Model comparison
GPT-5 Nano vs Qwen1.5-14B
GPT-5 Nano and Qwen1.5-14B score almost the same on the Noometry Index (33.5 vs 32.7), so choose on price, context window or the category you care about most.
Last verified . 15 shared benchmarks.
Alibaba (Qwen)Summary
- They share 15 benchmarks with published results for both. GPT-5 Nano scores higher in 5 categories and Qwen1.5-14B in 3 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in instruction following, where GPT-5 Nano leads 75.0 to 56.8.
- Qwen1.5-14B has downloadable open weights; the other is API-only.
Side by side
| GPT-5 Nano | Qwen1.5-14B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 33.5 | 32.7 |
| Released | 2025-08-07 | 2024-02-04 |
| Weights | Proprietary | Open |
| Context window | 400K | — |
| Max output | 128K | — |
| Input $ / M tokens | $0.05 | — |
| Output $ / M tokens | $0.40 | — |
| Results tracked | 49 | 17 |
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Category by category
Coding Too close to call
GPT-5 Nano: 33.6 (#254), Qwen1.5-14B: 33.1 (#263)
| Benchmark | GPT-5 Nano | Qwen1.5-14B |
|---|---|---|
| LMArena Coding | 1351 | 1138 |
| SWE-bench Verified (bash only) | 34.8% | — |
| WeirdML | 38.1% | — |
| ALE-Bench | 718.67 | — |
Agentic & Tool Use Not comparable
GPT-5 Nano: 25.8 (#106), Qwen1.5-14B: —
| Benchmark | GPT-5 Nano | Qwen1.5-14B |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| Berkeley Function Calling Leaderboard | 51.5% | — |
Reasoning Qwen1.5-14B leads
GPT-5 Nano: 16.3 (#306), Qwen1.5-14B: 21.4 (#223)
| Benchmark | GPT-5 Nano | Qwen1.5-14B |
|---|---|---|
| LMArena Hard Prompts | 1328 | 1113 |
| ARC-AGI-2 | 2.6% | — |
| Kagi LLM Benchmark | 62.2% | — |
| ARC-AGI-1 | 20.7% | — |
| Chess Puzzles | 27% | — |
| Mystery Game Puzzles | 9% | — |
| DTBench | 62.7% | — |
| LMCA | 7.9% | — |
| Epoch Capabilities Index | 139.38 | — |
| ForecastBench | 59.1 | — |
Math Qwen1.5-14B leads
GPT-5 Nano: 29.4 (#241), Qwen1.5-14B: 32.4 (#215)
| Benchmark | GPT-5 Nano | Qwen1.5-14B |
|---|---|---|
| LMArena Math | 1317 | 1125 |
| FrontierMath (Tiers 1-3) | 20% | — |
| FrontierMath Tier 4 | 2.4% | — |
| OTIS Mock AIME 2024-2025 | 81.1% | — |
| ProofBench | 12% | — |
| Omni-MATH | 54.6% | — |
| MATH Level 5 | 95.2% | — |
| FrontierMath (Feb 2025 set) | 8.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GPT-5 Nano leads
GPT-5 Nano: 35.9 (#178), Qwen1.5-14B: 29.8 (#232)
| Benchmark | GPT-5 Nano | Qwen1.5-14B |
|---|---|---|
| LMArena Expert | 1321 | 1094 |
| GPQA Diamond | 69.4% | — |
| SimpleQA Verified | 11.7% | — |
| MMLU-Pro | 77.8% | — |
| Vectara Hallucination Rate | 10.5% | — |
| GPQA (HELM) | 67.9% | — |
| MMLU | — | 68.6% |
Multimodal Not comparable
GPT-5 Nano: 31.3 (#108), Qwen1.5-14B: —
| Benchmark | GPT-5 Nano | Qwen1.5-14B |
|---|---|---|
| LMArena Vision | 1159 | — |
| VPCT | 37.2% | — |
Multilingual GPT-5 Nano leads
GPT-5 Nano: 45.3 (#172), Qwen1.5-14B: 30.7 (#262)
| Benchmark | GPT-5 Nano | Qwen1.5-14B |
|---|---|---|
| LMArena Non-English | 1313 | 1095 |
| LMArena Chinese | 1356 | 1147 |
| LMArena German | 1327 | 1043 |
| LMArena Japanese | 1226 | 1019 |
| LMArena Russian | 1296 | 1046 |
| LMArena Spanish | 1360 | 1085 |
| LMArena French | — | 1116 |
| LMArena Korean | 1269 | — |
Instruction Following GPT-5 Nano leads
GPT-5 Nano: 75.0 (#79), Qwen1.5-14B: 56.8 (#271)
| Benchmark | GPT-5 Nano | Qwen1.5-14B |
|---|---|---|
| LMArena Instruction Following | 1306 | 1102 |
| IFEval | 93.2% | — |
Long Context Qwen1.5-14B leads
GPT-5 Nano: 31.3 (#281), Qwen1.5-14B: 33.7 (#257)
| Benchmark | GPT-5 Nano | Qwen1.5-14B |
|---|---|---|
| LMArena Longer Query | 1312 | 1113 |
| Fiction.LiveBench | 44.4% | — |
Writing & Preference GPT-5 Nano leads
GPT-5 Nano: 39.1 (#249), Qwen1.5-14B: 33.6 (#276)
| Benchmark | GPT-5 Nano | Qwen1.5-14B |
|---|---|---|
| LMArena Text | 1320 | 1128 |
| LMArena Creative Writing | 1249 | 1091 |
| LMArena Multi-Turn | 1311 | 1110 |
| EQ-Bench Creative Writing | 705 | — |
| WildBench | 80.6% | — |
Frequently asked questions
Is GPT-5 Nano better than Qwen1.5-14B?
GPT-5 Nano and Qwen1.5-14B score almost the same on the Noometry Index (33.5 vs 32.7), so choose on price, context window or the category you care about most.
Is GPT-5 Nano or Qwen1.5-14B better for coding?
They score almost the same on coding (33.6 vs 33.1); test both on your own repository before choosing.
How many benchmarks do GPT-5 Nano and Qwen1.5-14B share?
15 benchmarks have published results for both models. GPT-5 Nano has 49 scored results on Noometry and Qwen1.5-14B has 17.