Model comparison
GLM-5.3 vs o3-pro
GLM-5.3 is the stronger model overall, scoring 54.8 to 42.9 on the Noometry Index.
Last verified . 4 shared benchmarks.
Summary
- They share 4 benchmarks with published results for both. GLM-5.3 scores higher in 4 categories and o3-pro in 1 category; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.3 leads 58.3 to 29.5.
- The biggest single-benchmark swing is WeirdML: 75.4% for GLM-5.3 and 58.2% for o3-pro.
- GLM-5.3 is cheaper at $1.40 / $4.40 per million input/output tokens, against $20 / $80 for o3-pro.
- GLM-5.3 accepts more context: 1M tokens versus 200K.
- GLM-5.3 has downloadable open weights; the other is API-only.
Side by side
| GLM-5.3 | o3-pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 54.8 | 42.9 |
| Released | 2026-08-14 | 2025-06-10 |
| Weights | Open | Proprietary |
| Context window | 1M | 200K |
| Max output | 131K | 100K |
| Input $ / M tokens | $1.40 | $20 |
| Output $ / M tokens | $4.40 | $80 |
| Results tracked | 42 | 12 |
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Category by category
Coding GLM-5.3 leads
GLM-5.3: 59.5 (#14), o3-pro: 55.5 (#24)
| Benchmark | GLM-5.3 | o3-pro |
|---|---|---|
| WeirdML | 75.4% | 58.2% |
| DeepSWE | 69% | — |
| FrontierCode | 40.1% | — |
| Aider Polyglot | — | 84.9% |
| CursorBench | 42.6% | — |
| LMArena WebDev | 1622 | — |
| FrontierSWE | 30.2% | — |
| SciCode | 59% | — |
| LMArena Coding | 1496 | — |
| ALE-Bench | 1,317 | — |
Agentic & Tool Use Not comparable
GLM-5.3: 36.4 (#38), o3-pro: —
| Benchmark | GLM-5.3 | o3-pro |
|---|---|---|
| APEX-Agents | 56.6% | — |
| Vending-Bench 2 | 8,164 | — |
Reasoning GLM-5.3 leads
GLM-5.3: 46.1 (#46), o3-pro: 23.8 (#171)
| Benchmark | GLM-5.3 | o3-pro |
|---|---|---|
| DTBench | 87.7% | 86.9% |
| LMCA | 55.5% | 38.5% |
| Epoch Capabilities Index | 155.61 | 147.42 |
| ARC-AGI-2 | — | 4.9% |
| Kagi LLM Benchmark | — | 72.1% |
| NYT Connections (extended) | 74.2% | — |
| ARC-AGI-1 | — | 59.3% |
| CritPt | 19.1% | — |
| Chess Puzzles | 21% | — |
| LMArena Hard Prompts | 1489 | — |
| Mystery Game Puzzles | 33% | — |
| Bench to the Future 3 | 0.15 | — |
Math Not comparable
GLM-5.3: 62.3 (#33), o3-pro: —
| Benchmark | GLM-5.3 | o3-pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | 68.8% | — |
| FrontierMath Tier 4 | 29.3% | — |
| OTIS Mock AIME 2024-2025 | 91.1% | — |
| ProofBench | 49% | — |
| LMArena Math | 1489 | — |
Knowledge GLM-5.3 leads
GLM-5.3: 58.3 (#37), o3-pro: 29.5 (#238)
| Benchmark | GLM-5.3 | o3-pro |
|---|---|---|
| GPQA Diamond | 90.9% | — |
| SimpleQA Verified | 41% | — |
| Confabulations | — | 14.2% |
| Vectara Hallucination Rate | — | 23.3% |
| LMArena Expert | 1516 | — |
Multilingual Not comparable
GLM-5.3: 55.7 (#28), o3-pro: —
| Benchmark | GLM-5.3 | o3-pro |
|---|---|---|
| LMArena Non-English | 1457 | — |
| LMArena Chinese | 1528 | — |
| LMArena French | 1499 | — |
| LMArena German | 1499 | — |
| LMArena Japanese | 1453 | — |
| LMArena Korean | 1472 | — |
| LMArena Russian | 1463 | — |
| LMArena Spanish | 1460 | — |
Instruction Following Not comparable
GLM-5.3: 77.5 (#23), o3-pro: —
| Benchmark | GLM-5.3 | o3-pro |
|---|---|---|
| LMArena Instruction Following | 1477 | — |
Long Context o3-pro leads
GLM-5.3: 45.4 (#41), o3-pro: 72.2 (#1)
| Benchmark | GLM-5.3 | o3-pro |
|---|---|---|
| Fiction.LiveBench | — | 97.2% |
| LMArena Longer Query | 1482 | — |
Writing & Preference GLM-5.3 leads
GLM-5.3: 75.7 (#6), o3-pro: 57.1 (#133)
| Benchmark | GLM-5.3 | o3-pro |
|---|---|---|
| LMArena Text | 1471 | — |
| LMArena Creative Writing | 1457 | — |
| Short-Story Creative Writing | — | 84.4% |
| EQ-Bench Creative Writing | 2075 | — |
| LMArena Multi-Turn | 1472 | — |
Frequently asked questions
Is GLM-5.3 better than o3-pro?
GLM-5.3 is the stronger model overall, scoring 54.8 to 42.9 on the Noometry Index.
Which is cheaper, GLM-5.3 or o3-pro?
GLM-5.3 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; o3-pro lists at $20 and $80.
Is GLM-5.3 or o3-pro better for coding?
GLM-5.3 scores higher on coding benchmarks: 59.5 versus 55.5 in the Noometry coding category.
Which has the bigger context window?
GLM-5.3 does, with 1M tokens against 200K.
How many benchmarks do GLM-5.3 and o3-pro share?
4 benchmarks have published results for both models. GLM-5.3 has 42 scored results on Noometry and o3-pro has 12.