Model comparison
GLM-4.5 vs GPT-5.1
GPT-5.1 is the stronger model overall, scoring 49.0 to 42.0 on the Noometry Index. GLM-4.5 costs 3.4× less per token, which makes it the better buy when GPT-5.1's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
Summary
- They share 21 benchmarks with published results for both. GLM-4.5 scores higher in 0 categories and GPT-5.1 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5.1 leads 50.6 to 35.9.
- The biggest single-benchmark swing is WeirdML: 40.6% for GLM-4.5 and 60.8% for GPT-5.1.
- GLM-4.5 is cheaper at $0.60 / $2.20 per million input/output tokens, against $1.25 / $10 for GPT-5.1.
- GPT-5.1 accepts more context: 400K tokens versus 131K.
- GLM-4.5 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.5 | GPT-5.1 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 42.0 | 49.0 |
| Released | 2025-07-27 | 2025-11-13 |
| Weights | Open | Proprietary |
| Context window | 131K | 400K |
| Max output | 98K | 128K |
| Input $ / M tokens | $0.60 | $1.25 |
| Output $ / M tokens | $2.20 | $10 |
| Results tracked | 27 | 63 |
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Category by category
Coding GPT-5.1 leads
GLM-4.5: 41.4 (#125), GPT-5.1: 46.4 (#66)
| Benchmark | GLM-4.5 | GPT-5.1 |
|---|---|---|
| SWE-bench Verified (bash only) | 54.2% | 66% |
| WeirdML | 40.6% | 60.8% |
| LMArena Coding | 1434 | 1454 |
| ALE-Bench | 344.82 | 1,192 |
| SWE-bench Verified | — | 68% |
| LMArena WebDev | — | 1395 |
| SciCode | — | 43.3% |
| GSO | — | 13.7% |
| LiveBench Coding | — | 72.5% |
| AlgoTune | 1.52 | — |
Agentic & Tool Use Not comparable
GLM-4.5: —, GPT-5.1: 32.7 (#60)
| Benchmark | GLM-4.5 | GPT-5.1 |
|---|---|---|
| Terminal-Bench | — | 47.6% |
| DeepResearch Bench | — | 42.8% |
| LMArena Search | — | 1199 |
| Vending-Bench 2 | — | 1,473 |
Reasoning GPT-5.1 leads
GLM-4.5: 28.6 (#100), GPT-5.1: 39.8 (#58)
| Benchmark | GLM-4.5 | GPT-5.1 |
|---|---|---|
| LMArena Hard Prompts | 1429 | 1457 |
| ARC-AGI-2 | — | 17.6% |
| SimpleBench | — | 53.2% |
| Kagi LLM Benchmark | 57.9% | — |
| ARC-AGI-1 | — | 72.8% |
| CritPt | — | 4.9% |
| Chess Puzzles | — | 32% |
| EnigmaEval | — | 11.2% |
| LiveBench Reasoning | — | 95.8% |
| Mystery Game Puzzles | — | 19% |
| DTBench | — | 90.1% |
| LiveBench Data Analysis | — | 72.1% |
| LMCA | — | 43.9% |
| Epoch Capabilities Index | — | 149.64 |
| ForecastBench | — | 58.1 |
| LiveBench | — | 78.8% |
Math GPT-5.1 leads
GLM-4.5: 39.0 (#116), GPT-5.1: 52.2 (#51)
| Benchmark | GLM-4.5 | GPT-5.1 |
|---|---|---|
| LMArena Math | 1427 | 1447 |
| OTIS Mock AIME 2024-2025 | — | 88.6% |
| Omni-MATH | — | 46.4% |
| LiveBench Math | — | 94.5% |
| FrontierMath (Feb 2025 set) | — | 31% |
| FrontierMath Tier 4 (v1) | — | 12.5% |
Knowledge GPT-5.1 leads
GLM-4.5: 35.9 (#179), GPT-5.1: 50.6 (#71)
| Benchmark | GLM-4.5 | GPT-5.1 |
|---|---|---|
| Humanity's Last Exam | 8.3% | 23.7% |
| LMArena Expert | 1433 | 1470 |
| GPQA Diamond | — | 87.6% |
| SimpleQA Verified | — | 48% |
| MMLU-Pro | — | 57.9% |
| Confabulations | 11.3% | — |
| Vectara Hallucination Rate | — | 10.9% |
| GPQA (HELM) | — | 44.2% |
Multimodal Not comparable
GLM-4.5: —, GPT-5.1: 44.8 (#19)
| Benchmark | GLM-4.5 | GPT-5.1 |
|---|---|---|
| LMArena Vision | — | 1250 |
| VPCT | — | 58.7% |
| LMArena Document | — | 1403 |
Multilingual GPT-5.1 leads
GLM-4.5: 52.8 (#77), GPT-5.1: 53.8 (#56)
| Benchmark | GLM-4.5 | GPT-5.1 |
|---|---|---|
| LMArena Non-English | 1417 | 1431 |
| LMArena Chinese | 1465 | 1495 |
| LMArena French | 1418 | 1450 |
| LMArena German | 1407 | 1438 |
| LMArena Japanese | 1415 | 1453 |
| LMArena Korean | 1380 | 1401 |
| LMArena Russian | 1414 | 1435 |
| LMArena Spanish | 1454 | 1433 |
Instruction Following GPT-5.1 leads
GLM-4.5: 74.1 (#104), GPT-5.1: 83.9 (#1)
| Benchmark | GLM-4.5 | GPT-5.1 |
|---|---|---|
| LMArena Instruction Following | 1404 | 1443 |
| LiveBench Instruction Following | — | 93.3% |
| IFEval | — | 93.5% |
Long Context GPT-5.1 leads
GLM-4.5: 38.2 (#201), GPT-5.1: 47.6 (#14)
| Benchmark | GLM-4.5 | GPT-5.1 |
|---|---|---|
| LMArena Longer Query | 1412 | 1447 |
| Fiction.LiveBench | 58.3% | — |
| CL-bench | — | 23.7% |
| CL-bench Life | — | 17.3% |
Writing & Preference GPT-5.1 leads
GLM-4.5: 57.5 (#127), GPT-5.1: 64.5 (#55)
| Benchmark | GLM-4.5 | GPT-5.1 |
|---|---|---|
| LMArena Text | 1430 | 1443 |
| LMArena Creative Writing | 1395 | 1427 |
| LMArena Multi-Turn | 1415 | 1450 |
| Short-Story Creative Writing | 73.4% | — |
| EQ-Bench Creative Writing | 1343 | — |
| WildBench | — | 86.3% |
| LiveBench Language | — | 80.2% |
Frequently asked questions
Is GLM-4.5 better than GPT-5.1?
GPT-5.1 is the stronger model overall, scoring 49.0 to 42.0 on the Noometry Index. GLM-4.5 costs 3.4× less per token, which makes it the better buy when GPT-5.1's lead doesn't matter for your workload.
Which is cheaper, GLM-4.5 or GPT-5.1?
GLM-4.5 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; GPT-5.1 lists at $1.25 and $10.
Is GLM-4.5 or GPT-5.1 better for coding?
GPT-5.1 scores higher on coding benchmarks: 46.4 versus 41.4 in the Noometry coding category.
Which has the bigger context window?
GPT-5.1 does, with 400K tokens against 131K.
How many benchmarks do GLM-4.5 and GPT-5.1 share?
21 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and GPT-5.1 has 63.