Model comparison
GLM-5 vs Qwen3.7 Plus
GLM-5 and Qwen3.7 Plus score almost the same on the Noometry Index (46.1 vs 45.3), so choose on price, context window or the category you care about most.
Last verified . 22 shared benchmarks.
Alibaba (Qwen)Summary
- They share 22 benchmarks with published results for both. GLM-5 scores higher in 4 categories and Qwen3.7 Plus in 5 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-5 leads 49.0 to 36.6.
- The biggest single-benchmark swing is Chess Puzzles: 10% for GLM-5 and 24% for Qwen3.7 Plus.
- Qwen3.7 Plus is cheaper at $0.40 / $1.60 per million input/output tokens, against $1 / $3.20 for GLM-5.
- Qwen3.7 Plus accepts more context: 1M tokens versus 205K.
- GLM-5 has downloadable open weights; the other is API-only.
Side by side
| GLM-5 | Qwen3.7 Plus | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 46.1 | 45.3 |
| Released | 2026-02-11 | 2026-06-02 |
| Weights | Open | Proprietary |
| Context window | 205K | 1M |
| Max output | 131K | 131K |
| Input $ / M tokens | $1 | $0.40 |
| Output $ / M tokens | $3.20 | $1.60 |
| Results tracked | 45 | 32 |
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Category by category
Coding GLM-5 leads
GLM-5: 49.0 (#52), Qwen3.7 Plus: 36.6 (#206)
| Benchmark | GLM-5 | Qwen3.7 Plus |
|---|---|---|
| LMArena Coding | 1461 | 1473 |
| SWE-bench Verified | 72.1% | — |
| FrontierCode | — | 10.2% |
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1434 | — |
| SWE-bench Multilingual | 69.7% | — |
| SciCode | — | 45.5% |
| WeirdML | 48.2% | — |
| ALE-Bench | 765.62 | — |
Agentic & Tool Use GLM-5 leads
GLM-5: 31.1 (#71), Qwen3.7 Plus: 21.4 (#138)
| Benchmark | GLM-5 | Qwen3.7 Plus |
|---|---|---|
| Terminal-Bench | 52.4% | — |
| OSWorld 2.0 | — | 2.8% |
| τ²-bench Airline | 82.5% | — |
| τ²-bench Banking | 9.8% | — |
| τ²-bench Retail | 73.7% | — |
| τ²-bench Telecom | 86.8% | — |
| Vending-Bench 2 | 4,432 | — |
Reasoning Qwen3.7 Plus leads
GLM-5: 27.6 (#116), Qwen3.7 Plus: 39.3 (#59)
| Benchmark | GLM-5 | Qwen3.7 Plus |
|---|---|---|
| NYT Connections (extended) | 74.8% | 74.8% |
| Chess Puzzles | 10% | 24% |
| LMArena Hard Prompts | 1452 | 1460 |
| Epoch Capabilities Index | 145.83 | 147.37 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 53.2% | — |
| Kagi LLM Benchmark | 75% | — |
| ARC-AGI-1 | 44.7% | — |
| CritPt | — | 9.1% |
| Mystery Game Puzzles | — | 17% |
| DTBench | — | 84% |
| LMCA | — | 37.6% |
| ForecastBench | 61 | — |
Math Qwen3.7 Plus leads
GLM-5: 46.4 (#71), Qwen3.7 Plus: 50.5 (#56)
| Benchmark | GLM-5 | Qwen3.7 Plus |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 80% | 93.3% |
| LMArena Math | 1440 | 1466 |
| FrontierMath (Tiers 1-3) | — | 34.4% |
| MathArena Final-Answer Competitions | 65.7% | — |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge Qwen3.7 Plus leads
GLM-5: 52.3 (#64), Qwen3.7 Plus: 54.9 (#51)
| Benchmark | GLM-5 | Qwen3.7 Plus |
|---|---|---|
| GPQA Diamond | 87.8% | 87.9% |
| LMArena Expert | 1454 | 1467 |
| Vectara Hallucination Rate | 10.1% | — |
Multimodal Not comparable
GLM-5: —, Qwen3.7 Plus: 41.8 (#33)
| Benchmark | GLM-5 | Qwen3.7 Plus |
|---|---|---|
| LMArena Vision | — | 1279 |
| LMArena Document | — | 1444 |
Multilingual Qwen3.7 Plus leads
GLM-5: 53.7 (#58), Qwen3.7 Plus: 54.8 (#38)
| Benchmark | GLM-5 | Qwen3.7 Plus |
|---|---|---|
| LMArena Non-English | 1430 | 1445 |
| LMArena Chinese | 1511 | 1510 |
| LMArena French | 1455 | 1473 |
| LMArena German | 1445 | 1471 |
| LMArena Japanese | 1416 | 1413 |
| LMArena Korean | 1423 | 1415 |
| LMArena Russian | 1436 | 1457 |
| LMArena Spanish | 1454 | 1457 |
Instruction Following Too close to call
GLM-5: 75.2 (#67), Qwen3.7 Plus: 75.8 (#52)
| Benchmark | GLM-5 | Qwen3.7 Plus |
|---|---|---|
| LMArena Instruction Following | 1428 | 1440 |
Long Context Too close to call
GLM-5: 44.7 (#60), Qwen3.7 Plus: 44.5 (#65)
| Benchmark | GLM-5 | Qwen3.7 Plus |
|---|---|---|
| LMArena Longer Query | 1446 | 1455 |
| CL-bench | 18.7% | — |
Writing & Preference GLM-5 leads
GLM-5: 66.0 (#38), Qwen3.7 Plus: 64.3 (#56)
| Benchmark | GLM-5 | Qwen3.7 Plus |
|---|---|---|
| LMArena Text | 1446 | 1455 |
| LMArena Creative Writing | 1439 | 1439 |
| LMArena Multi-Turn | 1456 | 1460 |
| EQ-Bench Creative Writing | 1601 | — |
Frequently asked questions
Is GLM-5 better than Qwen3.7 Plus?
GLM-5 and Qwen3.7 Plus score almost the same on the Noometry Index (46.1 vs 45.3), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-5 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-5 lists at $1 and $3.20.
Is GLM-5 or Qwen3.7 Plus better for coding?
GLM-5 scores higher on coding benchmarks: 49.0 versus 36.6 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-5 and Qwen3.7 Plus share?
22 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Qwen3.7 Plus has 32.