granite-4.0-micro: benchmark scores, price and ranking
granite-4.0-micro from IBM ranks #685 of 743 LLMs on the LLMs Tiger aggregate benchmark score (43.2), based on 3 benchmark results captured up to 2026-10-13.
- Organisation
- IBM
- Type
- Open-weight / local model
- Open weights
- Yes
- Released
- 2025-10-02 (source: epoch)
- Cheapest API price
- $0.017 in / $0.112 out per million tokens (via openrouter, observed 2026-10-13T20:47Z)
- Aggregate rank
- #685 of 743 (score 43.2)
Relative to other models, granite-4.0-micro is strongest on OTIS Mock AIME (#166 of 189) and weakest on GPQA Diamond (#254 of 275).
Across the 3 benchmarks where at least ten models are scored, granite-4.0-micro is in the top 10% on 0 and in the top half on 0.
Its cheapest listed input price, $0.017 per million tokens, is lower than that of 99% of the 427 models with a listed price.
granite-4.0-micro benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| OTIS Mock AIME | 2.8% | #166 of 189 | Epoch AI Benchmarking Hub | 2026-10-13 |
| Chess Puzzles | 0.0% | #111 of 122 | Epoch AI Benchmarking Hub | 2026-10-13 |
| GPQA Diamond | 28.3% | #254 of 275 | Epoch AI Benchmarking Hub | 2026-10-13 |
About granite-4.0-micro
granite-4.0-micro is an open-weight model that can run on your own hardware from IBM. It was released on 2025-10-02, according to Epoch AI. The cheapest API listing we track charges $0.017 per million input tokens and $0.112 per million output tokens, through openrouter. We hold 3 benchmark results for it across 2 areas, and none is in the top tenth of its board.
Where granite-4.0-micro stands
On our aggregate score, granite-4.0-micro is #685 of 743 ranked models, in the lower half. Its score is 43.2; the scale is centred on 50, so it sits 6.8 points below the typical model. That beats 8% of the ranked field. Among the 4 ranked IBM models it is #2. The next one up is ollama/granite3-dense:8b at 43.6. The next one down is granite-4.0-1b at 42.7.
granite-4.0-micro, benchmark by benchmark
OTIS Mock AIME is a weak spot. granite-4.0-micro scores 2.8%, #166 of 189, behind 87% of the models measured. The leader, Claude Fable 5.1 (max), reaches 100.0%. It covers competition maths (AIME 2024-25 style). The board median is 57.8%, so granite-4.0-micro is 55.0 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
Chess Puzzles is a weak spot. granite-4.0-micro scores 0.0%, #111 of 122, behind 90% of the models measured. The leader, GPT-6 Astra (max), reaches 72.0%. It covers chess tactics puzzles. The board median is 12.5%, so granite-4.0-micro is 12.5 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
GPQA Diamond is a weak spot. granite-4.0-micro scores 28.3%, #254 of 275, behind 92% of the models measured. The leader, GPT-6 Astra (max), reaches 95.8%. It covers expert-level science questions. The board median is 71.7%, so granite-4.0-micro is 43.4 points below it. Source: Epoch AI Benchmarking Hub, captured 2026-10-13.
Strengths and weaknesses
Reasoning, maths and science: weak, ahead of 10% of the field on average across 2 benchmarks. Its best board here is OTIS Mock AIME (#166 of 189) and its weakest is GPQA Diamond (#254 of 275).
Price and value
The median input price across the 427 priced models is $0.500 per million tokens, so granite-4.0-micro costs less 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 Qwen2-1.5B-Instruct ($0.020) and qwen3-8b ($0.040).
Release history
The next one was granite-4.0-1b on 2025-10-28, at 42.7.
Reading these numbers
The 3 scores on this page come from 1 source: Epoch AI Benchmarking Hub (3). No official leaderboard supplied any of them, so treat them as third-party measurements. With 3 results the aggregate rank can move a lot when one new score arrives.
Models ranked nearby
- #682 open-mixtral-8x7b (43.2)
- #683 SWE-Llama 7B (43.2)
- #684 Trinity Large Thinking (43.2)
- #686 SWE-Llama 13B (43.2)
- #687 claude-3-opus-20240229 (43.2)
- #688 granite-3.1-3b-a800m-base (43.1)
More from IBM
- ollama/granite3-dense:8b (#671, 43.6)
- granite-4.0-1b (#698, 42.7)
- granite-4.0-350m (#722, 41.6)
Compare it on the live leaderboard → · How the aggregate score works