# Claude Sonnet 4.5 vs Llama 3.2 1B

> Claude Sonnet 4.5 is the stronger model overall, scoring 44.1 to 20.1 on the Noometry Index. Llama 3.2 1B costs 85× less per token, which makes it the better buy when Claude Sonnet 4.5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-sonnet-4-5-vs-llama-3-2-1b
- Last updated: 2026-10-12
- Shared benchmarks: 19

## Summary

- They share 19 benchmarks with published results for both. Claude Sonnet 4.5 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 Sonnet 4.5 leads 66.5 to 21.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 77.8% for Claude Sonnet 4.5 and 0.6% for Llama 3.2 1B.
- Llama 3.2 1B is cheaper at $0.027 / $0.20 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.5.
- Claude Sonnet 4.5 accepts more context: 200K tokens versus 60K.
- Llama 3.2 1B has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Sonnet 4.5 | Llama 3.2 1B |
|---|---|---|
| Provider | Anthropic | Meta |
| Noometry Index | 44.1 | 20.1 |
| Rank | 81 | 354 |
| Context | 200K | 60K |
| Input $/M | $3 | $0.027 |
| Output $/M | $15 | $0.20 |
| Weights | Proprietary | Open |

## Coding

- Claude Sonnet 4.5: 47.3 (#61)
- Llama 3.2 1B: 21.1 (#338)

| Benchmark | Claude Sonnet 4.5 | Llama 3.2 1B |
|---|---|---|
| LMArena Coding | 1489 | 1070 |
| SWE-bench Verified | 71.3% | — |
| SWE-bench Verified (bash only) | 71.4% | — |
| LMArena WebDev | 1393 | — |
| SWE-bench Multilingual | 67% | — |
| SciCode | 44.7% | — |
| GSO | 14.7% | — |
| WeirdML | 47.7% | — |
| BigCodeBench Instruct | — | 8.2% |
| BigCodeBench Complete | — | 11.3% |
| ALE-Bench | 796.15 | — |
| AlgoTune | 1.52 | — |

## Agentic & Tool Use

- Claude Sonnet 4.5: 38.3 (#32)
- Llama 3.2 1B: 14.6 (#150)

| Benchmark | Claude Sonnet 4.5 | Llama 3.2 1B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 73.2% | 10.8% |
| Terminal-Bench | 46.5% | — |
| GDPval | 42.5% | — |
| Remote Labor Index | 2.1% | — |
| τ²-bench Airline | 72% | — |
| τ²-bench Banking | 25.3% | — |
| τ²-bench Retail | 72.4% | — |
| τ²-bench Telecom | 84.9% | — |
| Cybench | 60% | — |
| DeepResearch Bench | 52.6% | — |
| OSWorld | 62.9% | — |
| BALROG | — | 6.6% |
| LMArena Search | 1159 | — |
| METR Time Horizons | 67.4% | — |
| Vending-Bench 2 | 3,839 | — |

## Reasoning

- Claude Sonnet 4.5: 26.9 (#125)
- Llama 3.2 1B: 16.2 (#308)

| Benchmark | Claude Sonnet 4.5 | Llama 3.2 1B |
|---|---|---|
| Chess Puzzles | 12% | 0% |
| LMArena Hard Prompts | 1462 | 1044 |
| Epoch Capabilities Index | 146.84 | 101.99 |
| ARC-AGI-2 | 13.6% | — |
| SimpleBench | 54.3% | — |
| Kagi LLM Benchmark | 57.9% | — |
| NYT Connections (extended) | 37.3% | — |
| ARC-AGI-1 | 63.7% | — |
| CritPt | 1.1% | — |
| EnigmaEval | 6% | — |
| EBR-Bench | 2.4% | — |
| Mystery Game Puzzles | 17% | — |
| DTBench | 83.2% | — |
| LMCA | 38.8% | — |
| ForecastBench | 61.9 | — |

