Model comparison
GLM-4.7-Flash vs o3-pro
o3-pro is the stronger model overall, scoring 42.9 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 241× 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-4.7-Flash scores higher in 1 category and o3-pro in 4 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in long context, where o3-pro leads 72.2 to 40.9.
- The biggest single-benchmark swing is Vectara Hallucination Rate: 9.3% for GLM-4.7-Flash and 23.3% for o3-pro.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $20 / $80 for o3-pro.
- GLM-4.7-Flash has downloadable open weights; the other is API-only.
Side by side
| GLM-4.7-Flash | o3-pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 38.8 | 42.9 |
| Released | 2026-01-19 | 2025-06-10 |
| Weights | Open | Proprietary |
| Context window | 200K | 200K |
| Max output | 131K | 100K |
| Input $ / M tokens | $0.06 | $20 |
| Output $ / M tokens | $0.40 | $80 |
| Results tracked | 21 | 12 |
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Category by category
Coding o3-pro leads
GLM-4.7-Flash: 40.6 (#135), o3-pro: 55.5 (#24)
| Benchmark | GLM-4.7-Flash | o3-pro |
|---|---|---|
| Aider Polyglot | — | 84.9% |
| WeirdML | — | 58.2% |
| LMArena Coding | 1383 | — |
Reasoning o3-pro leads
GLM-4.7-Flash: 20.9 (#229), o3-pro: 23.8 (#171)
| Benchmark | GLM-4.7-Flash | o3-pro |
|---|---|---|
| ARC-AGI-2 | — | 4.9% |
| Kagi LLM Benchmark | — | 72.1% |
| ARC-AGI-1 | — | 59.3% |
| Chess Puzzles | 0% | — |
| LMArena Hard Prompts | 1356 | — |
| DTBench | — | 86.9% |
| LMCA | — | 38.5% |
| Epoch Capabilities Index | — | 147.42 |
Math Not comparable
GLM-4.7-Flash: 36.1 (#173), o3-pro: —
| Benchmark | GLM-4.7-Flash | o3-pro |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | — |
| LMArena Math | 1355 | — |
Knowledge GLM-4.7-Flash leads
GLM-4.7-Flash: 35.5 (#184), o3-pro: 29.5 (#238)
| Benchmark | GLM-4.7-Flash | o3-pro |
|---|---|---|
| Vectara Hallucination Rate | 9.3% | 23.3% |
| GPQA Diamond | 60.5% | — |
| Confabulations | — | 14.2% |
| LMArena Expert | 1357 | — |
Multilingual Not comparable
GLM-4.7-Flash: 46.5 (#158), o3-pro: —
| Benchmark | GLM-4.7-Flash | o3-pro |
|---|---|---|
| LMArena Non-English | 1330 | — |
| LMArena Chinese | 1403 | — |
| LMArena French | 1332 | — |
| LMArena German | 1337 | — |
| LMArena Korean | 1283 | — |
| LMArena Russian | 1332 | — |
| LMArena Spanish | 1350 | — |
Instruction Following Not comparable
GLM-4.7-Flash: 70.1 (#167), o3-pro: —
| Benchmark | GLM-4.7-Flash | o3-pro |
|---|---|---|
| LMArena Instruction Following | 1327 | — |
Long Context o3-pro leads
GLM-4.7-Flash: 40.9 (#148), o3-pro: 72.2 (#1)
| Benchmark | GLM-4.7-Flash | o3-pro |
|---|---|---|
| Fiction.LiveBench | — | 97.2% |
| LMArena Longer Query | 1345 | — |
Writing & Preference o3-pro leads
GLM-4.7-Flash: 47.4 (#210), o3-pro: 57.1 (#133)
| Benchmark | GLM-4.7-Flash | o3-pro |
|---|---|---|
| LMArena Text | 1351 | — |
| LMArena Creative Writing | 1297 | — |
| Short-Story Creative Writing | — | 84.4% |
| EQ-Bench Creative Writing | 1125 | — |
| LMArena Multi-Turn | 1342 | — |
Frequently asked questions
Is GLM-4.7-Flash better than o3-pro?
o3-pro is the stronger model overall, scoring 42.9 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 241× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.
Which is cheaper, GLM-4.7-Flash or o3-pro?
GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; o3-pro lists at $20 and $80.
Is GLM-4.7-Flash or o3-pro better for coding?
o3-pro scores higher on coding benchmarks: 55.5 versus 40.6 in the Noometry coding category.
Which has the bigger context window?
Both accept 200K tokens.
How many benchmarks do GLM-4.7-Flash and o3-pro share?
1 benchmark has published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and o3-pro has 12.