Model comparison
GLM-4.7 vs Qwen3.7 Plus
Qwen3.7 Plus is the stronger model overall, scoring 45.0 to 41.7 on the Noometry Index.
Last verified . 23 shared benchmarks.
Alibaba (Qwen)Summary
- They share 23 benchmarks with published results for both. GLM-4.7 scores higher in 2 categories and Qwen3.7 Plus in 7 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.7 Plus leads 38.4 to 23.7.
- The biggest single-benchmark swing is Chess Puzzles: 6% for GLM-4.7 and 24% for Qwen3.7 Plus.
- Qwen3.7 Plus is cheaper at $0.40 / $1.60 per million input/output tokens, against $0.60 / $2.20 for GLM-4.7.
- Qwen3.7 Plus 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 Plus | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 41.7 | 45.0 |
| Released | 2025-12-22 | 2026-06-02 |
| Weights | Open | Proprietary |
| Context window | 205K | 1M |
| Max output | 131K | 131K |
| Input $ / M tokens | $0.60 | $0.40 |
| Output $ / M tokens | $2.20 | $1.60 |
| Results tracked | 36 | 32 |
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Category by category
Coding GLM-4.7 leads
GLM-4.7: 43.6 (#74), Qwen3.7 Plus: 36.1 (#200)
| Benchmark | GLM-4.7 | Qwen3.7 Plus |
|---|---|---|
| SciCode | 45.1% | 45.5% |
| LMArena Coding | 1454 | 1473 |
| FrontierCode | — | 10.2% |
| LMArena WebDev | 1435 | — |
| ALE-Bench | 399.48 | — |
Agentic & Tool Use GLM-4.7 leads
GLM-4.7: 26.4 (#96), Qwen3.7 Plus: 21.2 (#130)
| Benchmark | GLM-4.7 | Qwen3.7 Plus |
|---|---|---|
| Terminal-Bench | 33.4% | — |
| OSWorld 2.0 | — | 2.8% |
| Vending-Bench 2 | 2,377 | — |
Reasoning Qwen3.7 Plus leads
GLM-4.7: 23.7 (#161), Qwen3.7 Plus: 38.4 (#54)
| Benchmark | GLM-4.7 | Qwen3.7 Plus |
|---|---|---|
| CritPt | 1.7% | 9.1% |
| Chess Puzzles | 6% | 24% |
| LMArena Hard Prompts | 1443 | 1460 |
| Epoch Capabilities Index | 143.53 | 147.39 |
| SimpleBench | 47.7% | — |
| NYT Connections (extended) | — | 74.8% |
| Mystery Game Puzzles | — | 17% |
| DTBench | — | 84% |
| LMCA | — | 37.6% |
Math Qwen3.7 Plus leads
GLM-4.7: 37.7 (#92), Qwen3.7 Plus: 49.3 (#47)
| Benchmark | GLM-4.7 | Qwen3.7 Plus |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 83.3% | 93.3% |
| LMArena Math | 1423 | 1467 |
| FrontierMath (Tiers 1-3) | — | 34.4% |
| ProofBench | 6% | — |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Qwen3.7 Plus leads
GLM-4.7: 47.0 (#74), Qwen3.7 Plus: 54.9 (#46)
| Benchmark | GLM-4.7 | Qwen3.7 Plus |
|---|---|---|
| GPQA Diamond | 83.3% | 87.9% |
| LMArena Expert | 1424 | 1467 |
| SimpleQA Verified | 32.2% | — |
| Vectara Hallucination Rate | 11.7% | — |
Multimodal Not comparable
GLM-4.7: —, Qwen3.7 Plus: 41.2 (#30)
| Benchmark | GLM-4.7 | Qwen3.7 Plus |
|---|---|---|
| LMArena Vision | — | 1281 |
| LMArena Document | — | 1444 |
Multilingual Qwen3.7 Plus leads
GLM-4.7: 53.0 (#75), Qwen3.7 Plus: 55.0 (#36)
| Benchmark | GLM-4.7 | Qwen3.7 Plus |
|---|---|---|
| LMArena Non-English | 1417 | 1445 |
| LMArena Chinese | 1495 | 1510 |
| LMArena French | 1432 | 1471 |
| LMArena German | 1426 | 1471 |
| LMArena Japanese | 1439 | 1411 |
| LMArena Korean | 1401 | 1416 |
| LMArena Russian | 1423 | 1457 |
| LMArena Spanish | 1433 | 1453 |
Instruction Following Qwen3.7 Plus leads
GLM-4.7: 74.6 (#90), Qwen3.7 Plus: 75.9 (#49)
| Benchmark | GLM-4.7 | Qwen3.7 Plus |
|---|---|---|
| LMArena Instruction Following | 1411 | 1439 |
Long Context Qwen3.7 Plus leads
GLM-4.7: 42.8 (#111), Qwen3.7 Plus: 44.5 (#61)
| Benchmark | GLM-4.7 | Qwen3.7 Plus |
|---|---|---|
| LMArena Longer Query | 1432 | 1454 |
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |
Writing & Preference Qwen3.7 Plus leads
GLM-4.7: 61.1 (#89), Qwen3.7 Plus: 64.5 (#54)
| Benchmark | GLM-4.7 | Qwen3.7 Plus |
|---|---|---|
| LMArena Text | 1436 | 1454 |
| LMArena Creative Writing | 1401 | 1439 |
| LMArena Multi-Turn | 1446 | 1459 |
| EQ-Bench Creative Writing | 1413 | — |
Frequently asked questions
Is GLM-4.7 better than Qwen3.7 Plus?
Qwen3.7 Plus is the stronger model overall, scoring 45.0 to 41.7 on the Noometry Index.
Which is cheaper, GLM-4.7 or Qwen3.7 Plus?
Qwen3.7 Plus is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; GLM-4.7 lists at $0.60 and $2.20.
Is GLM-4.7 or Qwen3.7 Plus better for coding?
GLM-4.7 scores higher on coding benchmarks: 43.6 versus 36.1 in the Noometry coding category.
Which has the bigger context window?
Qwen3.7 Plus does, with 1M tokens against 205K.
How many benchmarks do GLM-4.7 and Qwen3.7 Plus share?
23 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Qwen3.7 Plus has 32.