Model comparison
GLM-5.3-Flash vs GPT-5 Pro
GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 46.4 on the Noometry Index.
Last verified . 5 shared benchmarks.
Summary
- They share 5 benchmarks with published results for both. GLM-5.3-Flash scores higher in 4 categories and GPT-5 Pro in 0 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-5.3-Flash leads 53.1 to 44.0.
- The biggest single-benchmark swing is ARC-AGI-2: 65.8% for GLM-5.3-Flash and 18.3% for GPT-5 Pro.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $15 / $120 for GPT-5 Pro.
- GLM-5.3-Flash accepts more context: 1M tokens versus 400K.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.
Side by side
| GLM-5.3-Flash | GPT-5 Pro | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 51.8 | 46.4 |
| Released | 2026-08-20 | 2025-10-06 |
| Weights | Open | Proprietary |
| Context window | 1M | 400K |
| Max output | 131K | 272K |
| Input $ / M tokens | $0.15 | $15 |
| Output $ / M tokens | $0.50 | $120 |
| Results tracked | 40 | 12 |
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Category by category
Coding GLM-5.3-Flash leads
GLM-5.3-Flash: 53.1 (#31), GPT-5 Pro: 44.0 (#80)
| Benchmark | GLM-5.3-Flash | GPT-5 Pro |
|---|---|---|
| DeepSWE | 63.4% | — |
| FrontierCode | 31.8% | — |
| CursorBench | 36.8% | — |
| LMArena WebDev | 1609 | — |
| FrontierSWE | 18.1% | — |
| SciCode | 51.6% | — |
| WeirdML | — | 60.4% |
| LMArena Coding | 1508 | — |
| ALE-Bench | 303.55 | — |
| AlgoTune | — | 1.31 |
Agentic & Tool Use Not comparable
GLM-5.3-Flash: 34.2 (#47), GPT-5 Pro: —
| Benchmark | GLM-5.3-Flash | GPT-5 Pro |
|---|---|---|
| APEX-Agents | 52.8% | — |
| GDP.pdf | 14% | — |
Reasoning GLM-5.3-Flash leads
GLM-5.3-Flash: 48.0 (#42), GPT-5 Pro: 38.9 (#62)
| Benchmark | GLM-5.3-Flash | GPT-5 Pro |
|---|---|---|
| ARC-AGI-2 | 65.8% | 18.3% |
| ARC-AGI-1 | 91% | 70.2% |
| Epoch Capabilities Index | 151.88 | 150.28 |
| SimpleBench | — | 61.6% |
| Kagi LLM Benchmark | — | 76.8% |
| CritPt | 15.4% | — |
| Chess Puzzles | 14% | — |
| EnigmaEval | — | 18.8% |
| LMArena Hard Prompts | 1491 | — |
| Mystery Game Puzzles | 8% | — |
| Surface Evolver Bench | 52.5% | — |
| Bench to the Future 3 | 0.15 | — |
Math GLM-5.3-Flash leads
GLM-5.3-Flash: 53.3 (#47), GPT-5 Pro: 48.5 (#63)
| Benchmark | GLM-5.3-Flash | GPT-5 Pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | 55.8% | 55.8% |
| FrontierMath Tier 4 | 17.1% | 19.5% |
| OTIS Mock AIME 2024-2025 | 93.9% | — |
| ProofBench | 21% | — |
| LMArena Math | 1500 | — |
| FrontierMath Tier 4 (v1) | — | 14.6% |
Knowledge GLM-5.3-Flash leads
GLM-5.3-Flash: 58.4 (#36), GPT-5 Pro: 56.7 (#42)
| Benchmark | GLM-5.3-Flash | GPT-5 Pro |
|---|---|---|
| GPQA Diamond | 90.2% | — |
| Humanity's Last Exam | — | 31.6% |
| LMArena Expert | 1513 | — |
Multimodal Not comparable
GLM-5.3-Flash: 42.8 (#27), GPT-5 Pro: —
| Benchmark | GLM-5.3-Flash | GPT-5 Pro |
|---|---|---|
| LMArena Vision | 1296 | — |
Multilingual Not comparable
GLM-5.3-Flash: 56.0 (#25), GPT-5 Pro: —
| Benchmark | GLM-5.3-Flash | GPT-5 Pro |
|---|---|---|
| LMArena Non-English | 1462 | — |
| LMArena Chinese | 1527 | — |
| LMArena French | 1496 | — |
| LMArena German | 1470 | — |
| LMArena Japanese | 1429 | — |
| LMArena Korean | 1446 | — |
| LMArena Russian | 1469 | — |
| LMArena Spanish | 1471 | — |
Instruction Following Not comparable
GLM-5.3-Flash: 77.5 (#20), GPT-5 Pro: —
| Benchmark | GLM-5.3-Flash | GPT-5 Pro |
|---|---|---|
| LMArena Instruction Following | 1478 | — |
Long Context Not comparable
GLM-5.3-Flash: 45.4 (#39), GPT-5 Pro: —
| Benchmark | GLM-5.3-Flash | GPT-5 Pro |
|---|---|---|
| LMArena Longer Query | 1482 | — |
Writing & Preference Not comparable
GLM-5.3-Flash: 65.3 (#50), GPT-5 Pro: —
| Benchmark | GLM-5.3-Flash | GPT-5 Pro |
|---|---|---|
| LMArena Text | 1471 | — |
| LMArena Creative Writing | 1442 | — |
| LMArena Multi-Turn | 1467 | — |
Frequently asked questions
Is GLM-5.3-Flash better than GPT-5 Pro?
GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 46.4 on the Noometry Index.
Which is cheaper, GLM-5.3-Flash or GPT-5 Pro?
GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; GPT-5 Pro lists at $15 and $120.
Is GLM-5.3-Flash or GPT-5 Pro better for coding?
GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 44.0 in the Noometry coding category.
Which has the bigger context window?
GLM-5.3-Flash does, with 1M tokens against 400K.
How many benchmarks do GLM-5.3-Flash and GPT-5 Pro share?
5 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and GPT-5 Pro has 12.