [Gemini 3.8 Flash](/models/google__gemini-3.8-flash/) - Nearby on the capability axis [Qwen3 235B A22B](/models/qwen__qwen3-235b-a22b/) - Same vendor [GPT-5.4 Nano](/models/openai__gpt-5.4-nano/) - OpenAI models [OpenAI](/providers/openai/) - Where this model appears [significance](/significance/) - Nearby on the capability axis [gpt-oss-120b](/models/openai__gpt-oss-120b/) - Same vendor [GPT-5 Mini](/models/openai__gpt-5-mini/) - Where this model appears [cheapest-at](/cheapest-at/) - Nearby on the capability axis [Qwen3 Next 80B A3B Thinking](/models/qwen__qwen3-next-80b-a3b-thinking/) - Same vendor [o4 Mini](/models/openai__o4-mini/) - Where this model appears [subscription vs API](/plans/) ## Badge The verdict as one SVG, for a README or a docs page. It states this model's dominance status at the balanced workload on the LMArena lens, with the date it was computed, and it is rebuilt with the catalogue — so it changes when the verdict changes, including to one you would rather it did not. Markdown Copy [![o1 — Undominated.ai dominance verdict](https://undominated.ai/badge/openai__o1.svg)](https://undominated.ai/models/openai__o1/) HTML Copy o1 — Undominated.ai dominance verdict Direct file: [https://undominated.ai/badge/openai__o1.svg](https://undominated.ai/badge/openai__o1.svg) — a static SVG, written by scripts/build-badges.mjs on every build, so the copy you embed is never older than the last deploy. ## Continue your investigation - [Explore model families](/families/) - [Compare a shortlist](/compare/) - [Check a model](/check/) - [Understand the evidence](/methodology/)