Model comparison
Claude 3.7 Sonnet vs Llama 3.2 1B
Claude 3.7 Sonnet is the stronger model overall, scoring 39.5 to 20.1 on the Noometry Index.
Last verified . 17 shared benchmarks.
MetaSummary
- They share 17 benchmarks with published results for both. Claude 3.7 Sonnet scores higher in 9 categories and Llama 3.2 1B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Claude 3.7 Sonnet leads 54.4 to 21.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 57.8% for Claude 3.7 Sonnet and 0.6% for Llama 3.2 1B.
- Llama 3.2 1B has downloadable open weights; the other is API-only.
Side by side
| Claude 3.7 Sonnet | Llama 3.2 1B | |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 39.5 | 20.1 |
| Released | 2025-02-24 | 2024-09-24 |
| Weights | Proprietary | Open |
| Context window | — | 60K |
| Max output | — | 54K |
| Input $ / M tokens | — | $0.027 |
| Output $ / M tokens | — | $0.20 |
| Results tracked | 58 | 22 |
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Category by category
Coding Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 40.6 (#136), Llama 3.2 1B: 21.1 (#338)
| Benchmark | Claude 3.7 Sonnet | Llama 3.2 1B |
|---|---|---|
| LMArena Coding | 1361 | 1070 |
| SWE-bench Verified | 61% | — |
| SWE-bench Verified (bash only) | 52.8% | — |
| Aider Polyglot | 64.9% | — |
| GSO | 3.8% | — |
| BigCodeBench Instruct | — | 8.2% |
| LiveBench Coding | 74.5% | — |
| BigCodeBench Complete | — | 11.3% |
| CadEval | 54% | — |
Agentic & Tool Use Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 34.1 (#50), Llama 3.2 1B: 14.6 (#150)
| Benchmark | Claude 3.7 Sonnet | Llama 3.2 1B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 10.8% |
| TheAgentCompany | 30.9% | — |
| Cybench | 20% | — |
| DeepResearch Bench | 43.6% | — |
| OSWorld | 35.8% | — |
| BALROG | — | 6.6% |
| METR Time Horizons | 60% | — |
Reasoning Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 18.6 (#277), Llama 3.2 1B: 16.2 (#308)
| Benchmark | Claude 3.7 Sonnet | Llama 3.2 1B |
|---|---|---|
| LMArena Hard Prompts | 1333 | 1044 |
| Epoch Capabilities Index | 141.16 | 101.99 |
| ARC-AGI-2 | 0.9% | — |
| SimpleBench | 46.4% | — |
| ARC-AGI-1 | 28.6% | — |
| Chess Puzzles | — | 0% |
| EnigmaEval | 4.2% | — |
| LiveBench Reasoning | 87.8% | — |
| LiveBench Data Analysis | 74% | — |
| ForecastBench | 61.8 | — |
| LiveBench | 76.1% | — |
Math Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 37.5 (#153), Llama 3.2 1B: 10.4 (#313)
| Benchmark | Claude 3.7 Sonnet | Llama 3.2 1B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 57.8% | 0.6% |
| LMArena Math | 1337 | 1086 |
| Omni-MATH | 33% | — |
| LiveBench Math | 79% | — |
| MATH Level 5 | 91.2% | — |
| FrontierMath (Feb 2025 set) | 4.1% | — |
Knowledge Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 39.8 (#130), Llama 3.2 1B: 7.2 (#312)
| Benchmark | Claude 3.7 Sonnet | Llama 3.2 1B |
|---|---|---|
| GPQA Diamond | 79.7% | 23.9% |
| LMArena Expert | 1321 | 1007 |
| Humanity's Last Exam | 8% | — |
| MMLU-Pro | 78.4% | — |
| Confabulations | 14.7% | — |
| GPQA (HELM) | 60.8% | — |
Multimodal Not comparable
Claude 3.7 Sonnet: 33.7 (#95), Llama 3.2 1B: —
| Benchmark | Claude 3.7 Sonnet | Llama 3.2 1B |
|---|---|---|
| LMArena Vision | 1169 | — |
| GeoBench | 68% | — |
| VPCT | 39% | — |
| SpatialViz-Bench | 33.9% | — |
Multilingual Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 44.1 (#179), Llama 3.2 1B: 23.8 (#292)
| Benchmark | Claude 3.7 Sonnet | Llama 3.2 1B |
|---|---|---|
| LMArena Non-English | 1296 | 973 |
| LMArena Chinese | 1299 | 959 |
| LMArena German | 1301 | 1014 |
| LMArena Russian | 1311 | 941 |
| LMArena French | 1303 | — |
| LMArena Japanese | 1267 | — |
| LMArena Korean | 1249 | — |
| LMArena Spanish | 1298 | — |
Instruction Following Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 72.9 (#125), Llama 3.2 1B: 52.4 (#290)
| Benchmark | Claude 3.7 Sonnet | Llama 3.2 1B |
|---|---|---|
| LMArena Instruction Following | 1352 | 1031 |
| LiveBench Instruction Following | 81.3% | — |
| IFEval | 83.4% | — |
Long Context Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 50.3 (#10), Llama 3.2 1B: 31.9 (#274)
| Benchmark | Claude 3.7 Sonnet | Llama 3.2 1B |
|---|---|---|
| LMArena Longer Query | 1373 | 1050 |
| Fiction.LiveBench | 83.3% | — |
Writing & Preference Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 54.4 (#150), Llama 3.2 1B: 21.3 (#310)
| Benchmark | Claude 3.7 Sonnet | Llama 3.2 1B |
|---|---|---|
| LMArena Text | 1314 | 1055 |
| LMArena Creative Writing | 1332 | 1033 |
| EQ-Bench Creative Writing | 1412 | 200 |
| LMArena Multi-Turn | 1339 | 1030 |
| Short-Story Creative Writing | 81.1% | — |
| WildBench | 81.4% | — |
| LiveBench Language | 59.9% | — |
Frequently asked questions
Is Claude 3.7 Sonnet better than Llama 3.2 1B?
Claude 3.7 Sonnet is the stronger model overall, scoring 39.5 to 20.1 on the Noometry Index.
Is Claude 3.7 Sonnet or Llama 3.2 1B better for coding?
Claude 3.7 Sonnet scores higher on coding benchmarks: 40.6 versus 21.1 in the Noometry coding category.
How many benchmarks do Claude 3.7 Sonnet and Llama 3.2 1B share?
17 benchmarks have published results for both models. Claude 3.7 Sonnet has 58 scored results on Noometry and Llama 3.2 1B has 22.