# GLM-4.7 vs Qwen3.5 27B

> GLM-4.7 and Qwen3.5 27B score almost the same on the Noometry Index (42.0 vs 41.9), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/glm-4-7-vs-qwen3-5-27b
- Last updated: 2026-10-10
- Shared benchmarks: 21

## Summary

- They share 21 benchmarks with published results for both. GLM-4.7 scores higher in 5 categories and Qwen3.5 27B in 3 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-4.7 leads 47.0 to 38.0.
- Qwen3.5 27B is cheaper at $0.30 / $2.40 per million input/output tokens, against $0.60 / $2.20 for GLM-4.7.
- Qwen3.5 27B accepts more context: 262K tokens versus 205K.

## Snapshot

| | GLM-4.7 | Qwen3.5 27B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 42.0 | 41.9 |
| Rank | 124 | 127 |
| Context | 205K | 262K |
| Input $/M | $0.60 | $0.30 |
| Output $/M | $2.20 | $2.40 |
| Weights | Open | Open |

## Coding

- GLM-4.7: 44.0 (#79)
- Qwen3.5 27B: 38.9 (#168)

| Benchmark | GLM-4.7 | Qwen3.5 27B |
|---|---|---|
| LMArena WebDev | 1435 | 1358 |
| LMArena Coding | 1454 | 1427 |
| ALE-Bench | 399.48 | 349.45 |
| SciCode | 45.1% | — |
| WeirdML | — | 39.5% |

## Agentic & Tool Use

- GLM-4.7: 26.5 (#103)
- Qwen3.5 27B: —

| Benchmark | GLM-4.7 | Qwen3.5 27B |
|---|---|---|
| Vending-Bench 2 | 2,377 | 201.98 |
| Terminal-Bench | 33.4% | — |

## Reasoning

- GLM-4.7: 24.3 (#164)
- Qwen3.5 27B: 27.5 (#117)

| Benchmark | GLM-4.7 | Qwen3.5 27B |
|---|---|---|
| LMArena Hard Prompts | 1443 | 1414 |
| SimpleBench | 47.7% | — |
| NYT Connections (extended) | — | 47.9% |
| CritPt | 1.7% | — |
| Chess Puzzles | 6% | — |
| Thematic Generalization | — | 45.5% |
| DTBench | — | 82.4% |
| LMCA | — | 34% |
| Epoch Capabilities Index | 143.51 | — |

## Math

- GLM-4.7: 38.6 (#135)
- Qwen3.5 27B: 38.8 (#127)

| Benchmark | GLM-4.7 | Qwen3.5 27B |
|---|---|---|
| LMArena Math | 1423 | 1429 |
| MathArena Final-Answer Competitions | — | 56.7% |
| OTIS Mock AIME 2024-2025 | 83.3% | — |
| ProofBench | 6% | — |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |

## Knowledge

- GLM-4.7: 47.0 (#80)
- Qwen3.5 27B: 38.0 (#150)

| Benchmark | GLM-4.7 | Qwen3.5 27B |
|---|---|---|
| Vectara Hallucination Rate | 11.7% | 12.1% |
| LMArena Expert | 1424 | 1428 |
| GPQA Diamond | 83.3% | — |
| SimpleQA Verified | 32.2% | — |

## Multimodal

- GLM-4.7: —
- Qwen3.5 27B: 39.4 (#59)

| Benchmark | GLM-4.7 | Qwen3.5 27B |
|---|---|---|
| LMArena Vision | — | 1241 |

## Multilingual

- GLM-4.7: 52.8 (#79)
- Qwen3.5 27B: 50.8 (#115)

| Benchmark | GLM-4.7 | Qwen3.5 27B |
|---|---|---|
| LMArena Non-English | 1417 | 1390 |
| LMArena Chinese | 1495 | 1478 |
| LMArena French | 1432 | 1410 |
| LMArena German | 1424 | 1393 |
| LMArena Japanese | 1439 | 1345 |
| LMArena Korean | 1399 | 1358 |
| LMArena Russian | 1423 | 1390 |
| LMArena Spanish | 1434 | 1407 |

## Instruction Following

- GLM-4.7: 74.4 (#95)
- Qwen3.5 27B: 73.5 (#119)

| Benchmark | GLM-4.7 | Qwen3.5 27B |
|---|---|---|
| LMArena Instruction Following | 1411 | 1393 |

## Long Context

- GLM-4.7: 42.8 (#116)
- Qwen3.5 27B: 43.1 (#106)

| Benchmark | GLM-4.7 | Qwen3.5 27B |
|---|---|---|
| LMArena Longer Query | 1432 | 1413 |
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |

## Writing & Preference

- GLM-4.7: 60.9 (#93)
- Qwen3.5 27B: 59.3 (#111)

| Benchmark | GLM-4.7 | Qwen3.5 27B |
|---|---|---|
| LMArena Text | 1435 | 1409 |
| LMArena Creative Writing | 1401 | 1362 |
| LMArena Multi-Turn | 1446 | 1410 |
| EQ-Bench Creative Writing | 1413 | — |

## FAQ

### Is GLM-4.7 better than Qwen3.5 27B?

GLM-4.7 and Qwen3.5 27B score almost the same on the Noometry Index (42.0 vs 41.9), so choose on price, context window or the category you care about most.

### Which is cheaper, GLM-4.7 or Qwen3.5 27B?

Qwen3.5 27B is cheaper. It lists at $0.30 per million input tokens and $2.40 per million output tokens; GLM-4.7 lists at $0.60 and $2.20.

### Is GLM-4.7 or Qwen3.5 27B better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 38.9 in the Noometry coding category.

### Which has the bigger context window?

Qwen3.5 27B does, with 262K tokens against 205K.

### How many benchmarks do GLM-4.7 and Qwen3.5 27B share?

21 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Qwen3.5 27B has 28.