Model comparison
GLM-4.6V vs Qwen3-Coder 480B-A35B Instruct
GLM-4.6V is the stronger model overall, scoring 41.3 to 38.1 on the Noometry Index.
Last verified . 11 shared benchmarks.
Alibaba (Qwen)Summary
- They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 5 categories and Qwen3-Coder 480B-A35B Instruct in 2 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-4.6V leads 40.9 to 35.5.
- GLM-4.6V is cheaper at $0.30 / $0.90 per million input/output tokens, against $1.50 / $7.50 for Qwen3-Coder 480B-A35B Instruct.
- Qwen3-Coder 480B-A35B Instruct accepts more context: 262K tokens versus 128K.
Side by side
| GLM-4.6V | Qwen3-Coder 480B-A35B Instruct | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 41.3 | 38.1 |
| Released | 2025-12-08 | 2025-04 |
| Weights | Open | Open |
| Context window | 128K | 262K |
| Max output | 33K | 66K |
| Input $ / M tokens | $0.30 | $1.50 |
| Output $ / M tokens | $0.90 | $7.50 |
| Results tracked | 12 | 25 |
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Category by category
Coding GLM-4.6V leads
GLM-4.6V: 40.9 (#128), Qwen3-Coder 480B-A35B Instruct: 35.5 (#223)
| Benchmark | GLM-4.6V | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Coding | 1390 | 1412 |
| SWE-bench Verified (bash only) | — | 55.4% |
| LMArena WebDev | — | 1275 |
| GSO | — | 4.9% |
| WeirdML | — | 41.2% |
| ALE-Bench | — | 461.45 |
| AlgoTune | — | 1.44 |
Agentic & Tool Use Not comparable
GLM-4.6V: —, Qwen3-Coder 480B-A35B Instruct: 23.9 (#123)
| Benchmark | GLM-4.6V | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| Terminal-Bench | — | 27.2% |
Reasoning GLM-4.6V leads
GLM-4.6V: 27.6 (#115), Qwen3-Coder 480B-A35B Instruct: 25.5 (#149)
| Benchmark | GLM-4.6V | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Hard Prompts | 1368 | 1372 |
| Kagi LLM Benchmark | — | 49.5% |
Math Not comparable
GLM-4.6V: —, Qwen3-Coder 480B-A35B Instruct: 37.6 (#150)
| Benchmark | GLM-4.6V | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Math | — | 1365 |
Knowledge GLM-4.6V leads
GLM-4.6V: 38.0 (#149), Qwen3-Coder 480B-A35B Instruct: 37.0 (#162)
| Benchmark | GLM-4.6V | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Expert | 1371 | 1338 |
Multimodal Not comparable
GLM-4.6V: 34.8 (#90), Qwen3-Coder 480B-A35B Instruct: —
| Benchmark | GLM-4.6V | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Vision | 1164 | — |
Multilingual Too close to call
GLM-4.6V: 48.6 (#141), Qwen3-Coder 480B-A35B Instruct: 47.7 (#148)
| Benchmark | GLM-4.6V | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Non-English | 1359 | 1346 |
| LMArena Chinese | 1425 | 1357 |
| LMArena Russian | 1340 | 1366 |
| LMArena French | — | 1398 |
| LMArena German | — | 1325 |
| LMArena Japanese | — | 1310 |
| LMArena Korean | — | 1305 |
| LMArena Spanish | — | 1360 |
Instruction Following Too close to call
GLM-4.6V: 71.4 (#151), Qwen3-Coder 480B-A35B Instruct: 71.6 (#147)
| Benchmark | GLM-4.6V | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Instruction Following | 1352 | 1355 |
Long Context Too close to call
GLM-4.6V: 41.3 (#143), Qwen3-Coder 480B-A35B Instruct: 42.0 (#131)
| Benchmark | GLM-4.6V | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Longer Query | 1358 | 1378 |
Writing & Preference GLM-4.6V leads
GLM-4.6V: 56.6 (#137), Qwen3-Coder 480B-A35B Instruct: 55.3 (#147)
| Benchmark | GLM-4.6V | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|
| LMArena Text | 1377 | 1357 |
| LMArena Creative Writing | 1347 | 1333 |
| LMArena Multi-Turn | 1360 | 1365 |
Frequently asked questions
Is GLM-4.6V better than Qwen3-Coder 480B-A35B Instruct?
GLM-4.6V is the stronger model overall, scoring 41.3 to 38.1 on the Noometry Index.
Which is cheaper, GLM-4.6V or Qwen3-Coder 480B-A35B Instruct?
GLM-4.6V is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; Qwen3-Coder 480B-A35B Instruct lists at $1.50 and $7.50.
Is GLM-4.6V or Qwen3-Coder 480B-A35B Instruct better for coding?
GLM-4.6V scores higher on coding benchmarks: 40.9 versus 35.5 in the Noometry coding category.
Which has the bigger context window?
Qwen3-Coder 480B-A35B Instruct does, with 262K tokens against 128K.
How many benchmarks do GLM-4.6V and Qwen3-Coder 480B-A35B Instruct share?
11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Qwen3-Coder 480B-A35B Instruct has 25.