Model comparison
Gemini 3 Pro vs Llama 3.2 3B
Gemini 3 Pro is the stronger model overall, scoring 54.7 to 28.4 on the Noometry Index.
Last verified . 16 shared benchmarks.
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MetaSummary
- They share 16 benchmarks with published results for both. Gemini 3 Pro scores higher in 9 categories and Llama 3.2 3B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Gemini 3 Pro leads 66.6 to 24.9.
- The biggest single-benchmark swing is Berkeley Function Calling Leaderboard: 72.5% for Gemini 3 Pro and 21.9% for Llama 3.2 3B.
- Llama 3.2 3B has downloadable open weights; the other is API-only.
Side by side
| Gemini 3 Pro | Llama 3.2 3B | |
|---|---|---|
| Provider | Meta | |
| Noometry Index | 54.7 | 28.4 |
| Released | 2025-11-18 | 2024-09-24 |
| Weights | Proprietary | Open |
| Context window | — | 131K |
| Max output | — | 118K |
| Input $ / M tokens | — | $0.05 |
| Output $ / M tokens | — | $0.33 |
| Results tracked | 67 | 18 |
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Category by category
Coding Gemini 3 Pro leads
Gemini 3 Pro: 52.1 (#33), Llama 3.2 3B: 27.1 (#314)
| Benchmark | Gemini 3 Pro | Llama 3.2 3B |
|---|---|---|
| LMArena Coding | 1482 | 1098 |
| SWE-bench Verified | 72.9% | — |
| SWE-bench Verified (bash only) | 74.2% | — |
| LMArena WebDev | 1439 | — |
| SWE-bench Multilingual | 68.7% | — |
| GSO | 18.6% | — |
| WeirdML | 69.9% | — |
| BigCodeBench Instruct | — | 23.4% |
| BigCodeBench Complete | — | 28.3% |
| ALE-Bench | 1,177 | — |
| AlgoTune | 1.83 | — |
Agentic & Tool Use Gemini 3 Pro leads
Gemini 3 Pro: 40.5 (#21), Llama 3.2 3B: 19.9 (#135)
| Benchmark | Gemini 3 Pro | Llama 3.2 3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 72.5% | 21.9% |
| BALROG | 58.1% | 10.1% |
| Terminal-Bench | 69.4% | — |
| GDPval | 40.3% | — |
| Remote Labor Index | 1.3% | — |
| τ²-bench Airline | 80.5% | — |
| τ²-bench Banking | 18% | — |
| τ²-bench Retail | 75.9% | — |
| τ²-bench Telecom | 91% | — |
| DeepResearch Bench | 46.3% | — |
| LMArena Search | 1207 | — |
| METR Time Horizons | 71% | — |
| Vending-Bench 2 | 5,478 | — |
Reasoning Gemini 3 Pro leads
Gemini 3 Pro: 52.5 (#28), Llama 3.2 3B: 20.1 (#225)
| Benchmark | Gemini 3 Pro | Llama 3.2 3B |
|---|---|---|
| LMArena Hard Prompts | 1481 | 1095 |
| ARC-AGI-2 | 31.1% | — |
| SimpleBench | 76.4% | — |
| Kagi LLM Benchmark | 80.1% | — |
| NYT Connections (extended) | 94.4% | — |
| ARC-AGI-1 | 75% | — |
| CritPt | 6.9% | — |
| Chess Puzzles | 31% | — |
| EnigmaEval | 18.2% | — |
| Epoch Capabilities Index | 152.96 | — |
| ForecastBench | 61.2 | — |
Math Gemini 3 Pro leads
Gemini 3 Pro: 48.8 (#50), Llama 3.2 3B: 29.9 (#213)
| Benchmark | Gemini 3 Pro | Llama 3.2 3B |
|---|---|---|
| LMArena Math | 1475 | 1126 |
| MathArena Final-Answer Competitions | 67% | — |
| OTIS Mock AIME 2024-2025 | 91.4% | — |
| ProofBench | 20% | — |
| Omni-MATH | 55.5% | — |
| FrontierMath (Feb 2025 set) | 37.6% | — |
| FrontierMath Tier 4 (v1) | 18.8% | — |
Knowledge Gemini 3 Pro leads
Gemini 3 Pro: 64.3 (#15), Llama 3.2 3B: 29.1 (#232)
| Benchmark | Gemini 3 Pro | Llama 3.2 3B |
|---|---|---|
| LMArena Expert | 1475 | 1090 |
| GPQA Diamond | 92.6% | — |
| Humanity's Last Exam | 37.5% | — |
| MMLU-Pro | 90.3% | — |
| Vectara Hallucination Rate | 13.6% | — |
| GPQA (HELM) | 80.3% | — |
Multimodal Not comparable
Gemini 3 Pro: 56.9 (#1), Llama 3.2 3B: —
| Benchmark | Gemini 3 Pro | Llama 3.2 3B |
|---|---|---|
| LMArena Vision | 1305 | — |
| GeoBench | 84% | — |
| VPCT | 91% | — |
| LMArena Document | 1434 | — |
Multilingual Gemini 3 Pro leads
Gemini 3 Pro: 57.1 (#14), Llama 3.2 3B: 26.4 (#276)
| Benchmark | Gemini 3 Pro | Llama 3.2 3B |
|---|---|---|
| LMArena Non-English | 1474 | 1019 |
| LMArena Chinese | 1522 | 1017 |
| LMArena German | 1517 | 1056 |
| LMArena Russian | 1493 | 949 |
| LMArena French | 1492 | — |
| LMArena Japanese | 1513 | — |
| LMArena Korean | 1449 | — |
| LMArena Spanish | 1468 | — |
Instruction Following Gemini 3 Pro leads
Gemini 3 Pro: 76.4 (#42), Llama 3.2 3B: 56.3 (#270)
| Benchmark | Gemini 3 Pro | Llama 3.2 3B |
|---|---|---|
| LMArena Instruction Following | 1458 | 1089 |
| IFEval | 87.7% | — |
Long Context Gemini 3 Pro leads
Gemini 3 Pro: 44.0 (#75), Llama 3.2 3B: 33.4 (#256)
| Benchmark | Gemini 3 Pro | Llama 3.2 3B |
|---|---|---|
| LMArena Longer Query | 1472 | 1101 |
| CL-bench | 15.8% | — |
Writing & Preference Gemini 3 Pro leads
Gemini 3 Pro: 66.6 (#34), Llama 3.2 3B: 24.9 (#302)
| Benchmark | Gemini 3 Pro | Llama 3.2 3B |
|---|---|---|
| LMArena Text | 1479 | 1110 |
| LMArena Creative Writing | 1482 | 1094 |
| EQ-Bench Creative Writing | 1525 | 595 |
| LMArena Multi-Turn | 1484 | 1105 |
| WildBench | 85.9% | — |
Frequently asked questions
Is Gemini 3 Pro better than Llama 3.2 3B?
Gemini 3 Pro is the stronger model overall, scoring 54.7 to 28.4 on the Noometry Index.
Is Gemini 3 Pro or Llama 3.2 3B better for coding?
Gemini 3 Pro scores higher on coding benchmarks: 52.1 versus 27.1 in the Noometry coding category.
How many benchmarks do Gemini 3 Pro and Llama 3.2 3B share?
16 benchmarks have published results for both models. Gemini 3 Pro has 67 scored results on Noometry and Llama 3.2 3B has 18.