Model comparison
GLM-4.6 vs Qwen3.5 122B-A10B
GLM-4.6 and Qwen3.5 122B-A10B score almost the same on the Noometry Index (41.4 vs 42.1), so choose on price, context window or the category you care about most.
Last verified . 21 shared benchmarks.
Alibaba (Qwen)Summary
- They share 21 benchmarks with published results for both. GLM-4.6 scores higher in 6 categories and Qwen3.5 122B-A10B in 2 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.5 122B-A10B leads 27.2 to 23.7.
- GLM-4.6 is cheaper at $0.60 / $2.20 per million input/output tokens, against $0.40 / $3.20 for Qwen3.5 122B-A10B.
- Qwen3.5 122B-A10B accepts more context: 262K tokens versus 205K.
Side by side
| GLM-4.6 | Qwen3.5 122B-A10B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 41.4 | 42.1 |
| Released | 2025-09-30 | 2026-02-23 |
| Weights | Open | Open |
| Context window | 205K | 262K |
| Max output | 131K | 66K |
| Input $ / M tokens | $0.60 | $0.40 |
| Output $ / M tokens | $2.20 | $3.20 |
| Results tracked | 29 | 27 |
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Category by category
Coding Too close to call
GLM-4.6: 40.1 (#148), Qwen3.5 122B-A10B: 39.1 (#162)
| Benchmark | GLM-4.6 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena WebDev | 1340 | 1360 |
| SciCode | 38.4% | 35.6% |
| LMArena Coding | 1449 | 1436 |
| SWE-bench Verified (bash only) | 55.4% | — |
| ALE-Bench | 340.82 | — |
Agentic & Tool Use Not comparable
GLM-4.6: 32.3 (#66), Qwen3.5 122B-A10B: —
| Benchmark | GLM-4.6 | Qwen3.5 122B-A10B |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |
Reasoning Qwen3.5 122B-A10B leads
GLM-4.6: 23.7 (#172), Qwen3.5 122B-A10B: 27.2 (#123)
| Benchmark | GLM-4.6 | Qwen3.5 122B-A10B |
|---|---|---|
| CritPt | 1.1% | 0.9% |
| LMArena Hard Prompts | 1440 | 1421 |
| Kagi LLM Benchmark | 47.4% | — |
| NYT Connections (extended) | — | 51.7% |
| Thematic Generalization | — | 51.2% |
| Mystery Game Puzzles | — | 17% |
| DTBench | — | 84.3% |
| LMCA | — | 32.2% |
Math Too close to call
GLM-4.6: 39.1 (#111), Qwen3.5 122B-A10B: 39.1 (#112)
| Benchmark | GLM-4.6 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Math | 1432 | 1432 |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GLM-4.6 leads
GLM-4.6: 40.2 (#124), Qwen3.5 122B-A10B: 38.8 (#142)
| Benchmark | GLM-4.6 | Qwen3.5 122B-A10B |
|---|---|---|
| Vectara Hallucination Rate | 9.5% | 11.2% |
| LMArena Expert | 1431 | 1432 |
Multimodal Not comparable
GLM-4.6: —, Qwen3.5 122B-A10B: 39.6 (#57)
| Benchmark | GLM-4.6 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Vision | — | 1245 |
Multilingual GLM-4.6 leads
GLM-4.6: 53.5 (#66), Qwen3.5 122B-A10B: 51.6 (#107)
| Benchmark | GLM-4.6 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Non-English | 1426 | 1400 |
| LMArena Chinese | 1499 | 1462 |
| LMArena French | 1459 | 1442 |
| LMArena German | 1447 | 1426 |
| LMArena Japanese | 1393 | 1367 |
| LMArena Korean | 1400 | 1352 |
| LMArena Russian | 1419 | 1400 |
| LMArena Spanish | 1436 | 1424 |
Instruction Following Too close to call
GLM-4.6: 74.3 (#98), Qwen3.5 122B-A10B: 73.8 (#115)
| Benchmark | GLM-4.6 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Instruction Following | 1410 | 1399 |
Long Context Too close to call
GLM-4.6: 43.4 (#94), Qwen3.5 122B-A10B: 43.0 (#109)
| Benchmark | GLM-4.6 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Longer Query | 1422 | 1410 |
Writing & Preference GLM-4.6 leads
GLM-4.6: 61.1 (#90), Qwen3.5 122B-A10B: 60.0 (#105)
| Benchmark | GLM-4.6 | Qwen3.5 122B-A10B |
|---|---|---|
| LMArena Text | 1440 | 1417 |
| LMArena Creative Writing | 1411 | 1368 |
| LMArena Multi-Turn | 1427 | 1416 |
| EQ-Bench Creative Writing | 1411 | — |
Frequently asked questions
Is GLM-4.6 better than Qwen3.5 122B-A10B?
GLM-4.6 and Qwen3.5 122B-A10B score almost the same on the Noometry Index (41.4 vs 42.1), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-4.6 or Qwen3.5 122B-A10B?
GLM-4.6 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Qwen3.5 122B-A10B lists at $0.40 and $3.20.
Is GLM-4.6 or Qwen3.5 122B-A10B better for coding?
They score almost the same on coding (40.1 vs 39.1); test both on your own repository before choosing.
Which has the bigger context window?
Qwen3.5 122B-A10B does, with 262K tokens against 205K.
How many benchmarks do GLM-4.6 and Qwen3.5 122B-A10B share?
21 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Qwen3.5 122B-A10B has 27.