Model comparison
GLM-4.5 vs Qwen3-4B
GLM-4.5 is the stronger model overall, scoring 42.0 to 31.9 on the Noometry Index.
Last verified . 0 shared benchmarks.
Alibaba (Qwen)Summary
- The widest gap is in reasoning, where GLM-4.5 leads 28.6 to 19.2.
Side by side
| GLM-4.5 | Qwen3-4B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 42.0 | 31.9 |
| Released | 2025-07-27 | 2025-04-29 |
| Weights | Open | Open |
| Context window | 131K | — |
| Max output | 98K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 27 | 6 |
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Category by category
Coding Not comparable
GLM-4.5: 41.4 (#125), Qwen3-4B: —
| Benchmark | GLM-4.5 | Qwen3-4B |
|---|---|---|
| SWE-bench Verified (bash only) | 54.2% | — |
| WeirdML | 40.6% | — |
| LMArena Coding | 1434 | — |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |
Agentic & Tool Use Not comparable
GLM-4.5: —, Qwen3-4B: 27.6 (#100)
| Benchmark | GLM-4.5 | Qwen3-4B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 35.7% |
Reasoning GLM-4.5 leads
GLM-4.5: 28.6 (#100), Qwen3-4B: 19.2 (#268)
| Benchmark | GLM-4.5 | Qwen3-4B |
|---|---|---|
| Kagi LLM Benchmark | 57.9% | — |
| Chess Puzzles | — | 4% |
| LMArena Hard Prompts | 1429 | — |
Math GLM-4.5 leads
GLM-4.5: 39.0 (#116), Qwen3-4B: 29.7 (#240)
| Benchmark | GLM-4.5 | Qwen3-4B |
|---|---|---|
| MathArena Final-Answer Competitions | — | 38.5% |
| OTIS Mock AIME 2024-2025 | — | 52.2% |
| LMArena Math | 1427 | — |
Knowledge GLM-4.5 leads
GLM-4.5: 35.9 (#179), Qwen3-4B: 33.0 (#208)
| Benchmark | GLM-4.5 | Qwen3-4B |
|---|---|---|
| GPQA Diamond | — | 52.3% |
| Humanity's Last Exam | 8.3% | — |
| Confabulations | 11.3% | — |
| Vectara Hallucination Rate | — | 5.7% |
| LMArena Expert | 1433 | — |
Multilingual Not comparable
GLM-4.5: 52.8 (#77), Qwen3-4B: —
| Benchmark | GLM-4.5 | Qwen3-4B |
|---|---|---|
| LMArena Non-English | 1417 | — |
| LMArena Chinese | 1465 | — |
| LMArena French | 1418 | — |
| LMArena German | 1407 | — |
| LMArena Japanese | 1415 | — |
| LMArena Korean | 1380 | — |
| LMArena Russian | 1414 | — |
| LMArena Spanish | 1454 | — |
Instruction Following Not comparable
GLM-4.5: 74.1 (#104), Qwen3-4B: —
| Benchmark | GLM-4.5 | Qwen3-4B |
|---|---|---|
| LMArena Instruction Following | 1404 | — |
Long Context Not comparable
GLM-4.5: 38.2 (#201), Qwen3-4B: —
| Benchmark | GLM-4.5 | Qwen3-4B |
|---|---|---|
| Fiction.LiveBench | 58.3% | — |
| LMArena Longer Query | 1412 | — |
Writing & Preference Not comparable
GLM-4.5: 57.5 (#127), Qwen3-4B: —
| Benchmark | GLM-4.5 | Qwen3-4B |
|---|---|---|
| LMArena Text | 1430 | — |
| LMArena Creative Writing | 1395 | — |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
| LMArena Multi-Turn | 1415 | — |
Frequently asked questions
Is GLM-4.5 better than Qwen3-4B?
GLM-4.5 is the stronger model overall, scoring 42.0 to 31.9 on the Noometry Index.
How many benchmarks do GLM-4.5 and Qwen3-4B share?
0 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Qwen3-4B has 6.