# Llama 3.2 3B vs o3-pro

> o3-pro is the stronger model overall, scoring 42.9 to 28.9 on the Noometry Index. Llama 3.2 3B costs 292× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/llama-3-2-3b-vs-o3-pro
- Last updated: 2026-10-11
- Shared benchmarks: 0

## Summary

- The widest gap is in long context, where o3-pro leads 72.2 to 33.4.
- Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $20 / $80 for o3-pro.
- o3-pro accepts more context: 200K tokens versus 131K.
- Llama 3.2 3B has downloadable open weights; the other is API-only.

## Snapshot

| | Llama 3.2 3B | o3-pro |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 28.9 | 42.9 |
| Rank | 321 | 105 |
| Context | 131K | 200K |
| Input $/M | $0.05 | $20 |
| Output $/M | $0.33 | $80 |
| Weights | Open | Proprietary |

## Coding

- Llama 3.2 3B: 27.6 (#319)
- o3-pro: 55.5 (#24)

| Benchmark | Llama 3.2 3B | o3-pro |
|---|---|---|
| Aider Polyglot | — | 84.9% |
| WeirdML | — | 58.2% |
| BigCodeBench Instruct | 23.4% | — |
| LMArena Coding | 1098 | — |
| BigCodeBench Complete | 28.3% | — |

## Agentic & Tool Use

- Llama 3.2 3B: 20.1 (#143)
- o3-pro: —

| Benchmark | Llama 3.2 3B | o3-pro |
|---|---|---|
| Berkeley Function Calling Leaderboard | 21.9% | — |
| BALROG | 10.1% | — |

## Reasoning

- Llama 3.2 3B: 21.0 (#228)
- o3-pro: 23.8 (#171)

| Benchmark | Llama 3.2 3B | o3-pro |
|---|---|---|
| ARC-AGI-2 | — | 4.9% |
| Kagi LLM Benchmark | — | 72.1% |
| ARC-AGI-1 | — | 59.3% |
| LMArena Hard Prompts | 1095 | — |
| DTBench | — | 86.9% |
| LMCA | — | 38.5% |
| Epoch Capabilities Index | — | 147.42 |

## Math

- Llama 3.2 3B: 32.4 (#214)
- o3-pro: —

| Benchmark | Llama 3.2 3B | o3-pro |
|---|---|---|
| LMArena Math | 1126 | — |

## Knowledge

- Llama 3.2 3B: 29.7 (#235)
- o3-pro: 29.5 (#238)

| Benchmark | Llama 3.2 3B | o3-pro |
|---|---|---|
| Confabulations | — | 14.2% |
| Vectara Hallucination Rate | — | 23.3% |
| LMArena Expert | 1090 | — |

## Multilingual

- Llama 3.2 3B: 26.2 (#281)
- o3-pro: —

| Benchmark | Llama 3.2 3B | o3-pro |
|---|---|---|
| LMArena Non-English | 1019 | — |
| LMArena Chinese | 1017 | — |
| LMArena German | 1056 | — |
| LMArena Russian | 949 | — |

## Instruction Following

- Llama 3.2 3B: 56.0 (#275)
- o3-pro: —

| Benchmark | Llama 3.2 3B | o3-pro |
|---|---|---|
| LMArena Instruction Following | 1089 | — |

## Long Context

- Llama 3.2 3B: 33.4 (#261)
- o3-pro: 72.2 (#1)

| Benchmark | Llama 3.2 3B | o3-pro |
|---|---|---|
| Fiction.LiveBench | — | 97.2% |
| LMArena Longer Query | 1100 | — |

## Writing & Preference

- Llama 3.2 3B: 24.7 (#307)
- o3-pro: 57.1 (#133)

| Benchmark | Llama 3.2 3B | o3-pro |
|---|---|---|
| LMArena Text | 1110 | — |
| LMArena Creative Writing | 1094 | — |
| Short-Story Creative Writing | — | 84.4% |
| EQ-Bench Creative Writing | 595 | — |
| LMArena Multi-Turn | 1105 | — |

## FAQ

### Is Llama 3.2 3B better than o3-pro?

o3-pro is the stronger model overall, scoring 42.9 to 28.9 on the Noometry Index. Llama 3.2 3B costs 292× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.

### Which is cheaper, Llama 3.2 3B or o3-pro?

Llama 3.2 3B is cheaper. It lists at $0.05 per million input tokens and $0.33 per million output tokens; o3-pro lists at $20 and $80.

### Is Llama 3.2 3B or o3-pro better for coding?

o3-pro scores higher on coding benchmarks: 55.5 versus 27.6 in the Noometry coding category.

### Which has the bigger context window?

o3-pro does, with 200K tokens against 131K.

### How many benchmarks do Llama 3.2 3B and o3-pro share?

0 benchmarks have published results for both models. Llama 3.2 3B has 18 scored results on Noometry and o3-pro has 12.