Model comparison
GLM-4.7 vs Qwen3.7 Max
Qwen3.7 Max is the stronger model overall, scoring 51.5 to 42.0 on the Noometry Index. GLM-4.7 costs 3.8× less per token, which makes it the better buy when Qwen3.7 Max's lead doesn't matter for your workload.
Last verified . 23 shared benchmarks.
Alibaba (Qwen)Summary
- They share 23 benchmarks with published results for both. GLM-4.7 scores higher in 1 category and Qwen3.7 Max in 8 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.7 Max leads 49.2 to 24.3.
- The biggest single-benchmark swing is SimpleQA Verified: 32.2% for GLM-4.7 and 55.8% for Qwen3.7 Max.
- GLM-4.7 is cheaper at $0.60 / $2.20 per million input/output tokens, against $2.50 / $7.50 for Qwen3.7 Max.
- Qwen3.7 Max accepts more context: 1M tokens versus 205K.
- GLM-4.7 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.7 | Qwen3.7 Max | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 42.0 | 51.5 |
| Released | 2025-12-22 | 2026-05-19 |
| Weights | Open | Proprietary |
| Context window | 205K | 1M |
| Max output | 131K | 131K |
| Input $ / M tokens | $0.60 | $2.50 |
| Output $ / M tokens | $2.20 | $7.50 |
| Results tracked | 36 | 33 |
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Category by category
Coding Qwen3.7 Max leads
GLM-4.7: 44.0 (#79), Qwen3.7 Max: 50.4 (#45)
| Benchmark | GLM-4.7 | Qwen3.7 Max |
|---|---|---|
| LMArena WebDev | 1435 | 1515 |
| SciCode | 45.1% | 48.8% |
| LMArena Coding | 1454 | 1498 |
| ALE-Bench | 399.48 | 1,189 |
| SWE-bench Verified | — | 77.3% |
Agentic & Tool Use GLM-4.7 leads
GLM-4.7: 26.5 (#103), Qwen3.7 Max: 22.1 (#135)
| Benchmark | GLM-4.7 | Qwen3.7 Max |
|---|---|---|
| Terminal-Bench | 33.4% | — |
| GBAEval | — | 0.4% |
| Vending-Bench 2 | 2,377 | — |
Reasoning Qwen3.7 Max leads
GLM-4.7: 24.3 (#164), Qwen3.7 Max: 49.2 (#38)
| Benchmark | GLM-4.7 | Qwen3.7 Max |
|---|---|---|
| SimpleBench | 47.7% | 70.4% |
| CritPt | 1.7% | 13.4% |
| Chess Puzzles | 6% | 19% |
| LMArena Hard Prompts | 1443 | 1483 |
| Epoch Capabilities Index | 143.51 | 153.68 |
| NYT Connections (extended) | — | 85.1% |
| EBR-Bench | — | 9.5% |
| Mystery Game Puzzles | — | 32% |
| DTBench | — | 92.3% |
| LMCA | — | 44% |
Math Qwen3.7 Max leads
GLM-4.7: 38.6 (#135), Qwen3.7 Max: 62.4 (#32)
| Benchmark | GLM-4.7 | Qwen3.7 Max |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 83.3% | 95.6% |
| ProofBench | 6% | 26% |
| LMArena Math | 1423 | 1490 |
| FrontierMath (Tiers 1-3) | — | 64.6% |
| FrontierMath Tier 4 | — | 34.1% |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Qwen3.7 Max leads
GLM-4.7: 47.0 (#80), Qwen3.7 Max: 61.6 (#28)
| Benchmark | GLM-4.7 | Qwen3.7 Max |
|---|---|---|
| GPQA Diamond | 83.3% | 90.9% |
| SimpleQA Verified | 32.2% | 55.8% |
| LMArena Expert | 1424 | 1488 |
| Vectara Hallucination Rate | 11.7% | — |
Multilingual Qwen3.7 Max leads
GLM-4.7: 52.8 (#79), Qwen3.7 Max: 56.9 (#15)
| Benchmark | GLM-4.7 | Qwen3.7 Max |
|---|---|---|
| LMArena Non-English | 1417 | 1474 |
| LMArena Chinese | 1495 | 1530 |
| LMArena Russian | 1423 | 1484 |
| LMArena French | 1432 | — |
| LMArena German | 1424 | — |
| LMArena Japanese | 1439 | — |
| LMArena Korean | 1399 | — |
| LMArena Spanish | 1434 | — |
Instruction Following Qwen3.7 Max leads
GLM-4.7: 74.4 (#95), Qwen3.7 Max: 76.7 (#38)
| Benchmark | GLM-4.7 | Qwen3.7 Max |
|---|---|---|
| LMArena Instruction Following | 1411 | 1460 |
Long Context Qwen3.7 Max leads
GLM-4.7: 42.8 (#116), Qwen3.7 Max: 45.4 (#40)
| Benchmark | GLM-4.7 | Qwen3.7 Max |
|---|---|---|
| LMArena Longer Query | 1432 | 1482 |
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |
Writing & Preference Qwen3.7 Max leads
GLM-4.7: 60.9 (#93), Qwen3.7 Max: 65.0 (#54)
| Benchmark | GLM-4.7 | Qwen3.7 Max |
|---|---|---|
| LMArena Text | 1435 | 1476 |
| LMArena Creative Writing | 1401 | 1449 |
| LMArena Multi-Turn | 1446 | 1481 |
| EQ-Bench Creative Writing | 1413 | — |
| EQ-Bench 4 | — | 1110 |
Frequently asked questions
Is GLM-4.7 better than Qwen3.7 Max?
Qwen3.7 Max is the stronger model overall, scoring 51.5 to 42.0 on the Noometry Index. GLM-4.7 costs 3.8× less per token, which makes it the better buy when Qwen3.7 Max's lead doesn't matter for your workload.
Which is cheaper, GLM-4.7 or Qwen3.7 Max?
GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Qwen3.7 Max lists at $2.50 and $7.50.
Is GLM-4.7 or Qwen3.7 Max better for coding?
Qwen3.7 Max scores higher on coding benchmarks: 50.4 versus 44.0 in the Noometry coding category.
Which has the bigger context window?
Qwen3.7 Max does, with 1M tokens against 205K.
How many benchmarks do GLM-4.7 and Qwen3.7 Max share?
23 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Qwen3.7 Max has 33.