Model comparison
Qwen3.5 397B-A17B vs Qwen3-Coder 480B-A35B Instruct
Qwen3.5 397B-A17B is the stronger model overall, scoring 46.0 to 38.1 on the Noometry Index.
Last verified . 19 shared benchmarks.
Alibaba (Qwen)Summary
- They share 19 benchmarks with published results for both. Qwen3.5 397B-A17B scores higher in 9 categories and Qwen3-Coder 480B-A35B Instruct in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3.5 397B-A17B leads 53.3 to 37.0.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 73.7% for Qwen3.5 397B-A17B and 49.5% for Qwen3-Coder 480B-A35B Instruct.
- Qwen3.5 397B-A17B is cheaper at $0.60 / $3.60 per million input/output tokens, against $1.50 / $7.50 for Qwen3-Coder 480B-A35B Instruct.
Side by side
| Qwen3.5 397B-A17B | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | Alibaba (Qwen) | Alibaba (Qwen) |
| Noometry Index | 46.0 | 38.1 |
| Released | 2026-02-01 | 2025-04 |
| Weights | Open | Open |
| Context window | 262K | 262K |
| Max output | 66K | 66K |
| Input $ / M tokens | $0.60 | $1.50 |
| Output $ / M tokens | $3.60 | $7.50 |
| Results tracked | 36 | 25 |
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Category by category
Coding Qwen3.5 397B-A17B leads
Qwen3.5 397B-A17B: 42.0 (#114), Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)
| Benchmark | Qwen3.5 397B-A17B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena WebDev | 1400 | 1275 |
| LMArena Coding | 1465 | 1412 |
| SWE-bench Verified (bash only) | — | 55.4% |
| GSO | — | 4.9% |
| WeirdML | — | 41.2% |
| ALE-Bench | — | 461.45 |
| AlgoTune | — | 1.44 |
Agentic & Tool Use Qwen3.5 397B-A17B leads
Qwen3.5 397B-A17B: 33.3 (#53), Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)
| Benchmark | Qwen3.5 397B-A17B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
| APEX-Agents | 24.9% | — |
| τ²-bench Airline | 81.5% | — |
| τ²-bench Banking | 9.8% | — |
| τ²-bench Retail | 84.4% | — |
| τ²-bench Telecom | 97.8% | — |
Reasoning Qwen3.5 397B-A17B leads
Qwen3.5 397B-A17B: 34.5 (#70), Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)
| Benchmark | Qwen3.5 397B-A17B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Kagi LLM Benchmark | 73.7% | 49.5% |
| LMArena Hard Prompts | 1448 | 1372 |
| NYT Connections (extended) | 58.9% | — |
| Chess Puzzles | 13% | — |
| Thematic Generalization | 65.1% | — |
| Mystery Game Puzzles | 18% | — |
| DTBench | 87.5% | — |
| LMCA | 37.9% | — |
| Epoch Capabilities Index | 146.65 | — |
Math Qwen3.5 397B-A17B leads
Qwen3.5 397B-A17B: 46.1 (#73), Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)
| Benchmark | Qwen3.5 397B-A17B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | 1454 | 1365 |
| FrontierMath (Tiers 1-3) | 31.2% | — |
| OTIS Mock AIME 2024-2025 | 88.9% | — |
Knowledge Qwen3.5 397B-A17B leads
Qwen3.5 397B-A17B: 53.3 (#58), Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)
| Benchmark | Qwen3.5 397B-A17B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1462 | 1338 |
| GPQA Diamond | 86.4% | — |
Multimodal Not comparable
Qwen3.5 397B-A17B: 40.7 (#44), Qwen3-Coder 480B-A35B Instruct: —
| Benchmark | Qwen3.5 397B-A17B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Vision | 1263 | — |
Multilingual Qwen3.5 397B-A17B leads
Qwen3.5 397B-A17B: 53.7 (#59), Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)
| Benchmark | Qwen3.5 397B-A17B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1430 | 1346 |
| LMArena Chinese | 1500 | 1357 |
| LMArena French | 1461 | 1398 |
| LMArena German | 1447 | 1325 |
| LMArena Japanese | 1426 | 1310 |
| LMArena Korean | 1384 | 1305 |
| LMArena Russian | 1429 | 1366 |
| LMArena Spanish | 1441 | 1360 |
Instruction Following Qwen3.5 397B-A17B leads
Qwen3.5 397B-A17B: 75.0 (#77), Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)
| Benchmark | Qwen3.5 397B-A17B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1424 | 1355 |
Long Context Qwen3.5 397B-A17B leads
Qwen3.5 397B-A17B: 44.1 (#74), Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)
| Benchmark | Qwen3.5 397B-A17B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1442 | 1378 |
Writing & Preference Qwen3.5 397B-A17B leads
Qwen3.5 397B-A17B: 62.3 (#79), Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)
| Benchmark | Qwen3.5 397B-A17B | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1438 | 1357 |
| LMArena Creative Writing | 1401 | 1333 |
| LMArena Multi-Turn | 1446 | 1365 |
| EQ-Bench Creative Writing | 1478 | — |
Frequently asked questions
Is Qwen3.5 397B-A17B better than Qwen3-Coder 480B-A35B Instruct?
Qwen3.5 397B-A17B is the stronger model overall, scoring 46.0 to 38.1 on the Noometry Index.
Which is cheaper, Qwen3.5 397B-A17B or Qwen3-Coder 480B-A35B Instruct?
Qwen3.5 397B-A17B is cheaper. It lists at $0.60 per million input tokens and $3.60 per million output tokens; Qwen3-Coder 480B-A35B Instruct lists at $1.50 and $7.50.
Is Qwen3.5 397B-A17B or Qwen3-Coder 480B-A35B Instruct better for coding?
Qwen3.5 397B-A17B scores higher on coding benchmarks: 42.0 versus 35.5 in the Noometry coding category.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do Qwen3.5 397B-A17B and Qwen3-Coder 480B-A35B Instruct share?
19 benchmarks have published results for both models. Qwen3.5 397B-A17B has 36 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.