gemini-1.5-pro-001: benchmark scores, price and ranking
gemini-1.5-pro-001 from Google DeepMind ranks #650 of 743 LLMs on the LLMs Tiger aggregate benchmark score (44.0), based on 4 benchmark results captured up to 2026-10-13.
- Organisation
- Google DeepMind
- Type
- Frontier model
- Open weights
- No
- Released
- 2024-05-14 (source: epoch)
- Aggregate rank
- #650 of 743 (score 44.0)
Relative to other models, gemini-1.5-pro-001 is strongest on Aider Code Editing (#44 of 92) and weakest on OTIS Mock AIME (#147 of 189).
Across the 4 benchmarks where at least ten models are scored, gemini-1.5-pro-001 is in the top 10% on 0 and in the top half on 1.
gemini-1.5-pro-001 benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| Aider Code Editing | 57.1% | #44 of 92 | Aider Aider Code Editing leaderboard | 2026-10-13 |
| GPQA Diamond | 45.9% | #207 of 275 | Epoch AI Benchmarking Hub | 2026-10-13 |
| DTBench | 56.5% | #111 of 146 | Epoch AI Benchmarking Hub | 2026-10-13 |
| OTIS Mock AIME | 6.8% | #147 of 189 | Epoch AI Benchmarking Hub | 2026-10-13 |
About gemini-1.5-pro-001
gemini-1.5-pro-001 is a frontier model from Google DeepMind. It was released on 2024-05-14, according to Epoch AI. No API price is listed for it yet. We hold 4 benchmark results for it across 3 areas, and none is in the top tenth of its board.
Where gemini-1.5-pro-001 stands
On our aggregate score, gemini-1.5-pro-001 is #650 of 743 ranked models, in the lower half. Its score is 44.0; the scale is centred on 50, so it sits 6.0 points below the typical model. That beats 13% of the ranked field. Among the 41 ranked Google DeepMind models it is #29. The next one up is gemini-2.5-flash-lite-preview-06-17 (Default thinking length) at 44.6. The next one down is gemini-1.5-pro-002 at 43.9.
gemini-1.5-pro-001, benchmark by benchmark
Aider Code Editing puts gemini-1.5-pro-001 at 57.1%, #44 of 92. That beats 52% of the models tested, but 27.1 points short of Claude 3.5-Sonnet-20241022 (84.2%). The results either side are Qwen2.5-Coder-7B-Instruct (57.9%) and gpt-3.5-turbo-1106 (56.1%). It covers Aider official benchmark. The board median is 55.6%, so gemini-1.5-pro-001 is 1.5 points above it. Source: Aider Aider Code Editing leaderboard, captured 2026-10-13.
gemini-1.5-pro-001 lands below the middle on GPQA Diamond: 45.9%, #207 of 275, with 75% of the field scoring higher. GPT-6 Astra (max) leads at 95.8%; the closest result above is gpt-oss-20b (high) at 46.0%. It covers expert-level science questions. The board median is 71.7%, so gemini-1.5-pro-001 is 25.9 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
gemini-1.5-pro-001 lands below the middle on DTBench: 56.5%, #111 of 146, with 75% of the field scoring higher. Claude Opus 5.5 (max) leads at 98.9%; the closest result above is Claude 3.5 Haiku (Oct 2024) at 56.7%. It covers dynamic tool-use benchmark. The board median is 68.8%, so gemini-1.5-pro-001 is 12.3 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
gemini-1.5-pro-001 lands below the middle on OTIS Mock AIME: 6.8%, #147 of 189, with 77% of the field scoring higher. Claude Fable 5.1 (max) leads at 100.0%; the closest result above is gpt-4o-mini-2024-07-18 at 6.9%. It covers competition maths (AIME 2024-25 style). The board median is 57.8%, so gemini-1.5-pro-001 is 51.0 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
Strengths and weaknesses
Reasoning, maths and science: weak, ahead of 23% of the field on average across 2 benchmarks. Its best board here is GPQA Diamond (#207 of 275) and its weakest is OTIS Mock AIME (#147 of 189).
Release history
The Google DeepMind model released before it was gemini-1.5-pro-001-feb24 on 2024-02-15, which scores 48.1. The next one was Gemini 1.5 Flash (May 2024) on 2024-05-23, at 42.6.
Reading these numbers
The 4 scores on this page come from 2 sources: Epoch AI Benchmarking Hub (3), Aider Aider Code Editing leaderboard (1). 1 of them come from an official leaderboard and 3 from datasets or third-party runs. With 4 results the aggregate rank can move a lot when one new score arrives.
Models ranked nearby
- #647 DeepSeek-V3 (Mar 2025) (44.1)
- #648 Yi-34B-Chat (44.0)
- #649 o3-mini (high) (44.0)
- #651 Mellum2-12B-A2.5B-Base (44.0)
- #652 Mellum2-12B-A2.5B-Base-Pretrain (44.0)
- #653 Phi-3-medium-128k-instruct (44.0)
More from Google DeepMind
- Gemini 3.8 Flash (high) (#26, 54.0)
- Gemini 3.7 Flash (high) (#27, 53.9)
- Gemini 3 Pro Preview (#31, 53.7)
- Gemini 3 Deep Think (#60, 52.6)
- AI co-mathematician (#69, 52.3)
- Gemini 3 Flash (#120, 51.5)
Compare it on the live leaderboard → · How the aggregate score works