# GLM-4.7 vs Qwen3-30B-A3B

> GLM-4.7 is the stronger model overall, scoring 42.0 to 38.9 on the Noometry Index. Qwen3-30B-A3B costs 4.7× less per token, which makes it the better buy when GLM-4.7's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-4-7-vs-qwen3-30b-a3b
- Last updated: 2026-10-12
- Shared benchmarks: 23

## Summary

- They share 23 benchmarks with published results for both. GLM-4.7 scores higher in 8 categories and Qwen3-30B-A3B in 1 category; 9 gaps are clear of the uncertainty.
- The widest gap is in long context, where GLM-4.7 leads 42.8 to 31.0.
- The biggest single-benchmark swing is GPQA Diamond: 83.3% for GLM-4.7 and 70.1% for Qwen3-30B-A3B.
- Qwen3-30B-A3B is cheaper at $0.12 / $0.50 per million input/output tokens, against $0.60 / $2.20 for GLM-4.7.
- GLM-4.7 accepts more context: 205K tokens versus 41K.

## Snapshot

| | GLM-4.7 | Qwen3-30B-A3B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 42.0 | 38.9 |
| Rank | 124 | 179 |
| Context | 205K | 41K |
| Input $/M | $0.60 | $0.12 |
| Output $/M | $2.20 | $0.50 |
| Weights | Open | Open |

## Coding

- GLM-4.7: 44.0 (#79)
- Qwen3-30B-A3B: 37.5 (#194)

| Benchmark | GLM-4.7 | Qwen3-30B-A3B |
|---|---|---|
| SciCode | 45.1% | 33.3% |
| LMArena Coding | 1454 | 1416 |
| LMArena WebDev | 1435 | — |
| WeirdML | — | 29.8% |
| ALE-Bench | 399.48 | — |

## Agentic & Tool Use

- GLM-4.7: 26.5 (#103)
- Qwen3-30B-A3B: 29.8 (#82)

| Benchmark | GLM-4.7 | Qwen3-30B-A3B |
|---|---|---|
| Terminal-Bench | 33.4% | — |
| Berkeley Function Calling Leaderboard | — | 41.4% |
| Vending-Bench 2 | 2,377 | — |

## Reasoning

- GLM-4.7: 24.3 (#164)
- Qwen3-30B-A3B: 22.2 (#204)

| Benchmark | GLM-4.7 | Qwen3-30B-A3B |
|---|---|---|
| CritPt | 1.7% | 0.3% |
| Chess Puzzles | 6% | 8% |
| LMArena Hard Prompts | 1443 | 1398 |
| Epoch Capabilities Index | 143.51 | 139.63 |
| SimpleBench | 47.7% | — |
| Kagi LLM Benchmark | — | 54.9% |
| DTBench | — | 69.3% |
| LMCA | — | 22.4% |

## Math

- GLM-4.7: 38.6 (#135)
- Qwen3-30B-A3B: 37.4 (#157)

| Benchmark | GLM-4.7 | Qwen3-30B-A3B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 83.3% | 70.3% |
| LMArena Math | 1423 | 1394 |
| MathArena Final-Answer Competitions | — | 47.8% |
| ProofBench | 6% | — |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |

## Knowledge

- GLM-4.7: 47.0 (#80)
- Qwen3-30B-A3B: 41.8 (#105)

| Benchmark | GLM-4.7 | Qwen3-30B-A3B |
|---|---|---|
| GPQA Diamond | 83.3% | 70.1% |
| LMArena Expert | 1424 | 1396 |
| SimpleQA Verified | 32.2% | — |
| Confabulations | — | 12.3% |
| Vectara Hallucination Rate | 11.7% | — |

## Multilingual

- GLM-4.7: 52.8 (#79)
- Qwen3-30B-A3B: 49.5 (#132)

| Benchmark | GLM-4.7 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Non-English | 1417 | 1372 |
| LMArena Chinese | 1495 | 1433 |
| LMArena French | 1432 | 1418 |
| LMArena German | 1424 | 1380 |
| LMArena Japanese | 1439 | 1337 |
| LMArena Korean | 1399 | 1331 |
| LMArena Russian | 1423 | 1370 |
| LMArena Spanish | 1434 | 1404 |

## Instruction Following

- GLM-4.7: 74.4 (#95)
- Qwen3-30B-A3B: 72.0 (#142)

| Benchmark | GLM-4.7 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Instruction Following | 1411 | 1363 |

## Long Context

- GLM-4.7: 42.8 (#116)
- Qwen3-30B-A3B: 31.0 (#283)

| Benchmark | GLM-4.7 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Longer Query | 1432 | 1379 |
| Fiction.LiveBench | — | 40.6% |
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |

## Writing & Preference

- GLM-4.7: 60.9 (#93)
- Qwen3-30B-A3B: 55.6 (#143)

| Benchmark | GLM-4.7 | Qwen3-30B-A3B |
|---|---|---|
| LMArena Text | 1435 | 1384 |
| LMArena Creative Writing | 1401 | 1317 |
| LMArena Multi-Turn | 1446 | 1378 |
| Short-Story Creative Writing | — | 75.3% |
| EQ-Bench Creative Writing | 1413 | — |

## FAQ

### Is GLM-4.7 better than Qwen3-30B-A3B?

GLM-4.7 is the stronger model overall, scoring 42.0 to 38.9 on the Noometry Index. Qwen3-30B-A3B costs 4.7× less per token, which makes it the better buy when GLM-4.7's lead doesn't matter for your workload.

### Which is cheaper, GLM-4.7 or Qwen3-30B-A3B?

Qwen3-30B-A3B is cheaper. It lists at $0.12 per million input tokens and $0.50 per million output tokens; GLM-4.7 lists at $0.60 and $2.20.

### Is GLM-4.7 or Qwen3-30B-A3B better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 37.5 in the Noometry coding category.

### Which has the bigger context window?

GLM-4.7 does, with 205K tokens against 41K.

### How many benchmarks do GLM-4.7 and Qwen3-30B-A3B share?

23 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Qwen3-30B-A3B has 32.