Model comparison
GLM-5.3-Flash vs GPT-5.1
GLM-5.3-Flash and GPT-5.1 score almost the same on the Noometry Index (49.6 vs 48.8), so choose on price, context window or the category you care about most.
Last verified . 27 shared benchmarks.
Summary
- They share 27 benchmarks with published results for both. GLM-5.3-Flash scores higher in 6 categories and GPT-5.1 in 4 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.1 leads 39.9 to 31.7.
- The biggest single-benchmark swing is Chess Puzzles: 14% for GLM-5.3-Flash and 32% for GPT-5.1.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $1.25 / $10 for GPT-5.1.
- 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-5.1 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 49.6 | 48.8 |
| Released | 2026-08-20 | 2025-11-13 |
| Weights | Open | Proprietary |
| Context window | 1M | 400K |
| Max output | 131K | 128K |
| Input $ / M tokens | $0.15 | $1.25 |
| Output $ / M tokens | $0.50 | $10 |
| Results tracked | 36 | 63 |
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Category by category
Coding GLM-5.3-Flash leads
GLM-5.3-Flash: 53.7 (#26), GPT-5.1: 46.9 (#59)
| Benchmark | GLM-5.3-Flash | GPT-5.1 |
|---|---|---|
| LMArena WebDev | 1614 | 1395 |
| SciCode | 51.6% | 43.3% |
| LMArena Coding | 1506 | 1454 |
| ALE-Bench | 303.55 | 1,192 |
| SWE-bench Verified | — | 68% |
| DeepSWE | 63.4% | — |
| FrontierCode | 31.8% | — |
| SWE-bench Verified (bash only) | — | 66% |
| GSO | — | 13.7% |
| WeirdML | — | 60.8% |
| LiveBench Coding | — | 72.5% |
Agentic & Tool Use GLM-5.3-Flash leads
GLM-5.3-Flash: 34.3 (#41), GPT-5.1: 32.5 (#55)
| Benchmark | GLM-5.3-Flash | GPT-5.1 |
|---|---|---|
| Terminal-Bench | — | 47.6% |
| APEX-Agents | 52.8% | — |
| DeepResearch Bench | — | 42.8% |
| GDP.pdf | 14% | — |
| LMArena Search | — | 1199 |
| Vending-Bench 2 | — | 1,473 |
Reasoning GPT-5.1 leads
GLM-5.3-Flash: 31.7 (#69), GPT-5.1: 39.9 (#50)
| Benchmark | GLM-5.3-Flash | GPT-5.1 |
|---|---|---|
| CritPt | 15.4% | 4.9% |
| Chess Puzzles | 14% | 32% |
| LMArena Hard Prompts | 1490 | 1457 |
| Mystery Game Puzzles | 8% | 19% |
| Epoch Capabilities Index | 151.9 | 149.66 |
| ARC-AGI-2 | — | 17.6% |
| SimpleBench | — | 53.2% |
| ARC-AGI-1 | — | 72.8% |
| EnigmaEval | — | 11.2% |
| LiveBench Reasoning | — | 95.8% |
| DTBench | — | 90.1% |
| LiveBench Data Analysis | — | 72.1% |
| LMCA | — | 43.9% |
| Surface Evolver Bench | 52.5% | — |
| Bench to the Future 3 | 0.15 | — |
| ForecastBench | — | 58.1 |
| LiveBench | — | 78.8% |
Math GLM-5.3-Flash leads
GLM-5.3-Flash: 53.1 (#38), GPT-5.1: 50.3 (#45)
| Benchmark | GLM-5.3-Flash | GPT-5.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 93.9% | 88.6% |
| LMArena Math | 1499 | 1446 |
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 17.1% | — |
| ProofBench | 21% | — |
| Omni-MATH | — | 46.4% |
| LiveBench Math | — | 94.5% |
| FrontierMath (Feb 2025 set) | — | 31% |
| FrontierMath Tier 4 (v1) | — | 12.5% |
Knowledge GLM-5.3-Flash leads
GLM-5.3-Flash: 58.4 (#33), GPT-5.1: 50.5 (#65)
| Benchmark | GLM-5.3-Flash | GPT-5.1 |
|---|---|---|
| GPQA Diamond | 90.2% | 87.6% |
| LMArena Expert | 1512 | 1470 |
| Humanity's Last Exam | — | 23.7% |
| SimpleQA Verified | — | 48% |
| MMLU-Pro | — | 57.9% |
| Vectara Hallucination Rate | — | 10.9% |
| GPQA (HELM) | — | 44.2% |
Multimodal GPT-5.1 leads
GLM-5.3-Flash: 42.6 (#25), GPT-5.1: 44.0 (#17)
| Benchmark | GLM-5.3-Flash | GPT-5.1 |
|---|---|---|
| LMArena Vision | 1304 | 1250 |
| VPCT | — | 58.7% |
| LMArena Document | — | 1403 |
Multilingual GLM-5.3-Flash leads
GLM-5.3-Flash: 56.2 (#24), GPT-5.1: 54.0 (#51)
| Benchmark | GLM-5.3-Flash | GPT-5.1 |
|---|---|---|
| LMArena Non-English | 1462 | 1431 |
| LMArena Chinese | 1529 | 1495 |
| LMArena French | 1495 | 1451 |
| LMArena German | 1457 | 1439 |
| LMArena Japanese | 1420 | 1453 |
| LMArena Korean | 1443 | 1401 |
| LMArena Russian | 1472 | 1435 |
| LMArena Spanish | 1471 | 1430 |
Instruction Following GPT-5.1 leads
GLM-5.3-Flash: 77.8 (#17), GPT-5.1: 84.0 (#1)
| Benchmark | GLM-5.3-Flash | GPT-5.1 |
|---|---|---|
| LMArena Instruction Following | 1480 | 1442 |
| LiveBench Instruction Following | — | 93.3% |
| IFEval | — | 93.5% |
Long Context GPT-5.1 leads
GLM-5.3-Flash: 45.3 (#41), GPT-5.1: 47.6 (#14)
| Benchmark | GLM-5.3-Flash | GPT-5.1 |
|---|---|---|
| LMArena Longer Query | 1479 | 1448 |
| CL-bench | — | 23.7% |
| CL-bench Life | — | 17.3% |
Writing & Preference Too close to call
GLM-5.3-Flash: 65.4 (#49), GPT-5.1: 64.7 (#53)
| Benchmark | GLM-5.3-Flash | GPT-5.1 |
|---|---|---|
| LMArena Text | 1471 | 1443 |
| LMArena Creative Writing | 1440 | 1427 |
| LMArena Multi-Turn | 1471 | 1449 |
| WildBench | — | 86.3% |
| LiveBench Language | — | 80.2% |
Frequently asked questions
Is GLM-5.3-Flash better than GPT-5.1?
GLM-5.3-Flash and GPT-5.1 score almost the same on the Noometry Index (49.6 vs 48.8), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-5.3-Flash or GPT-5.1?
GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; GPT-5.1 lists at $1.25 and $10.
Is GLM-5.3-Flash or GPT-5.1 better for coding?
GLM-5.3-Flash scores higher on coding benchmarks: 53.7 versus 46.9 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-5.1 share?
27 benchmarks have published results for both models. GLM-5.3-Flash has 36 scored results on Noometry and GPT-5.1 has 63.