LLMs TigerLive LLM benchmarks

o1-mini (high): benchmark scores, price and ranking

o1-mini (high) from OpenAI ranks #358 of 743 LLMs on the LLMs Tiger aggregate benchmark score (48.4), based on 2 benchmark results captured up to 2026-10-13.

Organisation
OpenAI
Type
Fast / low-cost (flash) model
Open weights
No
Released
2024-09-12 (source: curated)
Cheapest API price
$1.10 in / $4.40 out per million tokens (via azure, observed 2026-10-13T20:47Z)
Aggregate rank
#358 of 743 (score 48.4)

Across the 2 benchmarks where at least ten models are scored, o1-mini (high) is in the top 10% on 0 and in the top half on 0.

Its cheapest listed input price, $1.10 per million tokens, is lower than that of 33% of the 427 models with a listed price.

o1-mini (high) benchmark results

o1-mini (high) benchmark scores, ranked against all models measured on each benchmark
BenchmarkScoreRankSourceCaptured
OTIS Mock AIME46.9%#109 of 189Epoch AI Benchmarking Hub2026-10-13
GPQA Diamond62.4%#163 of 275Epoch AI Benchmarking Hub2026-10-13

About o1-mini (high)

o1-mini (high) is a smaller, lower-cost model from OpenAI. It was released on 2024-09-12, according to the developer's announcement. The cheapest API listing we track charges $1.10 per million input tokens and $4.40 per million output tokens, through azure. We hold 2 benchmark results for it across 1 area, and none is in the top tenth of its board.

Where o1-mini (high) stands

On our aggregate score, o1-mini (high) is #358 of 743 ranked models, around the middle of the table. Its score is 48.4; the scale is centred on 50, so it sits 1.6 points below the typical model. That beats 52% of the ranked field. Among the 88 ranked OpenAI models it is #46. The next one up is GPT-5.1 (Thinking, High) at 48.5. The next one down is gpt-3.5-turbo-0125 at 48.3.

o1-mini (high), benchmark by benchmark

o1-mini (high) lands below the middle on OTIS Mock AIME: 46.9%, #109 of 189, with 57% of the field scoring higher. Claude Fable 5.1 (max) leads at 100.0%; the closest result above is deepseek-chat at 48.9%. It covers competition maths (AIME 2024-25 style). The board median is 57.8%, so o1-mini (high) is 10.8 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.

o1-mini (high) lands below the middle on GPQA Diamond: 62.4%, #163 of 275, with 59% of the field scoring higher. GPT-6 Astra (max) leads at 95.8%; the closest result above is qwen3-14b at 63.8%. It covers expert-level science questions. The board median is 71.7%, so o1-mini (high) is 9.3 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.

Strengths and weaknesses

Reasoning, maths and science: uneven, ahead of 42% of the field on average across 2 benchmarks. Its best board here is OTIS Mock AIME (#109 of 189) and its weakest is GPQA Diamond (#163 of 275).

Price and value

The median input price across the 427 priced models is $0.500 per million tokens, so o1-mini (high) costs more than the typical listing. Models that score within 1.5 points or better and cost less: Qwen2.5-Coder-7B-Instruct ($0.010, 49.5), DeepSeek V4.1 Flash (high) ($0.010, 48.9), DeepSeek V4 Flash 0731 (max) ($0.016, 53.1). Similar scores cost more on grok-4.20-0309-reasoning ($1.25) and gemini-2.5-pro_32K ($1.25).

Release history

The OpenAI model released before it was o1-mini-2024-09-12 on 2024-09-12, which scores 44.8. The next one was gpt-4o-2024-11-20 on 2024-11-20, at 49.6.

Reading these numbers

The 2 scores on this page come from 1 source: Epoch AI Benchmarking Hub (2). No official leaderboard supplied any of them, so treat them as third-party measurements. The leaderboard also lists 2 other reasoning-effort settings of this model, which redirect here. This page shows the highest. With 2 results the aggregate rank can move a lot when one new score arrives.

o1-mini (high) is also listed at 2 other reasoning-effort settings; this page shows the highest-effort row, which is the one the leaderboard keeps by default.

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Compare it on the live leaderboard → · How the aggregate score works