# Llama 3.2 3B vs Mistral Nemo

> Llama 3.2 3B is the stronger model overall, scoring 28.4 to 25.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/llama-3-2-3b-vs-mistral-nemo
- Last updated: 2026-10-10
- Shared benchmarks: 3

## Summary

- They share 3 benchmarks with published results for both. Llama 3.2 3B scores higher in 3 categories and Mistral Nemo in 2 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Llama 3.2 3B leads 29.1 to 12.3.
- The biggest single-benchmark swing is BALROG: 10.1% for Llama 3.2 3B and 17.6% for Mistral Nemo.
- Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $0.15 / $0.15 for Mistral Nemo.
- Llama 3.2 3B accepts more context: 131K tokens versus 128K.

## Snapshot

| | Llama 3.2 3B | Mistral Nemo |
|---|---|---|
| Provider | Meta | Mistral AI |
| Noometry Index | 28.4 | 25.9 |
| Rank | 318 | 332 |
| Context | 131K | 128K |
| Input $/M | $0.05 | $0.15 |
| Output $/M | $0.33 | $0.15 |
| Weights | Open | Open |

## Coding

- Llama 3.2 3B: 27.1 (#314)
- Mistral Nemo: —

| Benchmark | Llama 3.2 3B | Mistral Nemo |
|---|---|---|
| BigCodeBench Instruct | 23.4% | — |
| LMArena Coding | 1098 | — |
| BigCodeBench Complete | 28.3% | — |

## Agentic & Tool Use

- Llama 3.2 3B: 19.9 (#135)
- Mistral Nemo: 23.3 (#118)

| Benchmark | Llama 3.2 3B | Mistral Nemo |
|---|---|---|
| Berkeley Function Calling Leaderboard | 21.9% | 27.6% |
| BALROG | 10.1% | 17.6% |

## Reasoning

- Llama 3.2 3B: 20.1 (#225)
- Mistral Nemo: 19.9 (#230)

| Benchmark | Llama 3.2 3B | Mistral Nemo |
|---|---|---|
| LMArena Hard Prompts | 1095 | — |
| DTBench | — | 48.6% |
| Epoch Capabilities Index | — | 118.63 |
| PIQA | — | 83.5% |

## Math

- Llama 3.2 3B: 29.9 (#213)
- Mistral Nemo: 23.5 (#263)

| Benchmark | Llama 3.2 3B | Mistral Nemo |
|---|---|---|
| LMArena Math | 1126 | — |
| MATH Level 5 | — | 10.8% |
| GSM8K | — | 84.2% |

## Knowledge

- Llama 3.2 3B: 29.1 (#232)
- Mistral Nemo: 12.3 (#293)

| Benchmark | Llama 3.2 3B | Mistral Nemo |
|---|---|---|
| GPQA Diamond | — | 29.9% |
| LMArena Expert | 1090 | — |
| BoolQ | — | 82.5% |

## Multilingual

- Llama 3.2 3B: 26.4 (#276)
- Mistral Nemo: —

| Benchmark | Llama 3.2 3B | Mistral Nemo |
|---|---|---|
| LMArena Non-English | 1019 | — |
| LMArena Chinese | 1017 | — |
| LMArena German | 1056 | — |
| LMArena Russian | 949 | — |

## Instruction Following

- Llama 3.2 3B: 56.3 (#270)
- Mistral Nemo: —

| Benchmark | Llama 3.2 3B | Mistral Nemo |
|---|---|---|
| LMArena Instruction Following | 1089 | — |

## Long Context

- Llama 3.2 3B: 33.4 (#256)
- Mistral Nemo: —

| Benchmark | Llama 3.2 3B | Mistral Nemo |
|---|---|---|
| LMArena Longer Query | 1101 | — |

## Writing & Preference

- Llama 3.2 3B: 24.9 (#302)
- Mistral Nemo: 28.6 (#291)

| Benchmark | Llama 3.2 3B | Mistral Nemo |
|---|---|---|
| EQ-Bench Creative Writing | 595 | 881 |
| LMArena Text | 1110 | — |
| LMArena Creative Writing | 1094 | — |
| LMArena Multi-Turn | 1105 | — |

## FAQ

### Is Llama 3.2 3B better than Mistral Nemo?

Llama 3.2 3B is the stronger model overall, scoring 28.4 to 25.9 on the Noometry Index.

### Which is cheaper, Llama 3.2 3B or Mistral Nemo?

Llama 3.2 3B is cheaper. It lists at $0.05 per million input tokens and $0.33 per million output tokens; Mistral Nemo lists at $0.15 and $0.15.

### Which has the bigger context window?

Llama 3.2 3B does, with 131K tokens against 128K.

### How many benchmarks do Llama 3.2 3B and Mistral Nemo share?

3 benchmarks have published results for both models. Llama 3.2 3B has 18 scored results on Noometry and Mistral Nemo has 10.