# GLM-4.5 vs Qwen3 235B-A22B

> Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 42.0 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-5-vs-qwen3-235b-a22b
- Last updated: 2026-10-12
- Shared benchmarks: 23

## Summary

- They share 23 benchmarks with published results for both. GLM-4.5 scores higher in 3 categories and Qwen3 235B-A22B in 5 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Qwen3 235B-A22B leads 49.6 to 35.9.
- The biggest single-benchmark swing is Fiction.LiveBench: 58.3% for GLM-4.5 and 75% for Qwen3 235B-A22B.
- GLM-4.5 is cheaper at $0.60 / $2.20 per million input/output tokens, against $0.70 / $2.80 for Qwen3 235B-A22B.

## Snapshot

| | GLM-4.5 | Qwen3 235B-A22B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 42.0 | 43.5 |
| Rank | 122 | 91 |
| Context | 131K | 131K |
| Input $/M | $0.60 | $0.70 |
| Output $/M | $2.20 | $2.80 |
| Weights | Open | Open |

## Coding

- GLM-4.5: 41.4 (#125)
- Qwen3 235B-A22B: 44.3 (#75)

| Benchmark | GLM-4.5 | Qwen3 235B-A22B |
|---|---|---|
| WeirdML | 40.6% | 41% |
| LMArena Coding | 1434 | 1445 |
| SWE-bench Verified (bash only) | 54.2% | — |
| Aider Polyglot | — | 59.6% |
| SciCode | — | 42.4% |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |

## Agentic & Tool Use

- GLM-4.5: —
- Qwen3 235B-A22B: 33.9 (#51)

| Benchmark | GLM-4.5 | Qwen3 235B-A22B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 52.1% |
| Vending-Bench 2 | — | -11.34 |

## Reasoning

- GLM-4.5: 28.6 (#100)
- Qwen3 235B-A22B: 15.7 (#311)

| Benchmark | GLM-4.5 | Qwen3 235B-A22B |
|---|---|---|
| Kagi LLM Benchmark | 57.9% | 69.4% |
| LMArena Hard Prompts | 1429 | 1433 |
| ARC-AGI-2 | — | 1.3% |
| SimpleBench | — | 31% |
| ARC-AGI-1 | — | 11% |
| CritPt | — | 0% |
| Chess Puzzles | — | 12% |
| Mystery Game Puzzles | — | 9% |
| DTBench | — | 80.3% |
| LMCA | — | 29.3% |
| Epoch Capabilities Index | — | 143.85 |
| ForecastBench | — | 59.7 |

## Math

- GLM-4.5: 39.0 (#116)
- Qwen3 235B-A22B: 50.4 (#57)

| Benchmark | GLM-4.5 | Qwen3 235B-A22B |
|---|---|---|
| LMArena Math | 1427 | 1432 |
| OTIS Mock AIME 2024-2025 | — | 86.7% |
| Omni-MATH | — | 71.8% |
| MATH Level 5 | — | 68.9% |
| FrontierMath (Feb 2025 set) | — | 8.5% |
| FrontierMath Tier 4 (v1) | — | 0% |

## Knowledge

- GLM-4.5: 35.9 (#179)
- Qwen3 235B-A22B: 49.6 (#73)

| Benchmark | GLM-4.5 | Qwen3 235B-A22B |
|---|---|---|
| Confabulations | 11.3% | 15.6% |
| LMArena Expert | 1433 | 1463 |
| GPQA Diamond | — | 80.1% |
| Humanity's Last Exam | 8.3% | — |
| SimpleQA Verified | — | 40.4% |
| MMLU-Pro | — | 84.4% |
| Vectara Hallucination Rate | — | 9.3% |
| GPQA (HELM) | — | 72.7% |

## Multilingual

- GLM-4.5: 52.8 (#77)
- Qwen3 235B-A22B: 52.3 (#89)

| Benchmark | GLM-4.5 | Qwen3 235B-A22B |
|---|---|---|
| LMArena Non-English | 1417 | 1409 |
| LMArena Chinese | 1465 | 1481 |
| LMArena French | 1418 | 1445 |
| LMArena German | 1407 | 1433 |
| LMArena Japanese | 1415 | 1399 |
| LMArena Korean | 1380 | 1391 |
| LMArena Russian | 1414 | 1411 |
| LMArena Spanish | 1454 | 1430 |

## Instruction Following

- GLM-4.5: 74.1 (#104)
- Qwen3 235B-A22B: 72.6 (#136)

| Benchmark | GLM-4.5 | Qwen3 235B-A22B |
|---|---|---|
| LMArena Instruction Following | 1404 | 1408 |
| IFEval | — | 83.5% |

## Long Context

- GLM-4.5: 38.2 (#201)
- Qwen3 235B-A22B: 46.1 (#26)

| Benchmark | GLM-4.5 | Qwen3 235B-A22B |
|---|---|---|
| Fiction.LiveBench | 58.3% | 75% |
| LMArena Longer Query | 1412 | 1426 |

## Writing & Preference

- GLM-4.5: 57.5 (#127)
- Qwen3 235B-A22B: 59.6 (#108)

| Benchmark | GLM-4.5 | Qwen3 235B-A22B |
|---|---|---|
| LMArena Text | 1430 | 1419 |
| LMArena Creative Writing | 1395 | 1384 |
| Short-Story Creative Writing | 73.4% | 83% |
| EQ-Bench Creative Writing | 1343 | 1366 |
| LMArena Multi-Turn | 1415 | 1432 |
| WildBench | — | 86.6% |

## FAQ

### Is GLM-4.5 better than Qwen3 235B-A22B?

Qwen3 235B-A22B is the stronger model overall, scoring 43.5 to 42.0 on the Noometry Index.

### Which is cheaper, GLM-4.5 or Qwen3 235B-A22B?

GLM-4.5 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Qwen3 235B-A22B lists at $0.70 and $2.80.

### Is GLM-4.5 or Qwen3 235B-A22B better for coding?

Qwen3 235B-A22B scores higher on coding benchmarks: 44.3 versus 41.4 in the Noometry coding category.

### Which has the bigger context window?

Both accept 131K tokens.

### How many benchmarks do GLM-4.5 and Qwen3 235B-A22B share?

23 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Qwen3 235B-A22B has 49.