Model comparison
GLM-5V-Turbo vs Qwen3 32B
GLM-5V-Turbo is the stronger model overall, scoring 43.1 to 38.8 on the Noometry Index. Qwen3 32B costs 1.6× less per token, which makes it the better buy when GLM-5V-Turbo's lead doesn't matter for your workload.
Last verified . 13 shared benchmarks.
Alibaba (Qwen)Summary
- They share 13 benchmarks with published results for both. GLM-5V-Turbo scores higher in 6 categories and Qwen3 32B in 2 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-5V-Turbo leads 62.6 to 53.1.
- Qwen3 32B is cheaper at $0.70 / $2.80 per million input/output tokens, against $1.20 / $4 for GLM-5V-Turbo.
- GLM-5V-Turbo accepts more context: 200K tokens versus 131K.
- Qwen3 32B has downloadable open weights; the other is API-only.
Side by side
| GLM-5V-Turbo | Qwen3 32B | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 43.1 | 38.8 |
| Released | 2026-04-01 | 2025-04 |
| Weights | Proprietary | Open |
| Context window | 200K | 131K |
| Max output | 131K | 16K |
| Input $ / M tokens | $1.20 | $0.70 |
| Output $ / M tokens | $4 | $2.80 |
| Results tracked | 19 | 26 |
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Category by category
Coding GLM-5V-Turbo leads
GLM-5V-Turbo: 41.8 (#105), Qwen3 32B: 37.3 (#184)
| Benchmark | GLM-5V-Turbo | Qwen3 32B |
|---|---|---|
| LMArena Coding | 1467 | 1358 |
| Aider Polyglot | — | 40% |
| LMArena WebDev | 1400 | — |
| SciCode | — | 35.4% |
Agentic & Tool Use Not comparable
GLM-5V-Turbo: —, Qwen3 32B: 32.3 (#58)
| Benchmark | GLM-5V-Turbo | Qwen3 32B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 48.7% |
Reasoning GLM-5V-Turbo leads
GLM-5V-Turbo: 28.5 (#87), Qwen3 32B: 19.6 (#233)
| Benchmark | GLM-5V-Turbo | Qwen3 32B |
|---|---|---|
| LMArena Hard Prompts | 1443 | 1335 |
| Kagi LLM Benchmark | — | 54.9% |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 5% |
| DTBench | — | 67.5% |
| LMCA | — | 17.3% |
| Epoch Capabilities Index | — | 138.51 |
Math Qwen3 32B leads
GLM-5V-Turbo: 36.6 (#109), Qwen3 32B: 37.9 (#89)
| Benchmark | GLM-5V-Turbo | Qwen3 32B |
|---|---|---|
| LMArena Math | 1440 | 1399 |
| OTIS Mock AIME 2024-2025 | — | 66.9% |
Knowledge Too close to call
GLM-5V-Turbo: 39.9 (#113), Qwen3 32B: 40.0 (#112)
| Benchmark | GLM-5V-Turbo | Qwen3 32B |
|---|---|---|
| LMArena Expert | 1451 | 1362 |
| GPQA Diamond | — | 65.7% |
| Vectara Hallucination Rate | — | 5.9% |
Multimodal Not comparable
GLM-5V-Turbo: 40.1 (#41), Qwen3 32B: —
| Benchmark | GLM-5V-Turbo | Qwen3 32B |
|---|---|---|
| LMArena Vision | 1264 | — |
| LMArena Document | 1416 | — |
Multilingual GLM-5V-Turbo leads
GLM-5V-Turbo: 53.2 (#69), Qwen3 32B: 45.8 (#162)
| Benchmark | GLM-5V-Turbo | Qwen3 32B |
|---|---|---|
| LMArena Non-English | 1420 | 1317 |
| LMArena Chinese | 1488 | 1357 |
| LMArena German | 1422 | 1341 |
| LMArena Russian | 1432 | 1311 |
| LMArena French | 1443 | — |
| LMArena Korean | 1399 | — |
| LMArena Spanish | 1446 | — |
Instruction Following GLM-5V-Turbo leads
GLM-5V-Turbo: 75.1 (#75), Qwen3 32B: 69.1 (#174)
| Benchmark | GLM-5V-Turbo | Qwen3 32B |
|---|---|---|
| LMArena Instruction Following | 1422 | 1305 |
Long Context Too close to call
GLM-5V-Turbo: 44.0 (#76), Qwen3 32B: 43.7 (#83)
| Benchmark | GLM-5V-Turbo | Qwen3 32B |
|---|---|---|
| LMArena Longer Query | 1439 | 1327 |
| Fiction.LiveBench | — | 74.2% |
Writing & Preference GLM-5V-Turbo leads
GLM-5V-Turbo: 62.6 (#69), Qwen3 32B: 53.1 (#158)
| Benchmark | GLM-5V-Turbo | Qwen3 32B |
|---|---|---|
| LMArena Text | 1437 | 1340 |
| LMArena Creative Writing | 1414 | 1297 |
| LMArena Multi-Turn | 1432 | 1331 |
Frequently asked questions
Is GLM-5V-Turbo better than Qwen3 32B?
GLM-5V-Turbo is the stronger model overall, scoring 43.1 to 38.8 on the Noometry Index. Qwen3 32B costs 1.6× 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 Qwen3 32B?
Qwen3 32B is cheaper. It lists at $0.70 per million input tokens and $2.80 per million output tokens; GLM-5V-Turbo lists at $1.20 and $4.
Is GLM-5V-Turbo or Qwen3 32B better for coding?
GLM-5V-Turbo scores higher on coding benchmarks: 41.8 versus 37.3 in the Noometry coding category.
Which has the bigger context window?
GLM-5V-Turbo does, with 200K tokens against 131K.
How many benchmarks do GLM-5V-Turbo and Qwen3 32B share?
13 benchmarks have published results for both models. GLM-5V-Turbo has 19 scored results on Noometry and Qwen3 32B has 26.