o3-mini-2025-01-31 (low): benchmark scores, price and ranking
o3-mini-2025-01-31 (low) from OpenAI ranks #547 of 743 LLMs on the LLMs Tiger aggregate benchmark score (46.0), based on 5 benchmark results captured up to 2026-10-13.
- Organisation
- OpenAI
- Type
- Fast / low-cost (flash) model
- Open weights
- No
- Released
- 2025-01-31 (source: name)
- Cheapest API price
- $1.10 in / $4.40 out per million tokens (via azure, observed 2026-10-13T20:47Z)
- Aggregate rank
- #547 of 743 (score 46.0)
Relative to other models, o3-mini-2025-01-31 (low) is strongest on GPQA Diamond (#147 of 275) and weakest on GSO-Bench (#18 of 19).
Across the 5 benchmarks where at least ten models are scored, o3-mini-2025-01-31 (low) 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.
o3-mini-2025-01-31 (low) benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| GPQA Diamond | 68.2% | #147 of 275 | Epoch AI Benchmarking Hub | 2026-10-13 |
| OTIS Mock AIME | 44.4% | #111 of 189 | Epoch AI Benchmarking Hub | 2026-10-13 |
| Chess Puzzles | 6.0% | #77 of 122 | Epoch AI Benchmarking Hub | 2026-10-13 |
| FrontierMath T1-3 | 3.9% | #64 of 68 | Epoch AI Benchmarking Hub | 2026-10-13 |
| GSO-Bench | 1.3% | #18 of 19 | Epoch AI Benchmarking Hub | 2026-10-13 |
About o3-mini-2025-01-31 (low)
o3-mini-2025-01-31 (low) is a smaller, lower-cost model from OpenAI. It was released on 2025-01-31, according to the model's own name. The cheapest API listing we track charges $1.10 per million input tokens and $4.40 per million output tokens, through azure. We hold 5 benchmark results for it across 3 areas, and none is in the top tenth of its board.
Where o3-mini-2025-01-31 (low) stands
On our aggregate score, o3-mini-2025-01-31 (low) is #547 of 743 ranked models, in the lower half. Its score is 46.0; the scale is centred on 50, so it sits 4.0 points below the typical model. That beats 26% of the ranked field. Among the 88 ranked OpenAI models it is #70. The next one up is GPT-5.4 mini (xhigh) at 46.3. The next one down is gpt-4-turbo at 45.4.
o3-mini-2025-01-31 (low), benchmark by benchmark
o3-mini-2025-01-31 (low) lands below the middle on GPQA Diamond: 68.2%, #147 of 275, with 53% of the field scoring higher. GPT-6 Astra (max) leads at 95.8%; the closest result above is GPT-4.5 Preview (Feb 2025) at 68.7%. It covers expert-level science questions. The board median is 71.7%, so o3-mini-2025-01-31 (low) is 3.5 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
o3-mini-2025-01-31 (low) lands below the middle on OTIS Mock AIME: 44.4%, #111 of 189, with 58% of the field scoring higher. Claude Fable 5.1 (max) leads at 100.0%; the closest result above is GPT-4.1 mini at 44.7%. It covers competition maths (AIME 2024-25 style). The board median is 57.8%, so o3-mini-2025-01-31 (low) is 13.3 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
o3-mini-2025-01-31 (low) lands below the middle on Chess Puzzles: 6.0%, #77 of 122, with 62% of the field scoring higher. GPT-6 Astra (max) leads at 72.0%; the closest result above is GPT-4.1 at 6.0%. It covers chess tactics puzzles. The board median is 12.5%, so o3-mini-2025-01-31 (low) is 6.5 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
FrontierMath T1-3 is a weak spot. o3-mini-2025-01-31 (low) scores 3.9%, #64 of 68, behind 93% of the models measured. The leader, GPT-6 Astra (max), reaches 93.7%. It covers research-level maths, tiers 1-3. The board median is 55.6%, so o3-mini-2025-01-31 (low) is 51.8 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
GSO-Bench is a weak spot. o3-mini-2025-01-31 (low) scores 1.3%, #18 of 19, behind 89% of the models measured. The leader, GPT-5.5 (xhigh), reaches 40.2%. It covers software performance optimisation. The board median is 4.9%, so o3-mini-2025-01-31 (low) is 3.6 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
Strengths and weaknesses
Reasoning, maths and science: uneven, ahead of 31% of the field on average across 3 benchmarks. Its best board here is GPQA Diamond (#147 of 275) and its weakest is FrontierMath T1-3 (#64 of 68).
Price and value
The median input price across the 427 priced models is $0.500 per million tokens, so o3-mini-2025-01-31 (low) 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), Qwen2.5-Coder-3B-Instruct ($0.010, 46.5). Similar scores cost more on GPT-5.1 (Thinking, None) ($1.25) and Magistral Medium ($1.50).
Release history
The OpenAI model released before it was chatgpt-4o-01-29-2025 on 2025-01-29, which scores 50.6. The next one was o3-mini (high) on 2025-01-31, at 44.0.
Reading these numbers
The 5 scores on this page come from 1 source: Epoch AI Benchmarking Hub (5). No official leaderboard supplied any of them, so treat them as third-party measurements. With 5 results the aggregate rank can move a lot when one new score arrives.
Models ranked nearby
- #544 claude-opus-4-1-20250805_32K (46.0)
- #545 Eurus-2-7B-PRIME (46.0)
- #546 DeepSeek-Coder-V2-Lite-Instruct (46.0)
- #548 nvidia.nemotron-nano-9b-v2 (46.0)
- #549 Gemini 2.0 Flash Thinking Exp (45.9)
- #550 Mixtral-8x7B-v0.1 (45.9)
More from OpenAI
- GPT-6 Astra (max) (#2, 64.0)
- GPT-6.1 Sol (max) (#5, 60.6)
- GPT-5.6 Sol (max) (#6, 60.1)
- GPT-6 Sol (max) (#7, 60.0)
- GPT-5.5 (xhigh) (#11, 58.0)
- GPT-5.6 Terra (max) (#12, 57.8)
Compare it on the live leaderboard → · How the aggregate score works