Model comparison
GLM-4.6 vs o3-pro
o3-pro is the stronger model overall, scoring 42.9 to 41.4 on the Noometry Index. GLM-4.6 costs 35× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Last verified . 2 shared benchmarks.
Summary
- They share 2 benchmarks with published results for both. GLM-4.6 scores higher in 2 categories and o3-pro in 3 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in long context, where o3-pro leads 72.2 to 43.4.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 47.4% for GLM-4.6 and 72.1% for o3-pro.
- GLM-4.6 is cheaper at $0.60 / $2.20 per million input/output tokens, against $20 / $80 for o3-pro.
- GLM-4.6 accepts more context: 205K tokens versus 200K.
- GLM-4.6 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.6 | o3-pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 41.4 | 42.9 |
| Released | 2025-09-30 | 2025-06-10 |
| Weights | Open | Proprietary |
| Context window | 205K | 200K |
| Max output | 131K | 100K |
| Input $ / M tokens | $0.60 | $20 |
| Output $ / M tokens | $2.20 | $80 |
| Results tracked | 29 | 12 |
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Category by category
Coding o3-pro leads
GLM-4.6: 40.1 (#148), o3-pro: 55.5 (#24)
| Benchmark | GLM-4.6 | o3-pro |
|---|---|---|
| SWE-bench Verified (bash only) | 55.4% | — |
| Aider Polyglot | — | 84.9% |
| LMArena WebDev | 1340 | — |
| SciCode | 38.4% | — |
| WeirdML | — | 58.2% |
| LMArena Coding | 1449 | — |
| ALE-Bench | 340.82 | — |
Agentic & Tool Use Not comparable
GLM-4.6: 32.3 (#66), o3-pro: —
| Benchmark | GLM-4.6 | o3-pro |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |
Reasoning Too close to call
GLM-4.6: 23.7 (#172), o3-pro: 23.8 (#171)
| Benchmark | GLM-4.6 | o3-pro |
|---|---|---|
| Kagi LLM Benchmark | 47.4% | 72.1% |
| ARC-AGI-2 | — | 4.9% |
| ARC-AGI-1 | — | 59.3% |
| CritPt | 1.1% | — |
| LMArena Hard Prompts | 1440 | — |
| DTBench | — | 86.9% |
| LMCA | — | 38.5% |
| Epoch Capabilities Index | — | 147.42 |
Math Not comparable
GLM-4.6: 39.1 (#111), o3-pro: —
| Benchmark | GLM-4.6 | o3-pro |
|---|---|---|
| LMArena Math | 1432 | — |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |
Knowledge GLM-4.6 leads
GLM-4.6: 40.2 (#124), o3-pro: 29.5 (#238)
| Benchmark | GLM-4.6 | o3-pro |
|---|---|---|
| Vectara Hallucination Rate | 9.5% | 23.3% |
| Confabulations | — | 14.2% |
| LMArena Expert | 1431 | — |
Multilingual Not comparable
GLM-4.6: 53.5 (#66), o3-pro: —
| Benchmark | GLM-4.6 | o3-pro |
|---|---|---|
| LMArena Non-English | 1426 | — |
| LMArena Chinese | 1499 | — |
| LMArena French | 1459 | — |
| LMArena German | 1447 | — |
| LMArena Japanese | 1393 | — |
| LMArena Korean | 1400 | — |
| LMArena Russian | 1419 | — |
| LMArena Spanish | 1436 | — |
Instruction Following Not comparable
GLM-4.6: 74.3 (#98), o3-pro: —
| Benchmark | GLM-4.6 | o3-pro |
|---|---|---|
| LMArena Instruction Following | 1410 | — |
Long Context o3-pro leads
GLM-4.6: 43.4 (#94), o3-pro: 72.2 (#1)
| Benchmark | GLM-4.6 | o3-pro |
|---|---|---|
| Fiction.LiveBench | — | 97.2% |
| LMArena Longer Query | 1422 | — |
Writing & Preference GLM-4.6 leads
GLM-4.6: 61.1 (#90), o3-pro: 57.1 (#133)
| Benchmark | GLM-4.6 | o3-pro |
|---|---|---|
| LMArena Text | 1440 | — |
| LMArena Creative Writing | 1411 | — |
| Short-Story Creative Writing | — | 84.4% |
| EQ-Bench Creative Writing | 1411 | — |
| LMArena Multi-Turn | 1427 | — |
Frequently asked questions
Is GLM-4.6 better than o3-pro?
o3-pro is the stronger model overall, scoring 42.9 to 41.4 on the Noometry Index. GLM-4.6 costs 35× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Which is cheaper, GLM-4.6 or o3-pro?
GLM-4.6 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; o3-pro lists at $20 and $80.
Is GLM-4.6 or o3-pro better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 40.1 in the Noometry coding category.
Which has the bigger context window?
GLM-4.6 does, with 205K tokens against 200K.
How many benchmarks do GLM-4.6 and o3-pro share?
2 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and o3-pro has 12.