Model comparison
GLM-4.5V vs o3-pro
o3-pro is the stronger model overall, scoring 42.9 to 39.8 on the Noometry Index. GLM-4.5V costs 39× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
Summary
- They share 1 benchmark with published results for both. GLM-4.5V scores higher in 2 categories and o3-pro in 3 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in long context, where o3-pro leads 72.2 to 39.6.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 59.8% for GLM-4.5V and 72.1% for o3-pro.
- GLM-4.5V is cheaper at $0.60 / $1.80 per million input/output tokens, against $20 / $80 for o3-pro.
- o3-pro accepts more context: 200K tokens versus 64K.
- GLM-4.5V has downloadable open weights; the other is API-only.
Side by side
| GLM-4.5V | o3-pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 39.8 | 42.9 |
| Released | 2025-08-11 | 2025-06-10 |
| Weights | Open | Proprietary |
| Context window | 64K | 200K |
| Max output | 16K | 100K |
| Input $ / M tokens | $0.60 | $20 |
| Output $ / M tokens | $1.80 | $80 |
| Results tracked | 15 | 12 |
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Category by category
Coding o3-pro leads
GLM-4.5V: 39.5 (#155), o3-pro: 55.5 (#24)
| Benchmark | GLM-4.5V | o3-pro |
|---|---|---|
| Aider Polyglot | — | 84.9% |
| WeirdML | — | 58.2% |
| LMArena Coding | 1347 | — |
Reasoning GLM-4.5V leads
GLM-4.5V: 27.4 (#119), o3-pro: 23.8 (#171)
| Benchmark | GLM-4.5V | o3-pro |
|---|---|---|
| Kagi LLM Benchmark | 59.8% | 72.1% |
| ARC-AGI-2 | — | 4.9% |
| ARC-AGI-1 | — | 59.3% |
| LMArena Hard Prompts | 1334 | — |
| DTBench | — | 86.9% |
| LMCA | — | 38.5% |
| Epoch Capabilities Index | — | 147.42 |
Math Not comparable
GLM-4.5V: 37.4 (#159), o3-pro: —
| Benchmark | GLM-4.5V | o3-pro |
|---|---|---|
| LMArena Math | 1354 | — |
Knowledge GLM-4.5V leads
GLM-4.5V: 37.5 (#156), o3-pro: 29.5 (#238)
| Benchmark | GLM-4.5V | o3-pro |
|---|---|---|
| Confabulations | — | 14.2% |
| Vectara Hallucination Rate | — | 23.3% |
| LMArena Expert | 1353 | — |
Multimodal Not comparable
GLM-4.5V: 34.3 (#92), o3-pro: —
| Benchmark | GLM-4.5V | o3-pro |
|---|---|---|
| LMArena Vision | 1154 | — |
Multilingual Not comparable
GLM-4.5V: 44.6 (#177), o3-pro: —
| Benchmark | GLM-4.5V | o3-pro |
|---|---|---|
| LMArena Non-English | 1303 | — |
| LMArena Chinese | 1337 | — |
| LMArena Russian | 1298 | — |
| LMArena Spanish | 1336 | — |
Instruction Following Not comparable
GLM-4.5V: 69.2 (#175), o3-pro: —
| Benchmark | GLM-4.5V | o3-pro |
|---|---|---|
| LMArena Instruction Following | 1311 | — |
Long Context o3-pro leads
GLM-4.5V: 39.6 (#171), o3-pro: 72.2 (#1)
| Benchmark | GLM-4.5V | o3-pro |
|---|---|---|
| Fiction.LiveBench | — | 97.2% |
| LMArena Longer Query | 1304 | — |
Writing & Preference o3-pro leads
GLM-4.5V: 52.5 (#170), o3-pro: 57.1 (#133)
| Benchmark | GLM-4.5V | o3-pro |
|---|---|---|
| LMArena Text | 1333 | — |
| LMArena Creative Writing | 1295 | — |
| Short-Story Creative Writing | — | 84.4% |
| LMArena Multi-Turn | 1332 | — |
Frequently asked questions
Is GLM-4.5V better than o3-pro?
o3-pro is the stronger model overall, scoring 42.9 to 39.8 on the Noometry Index. GLM-4.5V costs 39× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Which is cheaper, GLM-4.5V or o3-pro?
GLM-4.5V is cheaper. It lists at $0.60 per million input tokens and $1.80 per million output tokens; o3-pro lists at $20 and $80.
Is GLM-4.5V or o3-pro better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 39.5 in the Noometry coding category.
Which has the bigger context window?
o3-pro does, with 200K tokens against 64K.
How many benchmarks do GLM-4.5V and o3-pro share?
1 benchmark has published results for both models. GLM-4.5V has 15 scored results on Noometry and o3-pro has 12.