# Claude Sonnet 4.5 vs Qwen3 14B

> Claude Sonnet 4.5 is the stronger model overall, scoring 44.1 to 35.5 on the Noometry Index. Qwen3 14B costs 9.8× 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-qwen3-14b
- Last updated: 2026-10-10
- Shared benchmarks: 11

## Summary

- They share 11 benchmarks with published results for both. Claude Sonnet 4.5 scores higher in 5 categories and Qwen3 14B in 1 category; 6 gaps are clear of the uncertainty.
- The widest gap is in coding, where Claude Sonnet 4.5 leads 47.3 to 37.3.
- The biggest single-benchmark swing is Berkeley Function Calling Leaderboard: 73.2% for Claude Sonnet 4.5 and 41% for Qwen3 14B.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.5.
- Claude Sonnet 4.5 accepts more context: 200K tokens versus 131K.
- Qwen3 14B has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Sonnet 4.5 | Qwen3 14B |
|---|---|---|
| Provider | Anthropic | Alibaba (Qwen) |
| Noometry Index | 44.1 | 35.5 |
| Rank | 81 | 225 |
| Context | 200K | 131K |
| Input $/M | $3 | $0.35 |
| Output $/M | $15 | $1.40 |
| Weights | Proprietary | Open |

## Coding

- Claude Sonnet 4.5: 47.3 (#61)
- Qwen3 14B: 37.3 (#195)

| Benchmark | Claude Sonnet 4.5 | Qwen3 14B |
|---|---|---|
| SciCode | 44.7% | 31.6% |
| SWE-bench Verified | 71.3% | — |
| SWE-bench Verified (bash only) | 71.4% | — |
| LMArena WebDev | 1393 | — |
| SWE-bench Multilingual | 67% | — |
| GSO | 14.7% | — |
| WeirdML | 47.7% | — |
| LMArena Coding | 1489 | — |
| ALE-Bench | 796.15 | — |
| AlgoTune | 1.52 | — |

## Agentic & Tool Use

- Claude Sonnet 4.5: 38.3 (#32)
- Qwen3 14B: 29.6 (#83)

| Benchmark | Claude Sonnet 4.5 | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 73.2% | 41% |
| 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% | — |
| LMArena Search | 1159 | — |
| METR Time Horizons | 67.4% | — |
| Vending-Bench 2 | 3,839 | — |

## Reasoning

- Claude Sonnet 4.5: 26.9 (#125)
- Qwen3 14B: 18.5 (#280)

| Benchmark | Claude Sonnet 4.5 | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | 57.9% | 49.1% |
| CritPt | 1.1% | 0% |
| Chess Puzzles | 12% | 4% |
| DTBench | 83.2% | 64% |
| LMCA | 38.8% | 18.2% |
| Epoch Capabilities Index | 146.84 | 138.23 |
| ARC-AGI-2 | 13.6% | — |
| SimpleBench | 54.3% | — |
| NYT Connections (extended) | 37.3% | — |
| ARC-AGI-1 | 63.7% | — |
| EnigmaEval | 6% | — |
| EBR-Bench | 2.4% | — |
| LMArena Hard Prompts | 1462 | — |
| Mystery Game Puzzles | 17% | — |
| ForecastBench | 61.9 | — |

## Math

- Claude Sonnet 4.5: 32.3 (#216)
- Qwen3 14B: 38.6 (#133)

| Benchmark | Claude Sonnet 4.5 | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 77.8% | 66.4% |
| FrontierMath (Tiers 1-3) | 23.9% | — |
| FrontierMath Tier 4 | 2.4% | — |
| ProofBench | 19% | — |
| Omni-MATH | 55.3% | — |
| LMArena Math | 1449 | — |
| 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)
- Qwen3 14B: 39.3 (#134)

| Benchmark | Claude Sonnet 4.5 | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 82.3% | 63.8% |
| Vectara Hallucination Rate | 12% | 5.4% |
| Humanity's Last Exam | 13.7% | — |
| SimpleQA Verified | 30.7% | — |
| MMLU-Pro | 86.9% | — |
| GPQA (HELM) | 68.6% | — |
| LMArena Expert | 1482 | — |

## Multimodal

- Claude Sonnet 4.5: 34.8 (#89)
- Qwen3 14B: —

| Benchmark | Claude Sonnet 4.5 | Qwen3 14B |
|---|---|---|
| VPCT | 39.8% | — |
| LMArena Document | 1450 | — |

## Multilingual

- Claude Sonnet 4.5: 53.4 (#69)
- Qwen3 14B: —

| Benchmark | Claude Sonnet 4.5 | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1425 | — |
| LMArena Chinese | 1459 | — |
| LMArena French | 1458 | — |
| LMArena German | 1427 | — |
| LMArena Japanese | 1390 | — |
| LMArena Korean | 1403 | — |
| LMArena Russian | 1437 | — |
| LMArena Spanish | 1457 | — |

## Instruction Following

- Claude Sonnet 4.5: 75.0 (#78)
- Qwen3 14B: —

| Benchmark | Claude Sonnet 4.5 | Qwen3 14B |
|---|---|---|
| IFEval | 85% | — |
| LMArena Instruction Following | 1459 | — |

## Long Context

- Claude Sonnet 4.5: 45.2 (#46)
- Qwen3 14B: 38.1 (#204)

| Benchmark | Claude Sonnet 4.5 | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1476 | — |

## Writing & Preference

- Claude Sonnet 4.5: 66.5 (#34)
- Qwen3 14B: —

| Benchmark | Claude Sonnet 4.5 | Qwen3 14B |
|---|---|---|
| LMArena Text | 1439 | — |
| LMArena Creative Writing | 1442 | — |
| EQ-Bench Creative Writing | 1678 | — |
| WildBench | 85.4% | — |
| LMArena Multi-Turn | 1465 | — |

## FAQ

### Is Claude Sonnet 4.5 better than Qwen3 14B?

Claude Sonnet 4.5 is the stronger model overall, scoring 44.1 to 35.5 on the Noometry Index. Qwen3 14B costs 9.8× 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 Qwen3 14B?

Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; Claude Sonnet 4.5 lists at $3 and $15.

### Is Claude Sonnet 4.5 or Qwen3 14B better for coding?

Claude Sonnet 4.5 scores higher on coding benchmarks: 47.3 versus 37.3 in the Noometry coding category.

### Which has the bigger context window?

Claude Sonnet 4.5 does, with 200K tokens against 131K.

### How many benchmarks do Claude Sonnet 4.5 and Qwen3 14B share?

11 benchmarks have published results for both models. Claude Sonnet 4.5 has 73 scored results on Noometry and Qwen3 14B has 12.