Model comparison
Claude Haiku 4.5 vs Qwen3 14B
Claude Haiku 4.5 is the stronger model overall, scoring 39.5 to 35.5 on the Noometry Index. Qwen3 14B costs 3.3× less per token, which makes it the better buy when Claude Haiku 4.5's lead doesn't matter for your workload.
Last verified . 10 shared benchmarks.
Alibaba (Qwen)Summary
- They share 10 benchmarks with published results for both. Claude Haiku 4.5 scores higher in 4 categories and Qwen3 14B in 2 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in coding, where Claude Haiku 4.5 leads 44.0 to 37.3.
- The biggest single-benchmark swing is Berkeley Function Calling Leaderboard: 68.7% for Claude Haiku 4.5 and 41% for Qwen3 14B.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $1 / $5 for Claude Haiku 4.5.
- Claude Haiku 4.5 accepts more context: 200K tokens versus 131K.
- Qwen3 14B has downloadable open weights; the other is API-only.
Side by side
| Claude Haiku 4.5 | Qwen3 14B | |
|---|---|---|
| Provider | Anthropic | Alibaba (Qwen) |
| Noometry Index | 39.5 | 35.5 |
| Released | 2025-10-15 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 200K | 131K |
| Max output | 64K | 8K |
| Input $ / M tokens | $1 | $0.35 |
| Output $ / M tokens | $5 | $1.40 |
| Results tracked | 53 | 12 |
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Category by category
Coding Claude Haiku 4.5 leads
Claude Haiku 4.5: 44.0 (#78), Qwen3 14B: 37.3 (#195)
| Benchmark | Claude Haiku 4.5 | Qwen3 14B |
|---|---|---|
| SciCode | 43.3% | 31.6% |
| SWE-bench Verified (bash only) | 66.6% | — |
| LMArena WebDev | 1330 | — |
| SWE-bench Multilingual | 64.7% | — |
| WeirdML | 45.4% | — |
| LMArena Coding | 1453 | — |
| ALE-Bench | 653.48 | — |
Agentic & Tool Use Claude Haiku 4.5 leads
Claude Haiku 4.5: 33.6 (#52), Qwen3 14B: 29.6 (#83)
| Benchmark | Claude Haiku 4.5 | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 68.7% | 41% |
| Terminal-Bench | 35.5% | — |
| DeepResearch Bench | 45.5% | — |
| BALROG | 31.2% | — |
| ExploitBench | 13.7% | — |
| Vending-Bench 2 | 458.89 | — |
Reasoning Qwen3 14B leads
Claude Haiku 4.5: 15.1 (#320), Qwen3 14B: 18.5 (#280)
| Benchmark | Claude Haiku 4.5 | Qwen3 14B |
|---|---|---|
| CritPt | 0% | 0% |
| Chess Puzzles | 8% | 4% |
| DTBench | 73.6% | 64% |
| LMCA | 30.9% | 18.2% |
| Epoch Capabilities Index | 142.41 | 138.23 |
| ARC-AGI-2 | 4% | — |
| Kagi LLM Benchmark | — | 49.1% |
| NYT Connections (extended) | 14.3% | — |
| ARC-AGI-1 | 47.7% | — |
| LMArena Hard Prompts | 1420 | — |
| ForecastBench | 61.4 | — |
Math Claude Haiku 4.5 leads
Claude Haiku 4.5: 44.9 (#78), Qwen3 14B: 38.6 (#133)
| Benchmark | Claude Haiku 4.5 | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.7% | 66.4% |
| Omni-MATH | 56.1% | — |
| LMArena Math | 1396 | — |
| MATH Level 5 | 96.4% | — |
| FrontierMath (Feb 2025 set) | 5.9% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Qwen3 14B leads
Claude Haiku 4.5: 37.7 (#153), Qwen3 14B: 39.3 (#134)
| Benchmark | Claude Haiku 4.5 | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 71.2% | 63.8% |
| Vectara Hallucination Rate | 9.8% | 5.4% |
| SimpleQA Verified | 13.2% | — |
| MMLU-Pro | 77.7% | — |
| GPQA (HELM) | 60.5% | — |
| LMArena Expert | 1442 | — |
Multimodal Not comparable
Claude Haiku 4.5: 26.8 (#118), Qwen3 14B: —
| Benchmark | Claude Haiku 4.5 | Qwen3 14B |
|---|---|---|
| Blueprint-Bench 2 | 0% | — |
| LMArena Document | 1420 | — |
Multilingual Not comparable
Claude Haiku 4.5: 49.9 (#129), Qwen3 14B: —
| Benchmark | Claude Haiku 4.5 | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1377 | — |
| LMArena Chinese | 1417 | — |
| LMArena French | 1408 | — |
| LMArena German | 1375 | — |
| LMArena Japanese | 1339 | — |
| LMArena Korean | 1347 | — |
| LMArena Russian | 1381 | — |
| LMArena Spanish | 1420 | — |
Instruction Following Not comparable
Claude Haiku 4.5: 71.4 (#149), Qwen3 14B: —
| Benchmark | Claude Haiku 4.5 | Qwen3 14B |
|---|---|---|
| IFEval | 80.1% | — |
| LMArena Instruction Following | 1414 | — |
Long Context Claude Haiku 4.5 leads
Claude Haiku 4.5: 43.6 (#92), Qwen3 14B: 38.1 (#204)
| Benchmark | Claude Haiku 4.5 | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1427 | — |
Writing & Preference Not comparable
Claude Haiku 4.5: 57.9 (#123), Qwen3 14B: —
| Benchmark | Claude Haiku 4.5 | Qwen3 14B |
|---|---|---|
| LMArena Text | 1396 | — |
| LMArena Creative Writing | 1372 | — |
| WildBench | 83.9% | — |
| EQ-Bench 4 | 1064 | — |
| LMArena Multi-Turn | 1409 | — |
Frequently asked questions
Is Claude Haiku 4.5 better than Qwen3 14B?
Claude Haiku 4.5 is the stronger model overall, scoring 39.5 to 35.5 on the Noometry Index. Qwen3 14B costs 3.3× less per token, which makes it the better buy when Claude Haiku 4.5's lead doesn't matter for your workload.
Which is cheaper, Claude Haiku 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 Haiku 4.5 lists at $1 and $5.
Is Claude Haiku 4.5 or Qwen3 14B better for coding?
Claude Haiku 4.5 scores higher on coding benchmarks: 44.0 versus 37.3 in the Noometry coding category.
Which has the bigger context window?
Claude Haiku 4.5 does, with 200K tokens against 131K.
How many benchmarks do Claude Haiku 4.5 and Qwen3 14B share?
10 benchmarks have published results for both models. Claude Haiku 4.5 has 53 scored results on Noometry and Qwen3 14B has 12.