Model comparison
Llama 3.2 3B vs o1-pro
o1-pro is the stronger model overall, scoring 31.5 to 28.9 on the Noometry Index. Llama 3.2 3B costs 2188× less per token, which makes it the better buy when o1-pro's lead doesn't matter for your workload.
Last verified . 0 shared benchmarks.
MetaSummary
- Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $150 / $600 for o1-pro.
- o1-pro accepts more context: 200K tokens versus 131K.
- Llama 3.2 3B has downloadable open weights; the other is API-only.
Side by side
| Llama 3.2 3B | o1-pro | |
|---|---|---|
| Provider | Meta | OpenAI |
| Noometry Index | 28.9 | 31.5 |
| Released | 2024-09-24 | 2025-03-19 |
| Weights | Open | Proprietary |
| Context window | 131K | 200K |
| Max output | 118K | 100K |
| Input $ / M tokens | $0.05 | $150 |
| Output $ / M tokens | $0.33 | $600 |
| Results tracked | 18 | 3 |
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Category by category
Coding Not comparable
Llama 3.2 3B: 27.6 (#319), o1-pro: —
| Benchmark | Llama 3.2 3B | o1-pro |
|---|---|---|
| BigCodeBench Instruct | 23.4% | — |
| LMArena Coding | 1098 | — |
| BigCodeBench Complete | 28.3% | — |
Agentic & Tool Use Not comparable
Llama 3.2 3B: 20.1 (#143), o1-pro: —
| Benchmark | Llama 3.2 3B | o1-pro |
|---|---|---|
| Berkeley Function Calling Leaderboard | 21.9% | — |
| BALROG | 10.1% | — |
Reasoning Too close to call
Llama 3.2 3B: 21.0 (#228), o1-pro: 20.4 (#239)
| Benchmark | Llama 3.2 3B | o1-pro |
|---|---|---|
| ARC-AGI-1 | — | 23.3% |
| EnigmaEval | — | 6.1% |
| LMArena Hard Prompts | 1095 | — |
Math Not comparable
Llama 3.2 3B: 32.4 (#214), o1-pro: —
| Benchmark | Llama 3.2 3B | o1-pro |
|---|---|---|
| LMArena Math | 1126 | — |
Knowledge Too close to call
Llama 3.2 3B: 29.7 (#235), o1-pro: 29.7 (#234)
| Benchmark | Llama 3.2 3B | o1-pro |
|---|---|---|
| Humanity's Last Exam | — | 8.1% |
| LMArena Expert | 1090 | — |
Multilingual Not comparable
Llama 3.2 3B: 26.2 (#281), o1-pro: —
| Benchmark | Llama 3.2 3B | o1-pro |
|---|---|---|
| LMArena Non-English | 1019 | — |
| LMArena Chinese | 1017 | — |
| LMArena German | 1056 | — |
| LMArena Russian | 949 | — |
Instruction Following Not comparable
Llama 3.2 3B: 56.0 (#275), o1-pro: —
| Benchmark | Llama 3.2 3B | o1-pro |
|---|---|---|
| LMArena Instruction Following | 1089 | — |
Long Context Not comparable
Llama 3.2 3B: 33.4 (#261), o1-pro: —
| Benchmark | Llama 3.2 3B | o1-pro |
|---|---|---|
| LMArena Longer Query | 1100 | — |
Writing & Preference Not comparable
Llama 3.2 3B: 24.7 (#307), o1-pro: —
| Benchmark | Llama 3.2 3B | o1-pro |
|---|---|---|
| LMArena Text | 1110 | — |
| LMArena Creative Writing | 1094 | — |
| EQ-Bench Creative Writing | 595 | — |
| LMArena Multi-Turn | 1105 | — |
Frequently asked questions
Is Llama 3.2 3B better than o1-pro?
o1-pro is the stronger model overall, scoring 31.5 to 28.9 on the Noometry Index. Llama 3.2 3B costs 2188× less per token, which makes it the better buy when o1-pro's lead doesn't matter for your workload.
Which is cheaper, Llama 3.2 3B or o1-pro?
Llama 3.2 3B is cheaper. It lists at $0.05 per million input tokens and $0.33 per million output tokens; o1-pro lists at $150 and $600.
Which has the bigger context window?
o1-pro does, with 200K tokens against 131K.
How many benchmarks do Llama 3.2 3B and o1-pro share?
0 benchmarks have published results for both models. Llama 3.2 3B has 18 scored results on Noometry and o1-pro has 3.