Model comparison
GPT-5.1-Codex vs Qwen1.5-110B
GPT-5.1-Codex is the stronger model overall, scoring 38.6 to 34.2 on the Noometry Index.
Last verified . 0 shared benchmarks.
Summary
- The widest gap is in coding, where GPT-5.1-Codex leads 41.9 to 33.0.
- Qwen1.5-110B has downloadable open weights; the other is API-only.
Side by side
| GPT-5.1-Codex | Qwen1.5-110B | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 38.6 | 34.2 |
| Released | 2025-11-12 | 2024-04-25 |
| Weights | Proprietary | Open |
| Context window | 400K | — |
| Max output | 128K | — |
| Input $ / M tokens | $1.25 | — |
| Output $ / M tokens | $10 | — |
| Results tracked | 6 | 20 |
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Category by category
Coding GPT-5.1-Codex leads
GPT-5.1-Codex: 41.9 (#116), Qwen1.5-110B: 33.0 (#264)
| Benchmark | GPT-5.1-Codex | Qwen1.5-110B |
|---|---|---|
| SWE-bench Verified (bash only) | 66% | — |
| LMArena WebDev | 1337 | — |
| BigCodeBench Instruct | — | 35% |
| LMArena Coding | — | 1184 |
| BigCodeBench Complete | — | 44.4% |
| ALE-Bench | 1,245 | — |
Agentic & Tool Use Not comparable
GPT-5.1-Codex: 38.0 (#33), Qwen1.5-110B: —
| Benchmark | GPT-5.1-Codex | Qwen1.5-110B |
|---|---|---|
| Terminal-Bench | 60.4% | — |
| METR Time Horizons | 70.8% | — |
Reasoning Not comparable
GPT-5.1-Codex: —, Qwen1.5-110B: 22.7 (#189)
| Benchmark | GPT-5.1-Codex | Qwen1.5-110B |
|---|---|---|
| LMArena Hard Prompts | — | 1168 |
| ForecastBench | — | 57.7 |
Math Qwen1.5-110B leads
GPT-5.1-Codex: 30.3 (#235), Qwen1.5-110B: 33.7 (#201)
| Benchmark | GPT-5.1-Codex | Qwen1.5-110B |
|---|---|---|
| ProofBench | 9% | — |
| LMArena Math | — | 1185 |
Knowledge Not comparable
GPT-5.1-Codex: —, Qwen1.5-110B: 31.2 (#219)
| Benchmark | GPT-5.1-Codex | Qwen1.5-110B |
|---|---|---|
| LMArena Expert | — | 1144 |
Multilingual Not comparable
GPT-5.1-Codex: —, Qwen1.5-110B: 33.6 (#250)
| Benchmark | GPT-5.1-Codex | Qwen1.5-110B |
|---|---|---|
| LMArena Non-English | — | 1142 |
| LMArena Chinese | — | 1206 |
| LMArena French | — | 1151 |
| LMArena German | — | 1123 |
| LMArena Japanese | — | 1074 |
| LMArena Korean | — | 1044 |
| LMArena Russian | — | 1118 |
| LMArena Spanish | — | 1142 |
Instruction Following Not comparable
GPT-5.1-Codex: —, Qwen1.5-110B: 60.3 (#252)
| Benchmark | GPT-5.1-Codex | Qwen1.5-110B |
|---|---|---|
| LMArena Instruction Following | — | 1158 |
Long Context Not comparable
GPT-5.1-Codex: —, Qwen1.5-110B: 35.1 (#242)
| Benchmark | GPT-5.1-Codex | Qwen1.5-110B |
|---|---|---|
| LMArena Longer Query | — | 1157 |
Writing & Preference Not comparable
GPT-5.1-Codex: —, Qwen1.5-110B: 38.0 (#255)
| Benchmark | GPT-5.1-Codex | Qwen1.5-110B |
|---|---|---|
| LMArena Text | — | 1175 |
| LMArena Creative Writing | — | 1148 |
| LMArena Multi-Turn | — | 1160 |
Frequently asked questions
Is GPT-5.1-Codex better than Qwen1.5-110B?
GPT-5.1-Codex is the stronger model overall, scoring 38.6 to 34.2 on the Noometry Index.
Is GPT-5.1-Codex or Qwen1.5-110B better for coding?
GPT-5.1-Codex scores higher on coding benchmarks: 41.9 versus 33.0 in the Noometry coding category.
How many benchmarks do GPT-5.1-Codex and Qwen1.5-110B share?
0 benchmarks have published results for both models. GPT-5.1-Codex has 6 scored results on Noometry and Qwen1.5-110B has 20.