Model comparison
GLM-5V-Turbo vs o3-pro
GLM-5V-Turbo and o3-pro score almost the same on the Noometry Index (43.8 vs 42.9), so choose on price, context window or the category you care about most.
Last verified . 0 shared benchmarks.
Summary
- The widest gap is in long context, where o3-pro leads 72.2 to 44.0.
- GLM-5V-Turbo is cheaper at $1.20 / $4 per million input/output tokens, against $20 / $80 for o3-pro.
Side by side
| GLM-5V-Turbo | o3-pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 43.8 | 42.9 |
| Released | 2026-04-01 | 2025-06-10 |
| Weights | Proprietary | Proprietary |
| Context window | 200K | 200K |
| Max output | 131K | 100K |
| Input $ / M tokens | $1.20 | $20 |
| Output $ / M tokens | $4 | $80 |
| Results tracked | 19 | 12 |
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Category by category
Coding o3-pro leads
GLM-5V-Turbo: 42.1 (#111), o3-pro: 55.5 (#24)
| Benchmark | GLM-5V-Turbo | o3-pro |
|---|---|---|
| Aider Polyglot | — | 84.9% |
| LMArena WebDev | 1401 | — |
| WeirdML | — | 58.2% |
| LMArena Coding | 1466 | — |
Reasoning GLM-5V-Turbo leads
GLM-5V-Turbo: 29.7 (#89), o3-pro: 23.8 (#171)
| Benchmark | GLM-5V-Turbo | o3-pro |
|---|---|---|
| ARC-AGI-2 | — | 4.9% |
| Kagi LLM Benchmark | — | 72.1% |
| ARC-AGI-1 | — | 59.3% |
| LMArena Hard Prompts | 1443 | — |
| DTBench | — | 86.9% |
| LMCA | — | 38.5% |
| Epoch Capabilities Index | — | 147.42 |
Math Not comparable
GLM-5V-Turbo: 39.4 (#106), o3-pro: —
| Benchmark | GLM-5V-Turbo | o3-pro |
|---|---|---|
| LMArena Math | 1441 | — |
Knowledge GLM-5V-Turbo leads
GLM-5V-Turbo: 40.6 (#117), o3-pro: 29.5 (#238)
| Benchmark | GLM-5V-Turbo | o3-pro |
|---|---|---|
| Confabulations | — | 14.2% |
| Vectara Hallucination Rate | — | 23.3% |
| LMArena Expert | 1452 | — |
Multimodal Not comparable
GLM-5V-Turbo: 40.9 (#42), o3-pro: —
| Benchmark | GLM-5V-Turbo | o3-pro |
|---|---|---|
| LMArena Vision | 1264 | — |
| LMArena Document | 1416 | — |
Multilingual Not comparable
GLM-5V-Turbo: 53.0 (#73), o3-pro: —
| Benchmark | GLM-5V-Turbo | o3-pro |
|---|---|---|
| LMArena Non-English | 1420 | — |
| LMArena Chinese | 1488 | — |
| LMArena French | 1444 | — |
| LMArena German | 1423 | — |
| LMArena Korean | 1396 | — |
| LMArena Russian | 1431 | — |
| LMArena Spanish | 1450 | — |
Instruction Following Not comparable
GLM-5V-Turbo: 75.0 (#80), o3-pro: —
| Benchmark | GLM-5V-Turbo | o3-pro |
|---|---|---|
| LMArena Instruction Following | 1423 | — |
Long Context o3-pro leads
GLM-5V-Turbo: 44.0 (#80), o3-pro: 72.2 (#1)
| Benchmark | GLM-5V-Turbo | o3-pro |
|---|---|---|
| Fiction.LiveBench | — | 97.2% |
| LMArena Longer Query | 1438 | — |
Writing & Preference GLM-5V-Turbo leads
GLM-5V-Turbo: 62.5 (#73), o3-pro: 57.1 (#133)
| Benchmark | GLM-5V-Turbo | o3-pro |
|---|---|---|
| LMArena Text | 1437 | — |
| LMArena Creative Writing | 1416 | — |
| Short-Story Creative Writing | — | 84.4% |
| LMArena Multi-Turn | 1432 | — |
Frequently asked questions
Is GLM-5V-Turbo better than o3-pro?
GLM-5V-Turbo and o3-pro score almost the same on the Noometry Index (43.8 vs 42.9), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-5V-Turbo or o3-pro?
GLM-5V-Turbo is cheaper. It lists at $1.20 per million input tokens and $4 per million output tokens; o3-pro lists at $20 and $80.
Is GLM-5V-Turbo or o3-pro better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 42.1 in the Noometry coding category.
Which has the bigger context window?
Both accept 200K tokens.
How many benchmarks do GLM-5V-Turbo and o3-pro share?
0 benchmarks have published results for both models. GLM-5V-Turbo has 19 scored results on Noometry and o3-pro has 12.