Model comparison
GLM-4.7 vs Qwen3.6 35B-A3B
GLM-4.7 is the stronger model overall, scoring 42.0 to 37.6 on the Noometry Index. Qwen3.6 35B-A3B costs 1.8× less per token, which makes it the better buy when GLM-4.7's lead doesn't matter for your workload.
Last verified . 7 shared benchmarks.
Alibaba (Qwen)Summary
- They share 7 benchmarks with published results for both. GLM-4.7 scores higher in 2 categories and Qwen3.6 35B-A3B in 3 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-4.7 leads 44.0 to 37.2.
- The biggest single-benchmark swing is Chess Puzzles: 6% for GLM-4.7 and 26% for Qwen3.6 35B-A3B.
- Qwen3.6 35B-A3B is cheaper at $0.25 / $1.49 per million input/output tokens, against $0.60 / $2.20 for GLM-4.7.
- Qwen3.6 35B-A3B accepts more context: 262K tokens versus 205K.
Side by side
| GLM-4.7 | Qwen3.6 35B-A3B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 42.0 | 37.6 |
| Released | 2025-12-22 | 2026-04-01 |
| Weights | Open | Open |
| Context window | 205K | 262K |
| Max output | 131K | 66K |
| Input $ / M tokens | $0.60 | $0.25 |
| Output $ / M tokens | $2.20 | $1.49 |
| Results tracked | 36 | 14 |
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Category by category
Coding GLM-4.7 leads
GLM-4.7: 44.0 (#79), Qwen3.6 35B-A3B: 37.2 (#196)
| Benchmark | GLM-4.7 | Qwen3.6 35B-A3B |
|---|---|---|
| SciCode | 45.1% | 35.8% |
| LMArena WebDev | 1435 | — |
| WeirdML | — | 34.5% |
| LMArena Coding | 1454 | — |
| ALE-Bench | 399.48 | — |
Agentic & Tool Use GLM-4.7 leads
GLM-4.7: 26.5 (#103), Qwen3.6 35B-A3B: 22.1 (#134)
| Benchmark | GLM-4.7 | Qwen3.6 35B-A3B |
|---|---|---|
| Terminal-Bench | 33.4% | 23% |
| Vending-Bench 2 | 2,377 | — |
Reasoning Qwen3.6 35B-A3B leads
GLM-4.7: 24.3 (#164), Qwen3.6 35B-A3B: 28.0 (#109)
| Benchmark | GLM-4.7 | Qwen3.6 35B-A3B |
|---|---|---|
| CritPt | 1.7% | 0.3% |
| Chess Puzzles | 6% | 26% |
| Epoch Capabilities Index | 143.51 | 143.93 |
| SimpleBench | 47.7% | — |
| NYT Connections (extended) | — | 41.6% |
| LMArena Hard Prompts | 1443 | — |
| Mystery Game Puzzles | — | 22% |
| DTBench | — | 73.9% |
| LMCA | — | 29.7% |
| Surface Evolver Bench | — | 44.4% |
Math Too close to call
GLM-4.7: 38.6 (#135), Qwen3.6 35B-A3B: 38.9 (#121)
| Benchmark | GLM-4.7 | Qwen3.6 35B-A3B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 83.3% | 86.7% |
| FrontierMath (Tiers 1-3) | — | 20.4% |
| ProofBench | 6% | — |
| LMArena Math | 1423 | — |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Qwen3.6 35B-A3B leads
GLM-4.7: 47.0 (#80), Qwen3.6 35B-A3B: 51.3 (#68)
| Benchmark | GLM-4.7 | Qwen3.6 35B-A3B |
|---|---|---|
| GPQA Diamond | 83.3% | 84.8% |
| SimpleQA Verified | 32.2% | — |
| Vectara Hallucination Rate | 11.7% | — |
| LMArena Expert | 1424 | — |
Multilingual Not comparable
GLM-4.7: 52.8 (#79), Qwen3.6 35B-A3B: —
| Benchmark | GLM-4.7 | Qwen3.6 35B-A3B |
|---|---|---|
| LMArena Non-English | 1417 | — |
| LMArena Chinese | 1495 | — |
| LMArena French | 1432 | — |
| LMArena German | 1424 | — |
| LMArena Japanese | 1439 | — |
| LMArena Korean | 1399 | — |
| LMArena Russian | 1423 | — |
| LMArena Spanish | 1434 | — |
Instruction Following Not comparable
GLM-4.7: 74.4 (#95), Qwen3.6 35B-A3B: —
| Benchmark | GLM-4.7 | Qwen3.6 35B-A3B |
|---|---|---|
| LMArena Instruction Following | 1411 | — |
Long Context Not comparable
GLM-4.7: 42.8 (#116), Qwen3.6 35B-A3B: —
| Benchmark | GLM-4.7 | Qwen3.6 35B-A3B |
|---|---|---|
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |
| LMArena Longer Query | 1432 | — |
Writing & Preference Not comparable
GLM-4.7: 60.9 (#93), Qwen3.6 35B-A3B: —
| Benchmark | GLM-4.7 | Qwen3.6 35B-A3B |
|---|---|---|
| LMArena Text | 1435 | — |
| LMArena Creative Writing | 1401 | — |
| EQ-Bench Creative Writing | 1413 | — |
| LMArena Multi-Turn | 1446 | — |
Frequently asked questions
Is GLM-4.7 better than Qwen3.6 35B-A3B?
GLM-4.7 is the stronger model overall, scoring 42.0 to 37.6 on the Noometry Index. Qwen3.6 35B-A3B costs 1.8× less per token, which makes it the better buy when GLM-4.7's lead doesn't matter for your workload.
Which is cheaper, GLM-4.7 or Qwen3.6 35B-A3B?
Qwen3.6 35B-A3B is cheaper. It lists at $0.25 per million input tokens and $1.49 per million output tokens; GLM-4.7 lists at $0.60 and $2.20.
Is GLM-4.7 or Qwen3.6 35B-A3B better for coding?
GLM-4.7 scores higher on coding benchmarks: 44.0 versus 37.2 in the Noometry coding category.
Which has the bigger context window?
Qwen3.6 35B-A3B does, with 262K tokens against 205K.
How many benchmarks do GLM-4.7 and Qwen3.6 35B-A3B share?
7 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Qwen3.6 35B-A3B has 14.