# GLM-5.1 vs Qwen3.8 27B

> GLM-5.1 is the stronger model overall, scoring 47.8 to 46.0 on the Noometry Index. Qwen3.8 27B costs 1.9× less per token, which makes it the better buy when GLM-5.1's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-5-1-vs-qwen3-8-27b
- Last updated: 2026-10-10
- Shared benchmarks: 25

## Summary

- They share 25 benchmarks with published results for both. GLM-5.1 scores higher in 6 categories and Qwen3.8 27B in 3 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.1 leads 54.9 to 41.6.
- The biggest single-benchmark swing is NYT Connections (extended): 77.7% for GLM-5.1 and 54.5% for Qwen3.8 27B.
- Qwen3.8 27B is cheaper at $0.99 / $1.49 per million input/output tokens, against $1.40 / $4.40 for GLM-5.1.
- Qwen3.8 27B accepts more context: 262K tokens versus 200K.

## Snapshot

| | GLM-5.1 | Qwen3.8 27B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 47.8 | 46.0 |
| Rank | 59 | 68 |
| Context | 200K | 262K |
| Input $/M | $1.40 | $0.99 |
| Output $/M | $4.40 | $1.49 |
| Weights | Open | Open |

## Coding

- GLM-5.1: 48.7 (#55)
- Qwen3.8 27B: 50.5 (#44)

| Benchmark | GLM-5.1 | Qwen3.8 27B |
|---|---|---|
| LMArena WebDev | 1508 | 1593 |
| SciCode | 43.8% | 46.6% |
| LMArena Coding | 1485 | 1482 |
| SWE-bench Verified | 74.2% | — |
| WeirdML | 57.1% | — |
| ALE-Bench | 887.1 | — |

## Agentic & Tool Use

- GLM-5.1: 24.9 (#113)
- Qwen3.8 27B: 32.9 (#57)

| Benchmark | GLM-5.1 | Qwen3.8 27B |
|---|---|---|
| APEX-Agents | 40.9% | 47.5% |
| ExploitBench | 18.1% | — |
| GBAEval | 0% | — |
| Vending-Bench 2 | 5,634 | — |

## Reasoning

- GLM-5.1: 39.1 (#60)
- Qwen3.8 27B: 41.0 (#54)

| Benchmark | GLM-5.1 | Qwen3.8 27B |
|---|---|---|
| NYT Connections (extended) | 77.7% | 54.5% |
| CritPt | 4.6% | 5.4% |
| LMArena Hard Prompts | 1472 | 1460 |
| Epoch Capabilities Index | 149.84 | 149.38 |
| ARC-AGI-2 | — | 42.4% |
| SimpleBench | 55.1% | — |
| ARC-AGI-1 | — | 87.5% |
| Chess Puzzles | 19% | — |
| Thematic Generalization | 69.8% | — |
| DTBench | — | 88% |
| LMCA | — | 41.4% |
| Surface Evolver Bench | — | 45% |

## Math

- GLM-5.1: 49.7 (#60)
- Qwen3.8 27B: 37.1 (#161)

| Benchmark | GLM-5.1 | Qwen3.8 27B |
|---|---|---|
| ProofBench | 22.2% | 16% |
| LMArena Math | 1473 | 1456 |
| FrontierMath (Tiers 1-3) | 36.8% | — |
| MathArena Final-Answer Competitions | 67.1% | — |
| OTIS Mock AIME 2024-2025 | 93.3% | — |
| FrontierMath (Feb 2025 set) | 33.4% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |

## Knowledge

- GLM-5.1: 54.9 (#50)
- Qwen3.8 27B: 41.6 (#109)

| Benchmark | GLM-5.1 | Qwen3.8 27B |
|---|---|---|
| LMArena Expert | 1476 | 1482 |
| GPQA Diamond | 89.9% | — |
| SimpleQA Verified | 34% | — |

## Multimodal

- GLM-5.1: —
- Qwen3.8 27B: 41.3 (#37)

| Benchmark | GLM-5.1 | Qwen3.8 27B |
|---|---|---|
| LMArena Vision | — | 1271 |

## Multilingual

- GLM-5.1: 55.0 (#36)
- Qwen3.8 27B: 53.7 (#60)

| Benchmark | GLM-5.1 | Qwen3.8 27B |
|---|---|---|
| LMArena Non-English | 1447 | 1430 |
| LMArena Chinese | 1515 | 1504 |
| LMArena French | 1474 | 1465 |
| LMArena German | 1465 | 1438 |
| LMArena Japanese | 1434 | 1384 |
| LMArena Korean | 1418 | 1393 |
| LMArena Russian | 1454 | 1415 |
| LMArena Spanish | 1469 | 1448 |

## Instruction Following

- GLM-5.1: 76.3 (#42)
- Qwen3.8 27B: 75.8 (#53)

| Benchmark | GLM-5.1 | Qwen3.8 27B |
|---|---|---|
| LMArena Instruction Following | 1451 | 1439 |

## Long Context

- GLM-5.1: 44.9 (#53)
- Qwen3.8 27B: 44.3 (#70)

| Benchmark | GLM-5.1 | Qwen3.8 27B |
|---|---|---|
| LMArena Longer Query | 1466 | 1450 |

## Writing & Preference

- GLM-5.1: 66.9 (#31)
- Qwen3.8 27B: 65.8 (#43)

| Benchmark | GLM-5.1 | Qwen3.8 27B |
|---|---|---|
| LMArena Text | 1461 | 1441 |
| LMArena Creative Writing | 1453 | 1384 |
| EQ-Bench Creative Writing | 1592 | 1671 |
| LMArena Multi-Turn | 1472 | 1441 |

## FAQ

### Is GLM-5.1 better than Qwen3.8 27B?

GLM-5.1 is the stronger model overall, scoring 47.8 to 46.0 on the Noometry Index. Qwen3.8 27B costs 1.9× less per token, which makes it the better buy when GLM-5.1's lead doesn't matter for your workload.

### Which is cheaper, GLM-5.1 or Qwen3.8 27B?

Qwen3.8 27B is cheaper. It lists at $0.99 per million input tokens and $1.49 per million output tokens; GLM-5.1 lists at $1.40 and $4.40.

### Is GLM-5.1 or Qwen3.8 27B better for coding?

Qwen3.8 27B scores higher on coding benchmarks: 50.5 versus 48.7 in the Noometry coding category.

### Which has the bigger context window?

Qwen3.8 27B does, with 262K tokens against 200K.

### How many benchmarks do GLM-5.1 and Qwen3.8 27B share?

25 benchmarks have published results for both models. GLM-5.1 has 41 scored results on Noometry and Qwen3.8 27B has 31.