Model comparison
Claude Sonnet 5 vs Llama 3.2 3B
Claude Sonnet 5 is the stronger model overall, scoring 54.5 to 28.4 on the Noometry Index. Llama 3.2 3B costs 33× less per token, which makes it the better buy when Claude Sonnet 5's lead doesn't matter for your workload.
Last verified . 14 shared benchmarks.
MetaSummary
- They share 14 benchmarks with published results for both. Claude Sonnet 5 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 Claude Sonnet 5 leads 69.4 to 24.9.
- Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $2 / $10 for Claude Sonnet 5.
- Claude Sonnet 5 accepts more context: 1M tokens versus 131K.
- Llama 3.2 3B has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 5 | Llama 3.2 3B | |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 54.5 | 28.4 |
| Released | 2026-06-29 | 2024-09-24 |
| Weights | Proprietary | Open |
| Context window | 1M | 131K |
| Max output | 128K | 118K |
| Input $ / M tokens | $2 | $0.05 |
| Output $ / M tokens | $10 | $0.33 |
| Results tracked | 51 | 18 |
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Category by category
Coding Claude Sonnet 5 leads
Claude Sonnet 5: 55.5 (#20), Llama 3.2 3B: 27.1 (#314)
| Benchmark | Claude Sonnet 5 | Llama 3.2 3B |
|---|---|---|
| LMArena Coding | 1483 | 1098 |
| DeepSWE | 53.8% | — |
| FrontierCode | 42.7% | — |
| CursorBench | 34.1% | — |
| LMArena WebDev | 1540 | — |
| SciCode | 53.6% | — |
| GSO | 37.3% | — |
| WeirdML | 68.8% | — |
| BigCodeBench Instruct | — | 23.4% |
| BigCodeBench Complete | — | 28.3% |
| ALE-Bench | 1,463 | — |
Agentic & Tool Use Claude Sonnet 5 leads
Claude Sonnet 5: 42.7 (#16), Llama 3.2 3B: 19.9 (#135)
| Benchmark | Claude Sonnet 5 | Llama 3.2 3B |
|---|---|---|
| APEX-Agents | 54.5% | — |
| Berkeley Function Calling Leaderboard | — | 21.9% |
| BALROG | — | 10.1% |
| GBAEval | 65.3% | — |
| LMArena Search | 1194 | — |
| Vending-Bench 2 | 6,378 | — |
Reasoning Claude Sonnet 5 leads
Claude Sonnet 5: 48.2 (#37), Llama 3.2 3B: 20.1 (#225)
| Benchmark | Claude Sonnet 5 | Llama 3.2 3B |
|---|---|---|
| LMArena Hard Prompts | 1461 | 1095 |
| SimpleBench | 60.6% | — |
| NYT Connections (extended) | 75.1% | — |
| CritPt | 16.9% | — |
| Chess Puzzles | 35% | — |
| Mystery Game Puzzles | 35% | — |
| DTBench | 92.5% | — |
| LMCA | 50% | — |
| Surface Evolver Bench | 60% | — |
| Bench to the Future 3 | 0.14 | — |
| Epoch Capabilities Index | 156.34 | — |
| ForecastBench | 61.1 | — |
Math Claude Sonnet 5 leads
Claude Sonnet 5: 66.1 (#21), Llama 3.2 3B: 29.9 (#213)
| Benchmark | Claude Sonnet 5 | Llama 3.2 3B |
|---|---|---|
| LMArena Math | 1467 | 1126 |
| FrontierMath (Tiers 1-3) | 65.6% | — |
| FrontierMath Tier 4 | 29.3% | — |
| OTIS Mock AIME 2024-2025 | 94.7% | — |
| ProofBench | 77% | — |
Knowledge Claude Sonnet 5 leads
Claude Sonnet 5: 55.7 (#42), Llama 3.2 3B: 29.1 (#232)
| Benchmark | Claude Sonnet 5 | Llama 3.2 3B |
|---|---|---|
| LMArena Expert | 1491 | 1090 |
| GPQA Diamond | 90.5% | — |
| SimpleQA Verified | 33.7% | — |
Multimodal Not comparable
Claude Sonnet 5: 42.4 (#26), Llama 3.2 3B: —
| Benchmark | Claude Sonnet 5 | Llama 3.2 3B |
|---|---|---|
| LMArena Vision | 1275 | — |
| Blueprint-Bench 2 | 24.9% | — |
| LMArena Document | 1466 | — |
Multilingual Claude Sonnet 5 leads
Claude Sonnet 5: 54.0 (#55), Llama 3.2 3B: 26.4 (#276)
| Benchmark | Claude Sonnet 5 | Llama 3.2 3B |
|---|---|---|
| LMArena Non-English | 1431 | 1019 |
| LMArena Chinese | 1475 | 1017 |
| LMArena German | 1448 | 1056 |
| LMArena Russian | 1452 | 949 |
| LMArena French | 1457 | — |
| LMArena Japanese | 1422 | — |
| LMArena Korean | 1411 | — |
| LMArena Spanish | 1436 | — |
Instruction Following Claude Sonnet 5 leads
Claude Sonnet 5: 76.6 (#39), Llama 3.2 3B: 56.3 (#270)
| Benchmark | Claude Sonnet 5 | Llama 3.2 3B |
|---|---|---|
| LMArena Instruction Following | 1453 | 1089 |
Long Context Claude Sonnet 5 leads
Claude Sonnet 5: 44.8 (#53), Llama 3.2 3B: 33.4 (#256)
| Benchmark | Claude Sonnet 5 | Llama 3.2 3B |
|---|---|---|
| LMArena Longer Query | 1464 | 1101 |
Writing & Preference Claude Sonnet 5 leads
Claude Sonnet 5: 69.4 (#24), Llama 3.2 3B: 24.9 (#302)
| Benchmark | Claude Sonnet 5 | Llama 3.2 3B |
|---|---|---|
| LMArena Text | 1443 | 1110 |
| LMArena Creative Writing | 1416 | 1094 |
| EQ-Bench Creative Writing | 1794 | 595 |
| LMArena Multi-Turn | 1454 | 1105 |
| EQ-Bench 4 | 1236 | — |
Frequently asked questions
Is Claude Sonnet 5 better than Llama 3.2 3B?
Claude Sonnet 5 is the stronger model overall, scoring 54.5 to 28.4 on the Noometry Index. Llama 3.2 3B costs 33× less per token, which makes it the better buy when Claude Sonnet 5's lead doesn't matter for your workload.
Which is cheaper, Claude Sonnet 5 or Llama 3.2 3B?
Llama 3.2 3B is cheaper. It lists at $0.05 per million input tokens and $0.33 per million output tokens; Claude Sonnet 5 lists at $2 and $10.
Is Claude Sonnet 5 or Llama 3.2 3B better for coding?
Claude Sonnet 5 scores higher on coding benchmarks: 55.5 versus 27.1 in the Noometry coding category.
Which has the bigger context window?
Claude Sonnet 5 does, with 1M tokens against 131K.
How many benchmarks do Claude Sonnet 5 and Llama 3.2 3B share?
14 benchmarks have published results for both models. Claude Sonnet 5 has 51 scored results on Noometry and Llama 3.2 3B has 18.