# GLM-5 vs Qwen1.5-14B

> GLM-5 is the stronger model overall, scoring 45.9 to 32.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-vs-qwen1-5-14b
- Last updated: 2026-10-10
- Shared benchmarks: 16

## Summary

- They share 16 benchmarks with published results for both. GLM-5 scores higher in 8 categories and Qwen1.5-14B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-5 leads 66.2 to 33.7.

## Snapshot

| | GLM-5 | Qwen1.5-14B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 45.9 | 32.1 |
| Rank | 59 | 250 |
| Context | 205K | — |
| Input $/M | $1 | — |
| Output $/M | $3.20 | — |
| Weights | Open | Open |

## Coding

- GLM-5: 49.0 (#47)
- Qwen1.5-14B: 32.5 (#259)

| Benchmark | GLM-5 | Qwen1.5-14B |
|---|---|---|
| LMArena Coding | 1461 | 1138 |
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1434 | — |
| SWE-bench Multilingual | 69.7% | — |
| WeirdML | 48.2% | — |
| ALE-Bench | 765.62 | — |

## Agentic & Tool Use

- GLM-5: 30.9 (#65)
- Qwen1.5-14B: —

| Benchmark | GLM-5 | Qwen1.5-14B |
|---|---|---|
| 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)
- Qwen1.5-14B: 20.5 (#217)

| Benchmark | GLM-5 | Qwen1.5-14B |
|---|---|---|
| LMArena Hard Prompts | 1451 | 1113 |
| ARC-AGI-2 | 4.9% | — |
| SimpleBench | 53.2% | — |
| Kagi LLM Benchmark | 75% | — |
| NYT Connections (extended) | 74.8% | — |
| ARC-AGI-1 | 44.7% | — |
| Chess Puzzles | 10% | — |
| Epoch Capabilities Index | 145.84 | — |
| ForecastBench | 61 | — |

## Math

- GLM-5: 44.8 (#66)
- Qwen1.5-14B: 29.9 (#214)

| Benchmark | GLM-5 | Qwen1.5-14B |
|---|---|---|
| LMArena Math | 1440 | 1125 |
| MathArena Final-Answer Competitions | 65.7% | — |
| OTIS Mock AIME 2024-2025 | 80% | — |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-5: 52.2 (#59)
- Qwen1.5-14B: 29.3 (#230)

| Benchmark | GLM-5 | Qwen1.5-14B |
|---|---|---|
| LMArena Expert | 1454 | 1094 |
| GPQA Diamond | 87.8% | — |
| Vectara Hallucination Rate | 10.1% | — |
| MMLU | — | 68.6% |

## Multilingual

- GLM-5: 53.9 (#57)
- Qwen1.5-14B: 30.8 (#257)

| Benchmark | GLM-5 | Qwen1.5-14B |
|---|---|---|
| LMArena Non-English | 1430 | 1095 |
| LMArena Chinese | 1511 | 1147 |
| LMArena French | 1455 | 1115 |
| LMArena German | 1445 | 1043 |
| LMArena Japanese | 1416 | 1019 |
| LMArena Russian | 1436 | 1046 |
| LMArena Spanish | 1452 | 1085 |
| LMArena Korean | 1421 | — |

## Instruction Following

- GLM-5: 75.4 (#64)
- Qwen1.5-14B: 57.1 (#266)

| Benchmark | GLM-5 | Qwen1.5-14B |
|---|---|---|
| LMArena Instruction Following | 1427 | 1102 |

## Long Context

- GLM-5: 44.6 (#58)
- Qwen1.5-14B: 33.7 (#252)

| Benchmark | GLM-5 | Qwen1.5-14B |
|---|---|---|
| LMArena Longer Query | 1446 | 1113 |
| CL-bench | 18.7% | — |

## Writing & Preference

- GLM-5: 66.2 (#38)
- Qwen1.5-14B: 33.7 (#270)

| Benchmark | GLM-5 | Qwen1.5-14B |
|---|---|---|
| LMArena Text | 1446 | 1128 |
| LMArena Creative Writing | 1438 | 1091 |
| LMArena Multi-Turn | 1456 | 1110 |
| EQ-Bench Creative Writing | 1601 | — |

## FAQ

### Is GLM-5 better than Qwen1.5-14B?

GLM-5 is the stronger model overall, scoring 45.9 to 32.1 on the Noometry Index.

### Is GLM-5 or Qwen1.5-14B better for coding?

GLM-5 scores higher on coding benchmarks: 49.0 versus 32.5 in the Noometry coding category.

### How many benchmarks do GLM-5 and Qwen1.5-14B share?

16 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Qwen1.5-14B has 17.