Model comparison
GPT-4.1 vs Qwen3 14B
GPT-4.1 and Qwen3 14B score almost the same on the Noometry Index (35.9 vs 35.5), so choose on price, context window or the category you care about most.
Last verified . 10 shared benchmarks.
Alibaba (Qwen)Summary
- They share 10 benchmarks with published results for both. GPT-4.1 scores higher in 2 categories and Qwen3 14B in 4 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3 14B leads 38.6 to 22.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 38.3% for GPT-4.1 and 66.4% for Qwen3 14B.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $2 / $8 for GPT-4.1.
- GPT-4.1 accepts more context: 1.05M tokens versus 131K.
- Qwen3 14B has downloadable open weights; the other is API-only.
Side by side
| GPT-4.1 | Qwen3 14B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 35.9 | 35.5 |
| Released | 2025-04-14 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 1.05M | 131K |
| Max output | 33K | 8K |
| Input $ / M tokens | $2 | $0.35 |
| Output $ / M tokens | $8 | $1.40 |
| Results tracked | 52 | 12 |
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Category by category
Coding Qwen3 14B leads
GPT-4.1: 34.4 (#238), Qwen3 14B: 37.3 (#195)
| Benchmark | GPT-4.1 | Qwen3 14B |
|---|---|---|
| SWE-bench Verified | 48.5% | — |
| SWE-bench Verified (bash only) | 39.6% | — |
| Aider Polyglot | 52.4% | — |
| SciCode | — | 31.6% |
| WeirdML | 39% | — |
| LMArena Coding | 1391 | — |
| CadEval | 42% | — |
| ALE-Bench | 558.1 | — |
Agentic & Tool Use GPT-4.1 leads
GPT-4.1: 34.7 (#43), Qwen3 14B: 29.6 (#83)
| Benchmark | GPT-4.1 | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 54% | 41% |
Reasoning Qwen3 14B leads
GPT-4.1: 11.7 (#339), Qwen3 14B: 18.5 (#280)
| Benchmark | GPT-4.1 | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | 52.3% | 49.1% |
| Chess Puzzles | 6% | 4% |
| DTBench | 68.3% | 64% |
| LMCA | 25.6% | 18.2% |
| Epoch Capabilities Index | 136.78 | 138.23 |
| ARC-AGI-2 | 0.4% | — |
| SimpleBench | 27% | — |
| ARC-AGI-1 | 5.5% | — |
| CritPt | — | 0% |
| EnigmaEval | 2.2% | — |
| LMArena Hard Prompts | 1384 | — |
| ForecastBench | 61.5 | — |
Math Qwen3 14B leads
GPT-4.1: 22.3 (#280), Qwen3 14B: 38.6 (#133)
| Benchmark | GPT-4.1 | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 38.3% | 66.4% |
| FrontierMath (Tiers 1-3) | 6% | — |
| Omni-MATH | 47.1% | — |
| LMArena Math | 1370 | — |
| MATH Level 5 | 83% | — |
| FrontierMath (Feb 2025 set) | 5.5% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Qwen3 14B leads
GPT-4.1: 37.1 (#160), Qwen3 14B: 39.3 (#134)
| Benchmark | GPT-4.1 | Qwen3 14B |
|---|---|---|
| GPQA Diamond | 66.9% | 63.8% |
| Vectara Hallucination Rate | 5.6% | 5.4% |
| Humanity's Last Exam | 5.4% | — |
| SimpleQA Verified | 31.1% | — |
| MMLU-Pro | 81.1% | — |
| GPQA (HELM) | 65.9% | — |
| LMArena Expert | 1364 | — |
Multimodal Not comparable
GPT-4.1: 38.2 (#67), Qwen3 14B: —
| Benchmark | GPT-4.1 | Qwen3 14B |
|---|---|---|
| LMArena Vision | 1211 | — |
| GeoBench | 72% | — |
Multilingual Not comparable
GPT-4.1: 49.4 (#133), Qwen3 14B: —
| Benchmark | GPT-4.1 | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1370 | — |
| LMArena Chinese | 1382 | — |
| LMArena French | 1382 | — |
| LMArena German | 1381 | — |
| LMArena Japanese | 1319 | — |
| LMArena Korean | 1339 | — |
| LMArena Russian | 1377 | — |
| LMArena Spanish | 1376 | — |
Instruction Following Not comparable
GPT-4.1: 71.3 (#153), Qwen3 14B: —
| Benchmark | GPT-4.1 | Qwen3 14B |
|---|---|---|
| IFEval | 83.8% | — |
| LMArena Instruction Following | 1367 | — |
Long Context GPT-4.1 leads
GPT-4.1: 40.0 (#163), Qwen3 14B: 38.1 (#204)
| Benchmark | GPT-4.1 | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | 63.9% | 62.5% |
| LMArena Longer Query | 1385 | — |
Writing & Preference Not comparable
GPT-4.1: 57.6 (#125), Qwen3 14B: —
| Benchmark | GPT-4.1 | Qwen3 14B |
|---|---|---|
| LMArena Text | 1383 | — |
| LMArena Creative Writing | 1363 | — |
| EQ-Bench Creative Writing | 1420 | — |
| WildBench | 85.4% | — |
| LMArena Multi-Turn | 1398 | — |
Frequently asked questions
Is GPT-4.1 better than Qwen3 14B?
GPT-4.1 and Qwen3 14B score almost the same on the Noometry Index (35.9 vs 35.5), so choose on price, context window or the category you care about most.
Which is cheaper, GPT-4.1 or Qwen3 14B?
Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; GPT-4.1 lists at $2 and $8.
Is GPT-4.1 or Qwen3 14B better for coding?
Qwen3 14B scores higher on coding benchmarks: 37.3 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 does, with 1.05M tokens against 131K.
How many benchmarks do GPT-4.1 and Qwen3 14B share?
10 benchmarks have published results for both models. GPT-4.1 has 52 scored results on Noometry and Qwen3 14B has 12.