Model comparison
GPT-5.5 Instant vs Qwen3-Coder 480B-A35B Instruct
GPT-5.5 Instant is the stronger model overall, scoring 42.7 to 38.1 on the Noometry Index.
Last verified . 17 shared benchmarks.
Alibaba (Qwen)Summary
- They share 17 benchmarks with published results for both. GPT-5.5 Instant scores higher in 6 categories and Qwen3-Coder 480B-A35B Instruct in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5.5 Instant leads 48.9 to 37.0.
- Qwen3-Coder 480B-A35B Instruct has downloadable open weights; the other is API-only.
Side by side
| GPT-5.5 Instant | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | OpenAI | Alibaba (Qwen) |
| Noometry Index | 42.7 | 38.1 |
| Released | 2026-05-05 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | — | 262K |
| Max output | — | 66K |
| Input $ / M tokens | — | $1.50 |
| Output $ / M tokens | — | $7.50 |
| Results tracked | 27 | 25 |
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Category by category
Coding GPT-5.5 Instant leads
GPT-5.5 Instant: 44.3 (#74), Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)
| Benchmark | GPT-5.5 Instant | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Coding | 1433 | 1412 |
| SWE-bench Verified (bash only) | — | 55.4% |
| LMArena WebDev | — | 1275 |
| SciCode | 48.6% | — |
| GSO | — | 4.9% |
| WeirdML | — | 41.2% |
| ALE-Bench | — | 461.45 |
| AlgoTune | — | 1.44 |
Agentic & Tool Use Not comparable
GPT-5.5 Instant: —, Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)
| Benchmark | GPT-5.5 Instant | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
Reasoning Too close to call
GPT-5.5 Instant: 24.9 (#155), Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)
| Benchmark | GPT-5.5 Instant | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1426 | 1372 |
| Kagi LLM Benchmark | — | 49.5% |
| CritPt | 0% | — |
| Chess Puzzles | 12% | — |
| Epoch Capabilities Index | 142.52 | — |
Math Qwen3-Coder 480B-A35B Instruct leads
GPT-5.5 Instant: 26.5 (#259), Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)
| Benchmark | GPT-5.5 Instant | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | 1420 | 1365 |
| FrontierMath (Tiers 1-3) | 26.3% | — |
| FrontierMath Tier 4 | 2.4% | — |
| OTIS Mock AIME 2024-2025 | 68.1% | — |
Knowledge GPT-5.5 Instant leads
GPT-5.5 Instant: 48.9 (#74), Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)
| Benchmark | GPT-5.5 Instant | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1409 | 1338 |
| GPQA Diamond | 82.5% | — |
Multimodal Not comparable
GPT-5.5 Instant: 40.0 (#52), Qwen3-Coder 480B-A35B Instruct: —
| Benchmark | GPT-5.5 Instant | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Vision | 1250 | — |
| LMArena Document | 1403 | — |
Multilingual GPT-5.5 Instant leads
GPT-5.5 Instant: 52.8 (#80), Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)
| Benchmark | GPT-5.5 Instant | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1417 | 1346 |
| LMArena Chinese | 1456 | 1357 |
| LMArena French | 1428 | 1398 |
| LMArena German | 1411 | 1325 |
| LMArena Japanese | 1408 | 1310 |
| LMArena Korean | 1392 | 1305 |
| LMArena Russian | 1431 | 1366 |
| LMArena Spanish | 1429 | 1360 |
Instruction Following GPT-5.5 Instant leads
GPT-5.5 Instant: 74.2 (#100), Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)
| Benchmark | GPT-5.5 Instant | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1406 | 1355 |
Long Context GPT-5.5 Instant leads
GPT-5.5 Instant: 43.4 (#96), Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)
| Benchmark | GPT-5.5 Instant | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1422 | 1378 |
Writing & Preference GPT-5.5 Instant leads
GPT-5.5 Instant: 61.8 (#85), Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)
| Benchmark | GPT-5.5 Instant | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1419 | 1357 |
| LMArena Creative Writing | 1419 | 1333 |
| LMArena Multi-Turn | 1433 | 1365 |
Frequently asked questions
Is GPT-5.5 Instant better than Qwen3-Coder 480B-A35B Instruct?
GPT-5.5 Instant is the stronger model overall, scoring 42.7 to 38.1 on the Noometry Index.
Is GPT-5.5 Instant or Qwen3-Coder 480B-A35B Instruct better for coding?
GPT-5.5 Instant scores higher on coding benchmarks: 44.3 versus 35.5 in the Noometry coding category.
How many benchmarks do GPT-5.5 Instant and Qwen3-Coder 480B-A35B Instruct share?
17 benchmarks have published results for both models. GPT-5.5 Instant has 27 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.