ollama/llama3.2:3b-instruct-fp16: benchmark scores, price and ranking
ollama/llama3.2:3b-instruct-fp16 from Meta ranks #631 of 743 LLMs on the LLMs Tiger aggregate benchmark score (44.5), based on 1 benchmark results captured up to 2026-10-13.
- Organisation
- Meta
- Type
- Open-weight / local model
- Open weights
- Yes
- Aggregate rank
- #631 of 743 (score 44.5)
Across the 1 benchmark where at least ten models are scored, ollama/llama3.2:3b-instruct-fp16 is in the top 10% on 0 and in the top half on 0.
ollama/llama3.2:3b-instruct-fp16 benchmark results
| Benchmark | Score | Rank | Source | Captured |
|---|---|---|---|---|
| Aider Code Editing | 26.3% | #88 of 92 | Aider Aider Code Editing leaderboard | 2026-10-13 |
About ollama/llama3.2:3b-instruct-fp16
ollama/llama3.2:3b-instruct-fp16 is an open-weight model that can run on your own hardware from Meta. No API price is listed for it yet. We hold 1 benchmark result for it across 1 area, and none is in the top tenth of its board.
Where ollama/llama3.2:3b-instruct-fp16 stands
On our aggregate score, ollama/llama3.2:3b-instruct-fp16 is #631 of 743 ranked models, in the lower half. Its score is 44.5; the scale is centred on 50, so it sits 5.5 points below the typical model. That beats 15% of the ranked field. Among the 6 ranked Meta models it is #5. The next one up is Llama 4 Scout Instruct at 45.6. The next one down is SWE-Llama 7B at 43.2.
ollama/llama3.2:3b-instruct-fp16, benchmark by benchmark
Aider Code Editing is a weak spot. ollama/llama3.2:3b-instruct-fp16 scores 26.3%, #88 of 92, behind 95% of the models measured. The leader, Claude 3.5-Sonnet-20241022, reaches 84.2%. It covers Aider official benchmark. The board median is 55.6%, so ollama/llama3.2:3b-instruct-fp16 is 29.3 points below it. Source: Aider Aider Code Editing leaderboard, captured 2026-10-13.
Reading these numbers
The 1 score on this page comes from 1 source: Aider Aider Code Editing leaderboard (1). 1 of them come from an official leaderboard and 0 from datasets or third-party runs. With 1 results the aggregate rank can move a lot when one new score arrives.
Models ranked nearby
- #628 DeepSeek-R1-Distill-Qwen-1.5B (44.6)
- #629 granite-3.0-8b-base (44.6)
- #630 Mistral-7B-Instruct-v0.2 (44.6)
- #632 ollama/tulu3 (44.5)
- #633 qwen-turbo-2024-11-01 (44.5)
- #634 Mistral-7B-v0.2 (44.5)
More from Meta
- Llama3-SWE-RL-70B (#337, 48.6)
- llama3-70b-8192 (#381, 48.1)
- Llama 4 Maverick Instruct (#491, 46.7)
- Llama 4 Scout Instruct (#565, 45.6)
- SWE-Llama 7B (#683, 43.2)
Compare it on the live leaderboard → · How the aggregate score works