## Math

- Claude Sonnet 4.5: 32.3 (#216)
- Llama 3.2 1B: 10.4 (#313)

| Benchmark | Claude Sonnet 4.5 | Llama 3.2 1B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 77.8% | 0.6% |
| LMArena Math | 1449 | 1086 |
| FrontierMath (Tiers 1-3) | 23.9% | — |
| FrontierMath Tier 4 | 2.4% | — |
| ProofBench | 19% | — |
| Omni-MATH | 55.3% | — |
| MATH Level 5 | 97.7% | — |
| FrontierMath (Feb 2025 set) | 15.2% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |

## Knowledge

- Claude Sonnet 4.5: 48.4 (#76)
- Llama 3.2 1B: 7.2 (#312)

| Benchmark | Claude Sonnet 4.5 | Llama 3.2 1B |
|---|---|---|
| GPQA Diamond | 82.3% | 23.9% |
| LMArena Expert | 1482 | 1007 |
| Humanity's Last Exam | 13.7% | — |
| SimpleQA Verified | 30.7% | — |
| MMLU-Pro | 86.9% | — |
| Vectara Hallucination Rate | 12% | — |
| GPQA (HELM) | 68.6% | — |

## Multimodal

- Claude Sonnet 4.5: 34.8 (#89)
- Llama 3.2 1B: —

| Benchmark | Claude Sonnet 4.5 | Llama 3.2 1B |
|---|---|---|
| VPCT | 39.8% | — |
| LMArena Document | 1450 | — |

## Multilingual

- Claude Sonnet 4.5: 53.4 (#69)
- Llama 3.2 1B: 23.8 (#292)

| Benchmark | Claude Sonnet 4.5 | Llama 3.2 1B |
|---|---|---|
| LMArena Non-English | 1425 | 973 |
| LMArena Chinese | 1459 | 959 |
| LMArena German | 1427 | 1014 |
| LMArena Russian | 1437 | 941 |
| LMArena French | 1458 | — |
| LMArena Japanese | 1390 | — |
| LMArena Korean | 1403 | — |
| LMArena Spanish | 1457 | — |

## Instruction Following

- Claude Sonnet 4.5: 75.0 (#78)
- Llama 3.2 1B: 52.4 (#290)

| Benchmark | Claude Sonnet 4.5 | Llama 3.2 1B |
|---|---|---|
| LMArena Instruction Following | 1459 | 1031 |
| IFEval | 85% | — |

## Long Context

- Claude Sonnet 4.5: 45.2 (#46)
- Llama 3.2 1B: 31.9 (#274)

| Benchmark | Claude Sonnet 4.5 | Llama 3.2 1B |
|---|---|---|
| LMArena Longer Query | 1476 | 1050 |

## Writing & Preference

- Claude Sonnet 4.5: 66.5 (#34)
- Llama 3.2 1B: 21.3 (#310)

| Benchmark | Claude Sonnet 4.5 | Llama 3.2 1B |
|---|---|---|
| LMArena Text | 1439 | 1055 |
| LMArena Creative Writing | 1442 | 1033 |
| EQ-Bench Creative Writing | 1678 | 200 |
| LMArena Multi-Turn | 1465 | 1030 |
| WildBench | 85.4% | — |

## FAQ

### Is Claude Sonnet 4.5 better than Llama 3.2 1B?

Claude Sonnet 4.5 is the stronger model overall, scoring 44.1 to 20.1 on the Noometry Index. Llama 3.2 1B costs 85× less per token, which makes it the better buy when Claude Sonnet 4.5's lead doesn't matter for your workload.

### Which is cheaper, Claude Sonnet 4.5 or Llama 3.2 1B?

Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; Claude Sonnet 4.5 lists at $3 and $15.

### Is Claude Sonnet 4.5 or Llama 3.2 1B better for coding?

Claude Sonnet 4.5 scores higher on coding benchmarks: 47.3 versus 21.1 in the Noometry coding category.

### Which has the bigger context window?

Claude Sonnet 4.5 does, with 200K tokens against 60K.

### How many benchmarks do Claude Sonnet 4.5 and Llama 3.2 1B share?

19 benchmarks have published results for both models. Claude Sonnet 4.5 has 73 scored results on Noometry and Llama 3.2 1B has 22.