# GLM-5 vs Qwen3.8 27B

> GLM-5 and Qwen3.8 27B score almost the same on the Noometry Index (45.9 vs 45.3), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/glm-5-vs-qwen3-8-27b
- Last updated: 2026-10-10
- Shared benchmarks: 21

## Summary

- They share 21 benchmarks with published results for both. GLM-5 scores higher in 4 categories and Qwen3.8 27B in 4 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5 leads 52.2 to 40.9.
- The biggest single-benchmark swing is NYT Connections (extended): 74.8% for GLM-5 and 54.5% for Qwen3.8 27B.
- Qwen3.8 27B is cheaper at $0.99 / $1.49 per million input/output tokens, against $1 / $3.20 for GLM-5.
- Qwen3.8 27B accepts more context: 262K tokens versus 205K.

## Snapshot

| | GLM-5 | Qwen3.8 27B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 45.9 | 45.3 |
| Rank | 59 | 64 |
| Context | 205K | 262K |
| Input $/M | $1 | $0.99 |
| Output $/M | $3.20 | $1.49 |
| Weights | Open | Open |

## Coding

- GLM-5: 49.0 (#47)
- Qwen3.8 27B: 50.3 (#42)

| Benchmark | GLM-5 | Qwen3.8 27B |
|---|---|---|
| LMArena WebDev | 1434 | 1592 |
| LMArena Coding | 1461 | 1487 |
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| SWE-bench Multilingual | 69.7% | — |
| SciCode | — | 46.6% |
| WeirdML | 48.2% | — |
| ALE-Bench | 765.62 | — |

## Agentic & Tool Use

- GLM-5: 30.9 (#65)
- Qwen3.8 27B: —

| Benchmark | GLM-5 | Qwen3.8 27B |
|---|---|---|
| Terminal-Bench | 52.4% | — |
| 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

- GLM-5: 27.6 (#100)
- Qwen3.8 27B: 31.5 (#71)

| Benchmark | GLM-5 | Qwen3.8 27B |
|---|---|---|
| NYT Connections (extended) | 74.8% | 54.5% |
| LMArena Hard Prompts | 1451 | 1459 |
| Epoch Capabilities Index | 145.84 | 149.38 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 53.2% | — |
| Kagi LLM Benchmark | 75% | — |
| ARC-AGI-1 | 44.7% | — |
| CritPt | — | 5.4% |
| Chess Puzzles | 10% | — |
| DTBench | — | 88% |
| LMCA | — | 41.4% |
| Surface Evolver Bench | — | 45% |
| ForecastBench | 61 | — |

## Math

- GLM-5: 44.8 (#66)
- Qwen3.8 27B: 35.7 (#139)

| Benchmark | GLM-5 | Qwen3.8 27B |
|---|---|---|
| LMArena Math | 1440 | 1453 |
| MathArena Final-Answer Competitions | 65.7% | — |
| OTIS Mock AIME 2024-2025 | 80% | — |
| ProofBench | — | 16% |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-5: 52.2 (#59)
- Qwen3.8 27B: 40.9 (#105)

| Benchmark | GLM-5 | Qwen3.8 27B |
|---|---|---|
| LMArena Expert | 1454 | 1482 |
| GPQA Diamond | 87.8% | — |
| Vectara Hallucination Rate | 10.1% | — |

## Multimodal

- GLM-5: —
- Qwen3.8 27B: 40.5 (#36)

| Benchmark | GLM-5 | Qwen3.8 27B |
|---|---|---|
| LMArena Vision | — | 1270 |

## Multilingual

- GLM-5: 53.9 (#57)
- Qwen3.8 27B: 54.0 (#54)

| Benchmark | GLM-5 | Qwen3.8 27B |
|---|---|---|
| LMArena Non-English | 1430 | 1431 |
| LMArena Chinese | 1511 | 1504 |
| LMArena French | 1455 | 1468 |
| LMArena German | 1445 | 1435 |
| LMArena Japanese | 1416 | 1392 |
| LMArena Korean | 1421 | 1389 |
| LMArena Russian | 1436 | 1421 |
| LMArena Spanish | 1452 | 1444 |

## Instruction Following

- GLM-5: 75.4 (#64)
- Qwen3.8 27B: 75.8 (#54)

| Benchmark | GLM-5 | Qwen3.8 27B |
|---|---|---|
| LMArena Instruction Following | 1427 | 1436 |

## Long Context

- GLM-5: 44.6 (#58)
- Qwen3.8 27B: 44.3 (#66)

| Benchmark | GLM-5 | Qwen3.8 27B |
|---|---|---|
| LMArena Longer Query | 1446 | 1448 |
| CL-bench | 18.7% | — |

## Writing & Preference

- GLM-5: 66.2 (#38)
- Qwen3.8 27B: 65.9 (#41)

| Benchmark | GLM-5 | Qwen3.8 27B |
|---|---|---|
| LMArena Text | 1446 | 1441 |
| LMArena Creative Writing | 1438 | 1382 |
| EQ-Bench Creative Writing | 1601 | 1671 |
| LMArena Multi-Turn | 1456 | 1443 |

## FAQ

### Is GLM-5 better than Qwen3.8 27B?

GLM-5 and Qwen3.8 27B score almost the same on the Noometry Index (45.9 vs 45.3), so choose on price, context window or the category you care about most.

### Which is cheaper, GLM-5 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 lists at $1 and $3.20.

### Is GLM-5 or Qwen3.8 27B better for coding?

Qwen3.8 27B scores higher on coding benchmarks: 50.3 versus 49.0 in the Noometry coding category.

### Which has the bigger context window?

Qwen3.8 27B does, with 262K tokens against 205K.

### How many benchmarks do GLM-5 and Qwen3.8 27B share?

21 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Qwen3.8 27B has 28.