# GLM-4.6 vs Qwen3 14B

> GLM-4.6 is the stronger model overall, scoring 40.9 to 35.0 on the Noometry Index. Qwen3 14B costs 1.6× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-4-6-vs-qwen3-14b
- Last updated: 2026-10-10
- Shared benchmarks: 5

## Summary

- They share 5 benchmarks with published results for both. GLM-4.6 scores higher in 5 categories and Qwen3 14B in 1 category; 4 gaps are clear of the uncertainty.
- The widest gap is in long context, where GLM-4.6 leads 43.4 to 38.0.
- The biggest single-benchmark swing is Berkeley Function Calling Leaderboard: 72.4% for GLM-4.6 and 41% for Qwen3 14B.
- Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $0.60 / $2.20 for GLM-4.6.
- GLM-4.6 accepts more context: 205K tokens versus 131K.

## Snapshot

| | GLM-4.6 | Qwen3 14B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 40.9 | 35.0 |
| Rank | 132 | 222 |
| Context | 205K | 131K |
| Input $/M | $0.60 | $0.35 |
| Output $/M | $2.20 | $1.40 |
| Weights | Open | Open |

## Coding

- GLM-4.6: 39.9 (#137)
- Qwen3 14B: 36.7 (#191)

| Benchmark | GLM-4.6 | Qwen3 14B |
|---|---|---|
| SciCode | 38.4% | 31.6% |
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1339 | — |
| LMArena Coding | 1449 | — |
| ALE-Bench | 340.82 | — |

## Agentic & Tool Use

- GLM-4.6: 32.1 (#60)
- Qwen3 14B: 29.4 (#78)

| Benchmark | GLM-4.6 | Qwen3 14B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 72.4% | 41% |
| Terminal-Bench | 24.5% | — |

## Reasoning

- GLM-4.6: 23.1 (#168)
- Qwen3 14B: 18.1 (#272)

| Benchmark | GLM-4.6 | Qwen3 14B |
|---|---|---|
| Kagi LLM Benchmark | 47.4% | 49.1% |
| CritPt | 1.1% | 0% |
| Chess Puzzles | — | 4% |
| LMArena Hard Prompts | 1440 | — |
| DTBench | — | 64% |
| LMCA | — | 18.2% |
| Epoch Capabilities Index | — | 138.23 |

## Math

- GLM-4.6: 36.4 (#115)
- Qwen3 14B: 37.0 (#102)

| Benchmark | GLM-4.6 | Qwen3 14B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.4% |
| LMArena Math | 1431 | — |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-4.6: 39.6 (#118)
- Qwen3 14B: 39.2 (#124)

| Benchmark | GLM-4.6 | Qwen3 14B |
|---|---|---|
| Vectara Hallucination Rate | 9.5% | 5.4% |
| GPQA Diamond | — | 63.8% |
| LMArena Expert | 1432 | — |

## Multilingual

- GLM-4.6: 53.6 (#62)
- Qwen3 14B: —

| Benchmark | GLM-4.6 | Qwen3 14B |
|---|---|---|
| LMArena Non-English | 1426 | — |
| LMArena Chinese | 1500 | — |
| LMArena French | 1459 | — |
| LMArena German | 1447 | — |
| LMArena Japanese | 1394 | — |
| LMArena Korean | 1401 | — |
| LMArena Russian | 1418 | — |
| LMArena Spanish | 1436 | — |

## Instruction Following

- GLM-4.6: 74.5 (#93)
- Qwen3 14B: —

| Benchmark | GLM-4.6 | Qwen3 14B |
|---|---|---|
| LMArena Instruction Following | 1410 | — |

## Long Context

- GLM-4.6: 43.4 (#91)
- Qwen3 14B: 38.0 (#201)

| Benchmark | GLM-4.6 | Qwen3 14B |
|---|---|---|
| Fiction.LiveBench | — | 62.5% |
| LMArena Longer Query | 1423 | — |

## Writing & Preference

- GLM-4.6: 61.3 (#86)
- Qwen3 14B: —

| Benchmark | GLM-4.6 | Qwen3 14B |
|---|---|---|
| LMArena Text | 1440 | — |
| LMArena Creative Writing | 1411 | — |
| EQ-Bench Creative Writing | 1411 | — |
| LMArena Multi-Turn | 1427 | — |

## FAQ

### Is GLM-4.6 better than Qwen3 14B?

GLM-4.6 is the stronger model overall, scoring 40.9 to 35.0 on the Noometry Index. Qwen3 14B costs 1.6× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.

### Which is cheaper, GLM-4.6 or Qwen3 14B?

Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.

### Is GLM-4.6 or Qwen3 14B better for coding?

GLM-4.6 scores higher on coding benchmarks: 39.9 versus 36.7 in the Noometry coding category.

### Which has the bigger context window?

GLM-4.6 does, with 205K tokens against 131K.

### How many benchmarks do GLM-4.6 and Qwen3 14B share?

5 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Qwen3 14B has 12.