Model comparison
GLM-5V-Turbo vs Qwen2.5-Coder-32B
GLM-5V-Turbo is the stronger model overall, scoring 43.8 to 33.4 on the Noometry Index. Qwen2.5-Coder-32B costs 2.6× less per token, which makes it the better buy when GLM-5V-Turbo's lead doesn't matter for your workload.
Last verified . 12 shared benchmarks.
Alibaba (Qwen)Summary
- They share 12 benchmarks with published results for both. GLM-5V-Turbo scores higher in 8 categories and Qwen2.5-Coder-32B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-5V-Turbo leads 62.5 to 41.6.
- Qwen2.5-Coder-32B is cheaper at $0.66 / $1 per million input/output tokens, against $1.20 / $4 for GLM-5V-Turbo.
- GLM-5V-Turbo accepts more context: 200K tokens versus 33K.
- Qwen2.5-Coder-32B has downloadable open weights; the other is API-only.
Side by side
| GLM-5V-Turbo | Qwen2.5-Coder-32B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 43.8 | 33.4 |
| Released | 2026-04-01 | 2024-09-18 |
| Weights | Proprietary | Open |
| Context window | 200K | 33K |
| Max output | 131K | 29K |
| Input $ / M tokens | $1.20 | $0.66 |
| Output $ / M tokens | $4 | $1 |
| Results tracked | 19 | 31 |
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Category by category
Coding GLM-5V-Turbo leads
GLM-5V-Turbo: 42.1 (#111), Qwen2.5-Coder-32B: 22.6 (#333)
| Benchmark | GLM-5V-Turbo | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Coding | 1466 | 1276 |
| SWE-bench Verified (bash only) | — | 9% |
| Aider Polyglot | — | 16.4% |
| LMArena WebDev | 1401 | — |
| BigCodeBench Instruct | — | 49% |
| LiveBench Coding | — | 56.9% |
| BigCodeBench Complete | — | 58% |
| HumanEval+ | — | 87.2% |
| MBPP+ | — | 77% |
Reasoning GLM-5V-Turbo leads
GLM-5V-Turbo: 29.7 (#89), Qwen2.5-Coder-32B: 21.2 (#225)
| Benchmark | GLM-5V-Turbo | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Hard Prompts | 1443 | 1251 |
| LiveBench Reasoning | — | 42.1% |
| LiveBench Data Analysis | — | 49.9% |
| Epoch Capabilities Index | — | 119.49 |
| HellaSwag | — | 83% |
| LiveBench | — | 46.2% |
| WinoGrande | — | 80.8% |
Math GLM-5V-Turbo leads
GLM-5V-Turbo: 39.4 (#106), Qwen2.5-Coder-32B: 33.3 (#204)
| Benchmark | GLM-5V-Turbo | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Math | 1441 | 1251 |
| LiveBench Math | — | 46.6% |
| GSM8K | — | 93% |
Knowledge GLM-5V-Turbo leads
GLM-5V-Turbo: 40.6 (#117), Qwen2.5-Coder-32B: 33.4 (#203)
| Benchmark | GLM-5V-Turbo | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Expert | 1452 | 1221 |
| ARC (AI2) Challenge | — | 70.5% |
| MMLU | — | 79.1% |
Multimodal Not comparable
GLM-5V-Turbo: 40.9 (#42), Qwen2.5-Coder-32B: —
| Benchmark | GLM-5V-Turbo | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Vision | 1264 | — |
| LMArena Document | 1416 | — |
Multilingual GLM-5V-Turbo leads
GLM-5V-Turbo: 53.0 (#73), Qwen2.5-Coder-32B: 37.8 (#235)
| Benchmark | GLM-5V-Turbo | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Non-English | 1420 | 1205 |
| LMArena Chinese | 1488 | 1222 |
| LMArena Russian | 1431 | 1228 |
| LMArena French | 1444 | — |
| LMArena German | 1423 | — |
| LMArena Korean | 1396 | — |
| LMArena Spanish | 1450 | — |
Instruction Following GLM-5V-Turbo leads
GLM-5V-Turbo: 75.0 (#80), Qwen2.5-Coder-32B: 61.4 (#245)
| Benchmark | GLM-5V-Turbo | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Instruction Following | 1423 | 1223 |
| LiveBench Instruction Following | — | 58.7% |
Long Context GLM-5V-Turbo leads
GLM-5V-Turbo: 44.0 (#80), Qwen2.5-Coder-32B: 38.0 (#208)
| Benchmark | GLM-5V-Turbo | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Longer Query | 1438 | 1251 |
Writing & Preference GLM-5V-Turbo leads
GLM-5V-Turbo: 62.5 (#73), Qwen2.5-Coder-32B: 41.6 (#240)
| Benchmark | GLM-5V-Turbo | Qwen2.5-Coder-32B |
|---|---|---|
| LMArena Text | 1437 | 1230 |
| LMArena Creative Writing | 1416 | 1174 |
| LMArena Multi-Turn | 1432 | 1222 |
| LiveBench Language | — | 23.3% |
Frequently asked questions
Is GLM-5V-Turbo better than Qwen2.5-Coder-32B?
GLM-5V-Turbo is the stronger model overall, scoring 43.8 to 33.4 on the Noometry Index. Qwen2.5-Coder-32B costs 2.6× less per token, which makes it the better buy when GLM-5V-Turbo's lead doesn't matter for your workload.
Which is cheaper, GLM-5V-Turbo or Qwen2.5-Coder-32B?
Qwen2.5-Coder-32B is cheaper. It lists at $0.66 per million input tokens and $1 per million output tokens; GLM-5V-Turbo lists at $1.20 and $4.
Is GLM-5V-Turbo or Qwen2.5-Coder-32B better for coding?
GLM-5V-Turbo scores higher on coding benchmarks: 42.1 versus 22.6 in the Noometry coding category.
Which has the bigger context window?
GLM-5V-Turbo does, with 200K tokens against 33K.
How many benchmarks do GLM-5V-Turbo and Qwen2.5-Coder-32B share?
12 benchmarks have published results for both models. GLM-5V-Turbo has 19 scored results on Noometry and Qwen2.5-Coder-32B has 31.