Model comparison
GPT-6 Sol vs Qwen1.5-14B
GPT-6 Sol is the stronger model overall, scoring 49.2 to 32.1 on the Noometry Index.
Last verified . 13 shared benchmarks.
Alibaba (Qwen)Summary
- They share 13 benchmarks with published results for both. GPT-6 Sol scores higher in 8 categories and Qwen1.5-14B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GPT-6 Sol leads 72.3 to 33.7.
- Qwen1.5-14B has downloadable open weights; the other is API-only.
Side by side
| GPT-6 Sol | Qwen1.5-14B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 49.2 | 32.1 |
| Released | 2026-09-22 | 2024-02-04 |
| Weights | Proprietary | Open |
| Context window | 1.05M | — |
| Max output | 128K | — |
| Input $ / M tokens | $2 | — |
| Output $ / M tokens | $10 | — |
| Results tracked | 22 | 17 |
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Category by category
Coding GPT-6 Sol leads
GPT-6 Sol: 59.6 (#11), Qwen1.5-14B: 32.5 (#259)
| Benchmark | GPT-6 Sol | Qwen1.5-14B |
|---|---|---|
| LMArena Coding | 1453 | 1138 |
| DeepSWE | 68.8% | — |
| FrontierCode | 49.3% | — |
| LMArena WebDev | 1692 | — |
Agentic & Tool Use Not comparable
GPT-6 Sol: 33.5 (#49), Qwen1.5-14B: —
| Benchmark | GPT-6 Sol | Qwen1.5-14B |
|---|---|---|
| GDP.pdf | 28% | — |
Reasoning GPT-6 Sol leads
GPT-6 Sol: 49.3 (#34), Qwen1.5-14B: 20.5 (#217)
| Benchmark | GPT-6 Sol | Qwen1.5-14B |
|---|---|---|
| LMArena Hard Prompts | 1420 | 1113 |
| NYT Connections (extended) | 90.1% | — |
| EBR-Bench | 53.3% | — |
Math GPT-6 Sol leads
GPT-6 Sol: 35.8 (#135), Qwen1.5-14B: 29.9 (#214)
| Benchmark | GPT-6 Sol | Qwen1.5-14B |
|---|---|---|
| LMArena Math | 1404 | 1125 |
Knowledge GPT-6 Sol leads
GPT-6 Sol: 43.0 (#87), Qwen1.5-14B: 29.3 (#230)
| Benchmark | GPT-6 Sol | Qwen1.5-14B |
|---|---|---|
| LMArena Expert | 1449 | 1094 |
| Vectara Hallucination Rate | 6.5% | — |
| MMLU | — | 68.6% |
Multimodal Not comparable
GPT-6 Sol: 47.6 (#9), Qwen1.5-14B: —
| Benchmark | GPT-6 Sol | Qwen1.5-14B |
|---|---|---|
| Furniture Assembly | 58.3% | — |
Multilingual GPT-6 Sol leads
GPT-6 Sol: 51.0 (#113), Qwen1.5-14B: 30.8 (#257)
| Benchmark | GPT-6 Sol | Qwen1.5-14B |
|---|---|---|
| LMArena Non-English | 1389 | 1095 |
| LMArena Chinese | 1416 | 1147 |
| LMArena Russian | 1407 | 1046 |
| LMArena Spanish | 1377 | 1085 |
| LMArena French | — | 1115 |
| LMArena German | — | 1043 |
| LMArena Japanese | — | 1019 |
Instruction Following GPT-6 Sol leads
GPT-6 Sol: 74.4 (#97), Qwen1.5-14B: 57.1 (#266)
| Benchmark | GPT-6 Sol | Qwen1.5-14B |
|---|---|---|
| LMArena Instruction Following | 1406 | 1102 |
Long Context GPT-6 Sol leads
GPT-6 Sol: 43.2 (#100), Qwen1.5-14B: 33.7 (#252)
| Benchmark | GPT-6 Sol | Qwen1.5-14B |
|---|---|---|
| LMArena Longer Query | 1415 | 1113 |
Writing & Preference GPT-6 Sol leads
GPT-6 Sol: 72.3 (#15), Qwen1.5-14B: 33.7 (#270)
| Benchmark | GPT-6 Sol | Qwen1.5-14B |
|---|---|---|
| LMArena Text | 1396 | 1128 |
| LMArena Creative Writing | 1392 | 1091 |
| LMArena Multi-Turn | 1405 | 1110 |
| EQ-Bench Creative Writing | 2125 | — |
Frequently asked questions
Is GPT-6 Sol better than Qwen1.5-14B?
GPT-6 Sol is the stronger model overall, scoring 49.2 to 32.1 on the Noometry Index.
Is GPT-6 Sol or Qwen1.5-14B better for coding?
GPT-6 Sol scores higher on coding benchmarks: 59.6 versus 32.5 in the Noometry coding category.
How many benchmarks do GPT-6 Sol and Qwen1.5-14B share?
13 benchmarks have published results for both models. GPT-6 Sol has 22 scored results on Noometry and Qwen1.5-14B has 17.