Model comparison
GLM-5.1 vs GPT-5.3 Chat
GLM-5.1 is the stronger model overall, scoring 47.8 to 42.8 on the Noometry Index.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. GLM-5.1 scores higher in 8 categories and GPT-5.3 Chat in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.1 leads 54.9 to 38.8.
- GLM-5.1 is cheaper at $1.40 / $4.40 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
- GLM-5.1 accepts more context: 200K tokens versus 128K.
- GLM-5.1 has downloadable open weights; the other is API-only.
Side by side
| GLM-5.1 | GPT-5.3 Chat | |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 47.8 | 42.8 |
| Released | 2026-04-07 | 2026-03-03 |
| Weights | Open | Proprietary |
| Context window | 200K | 128K |
| Max output | 131K | 16K |
| Input $ / M tokens | $1.40 | $1.75 |
| Output $ / M tokens | $4.40 | $14 |
| Results tracked | 41 | 18 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GLM-5.1 leads
GLM-5.1: 48.7 (#55), GPT-5.3 Chat: 41.4 (#124)
| Benchmark | GLM-5.1 | GPT-5.3 Chat |
|---|---|---|
| LMArena Coding | 1485 | 1408 |
| SWE-bench Verified | 74.2% | — |
| LMArena WebDev | 1508 | — |
| SciCode | 43.8% | — |
| WeirdML | 57.1% | — |
| ALE-Bench | 887.1 | — |
Agentic & Tool Use Not comparable
GLM-5.1: 24.9 (#113), GPT-5.3 Chat: —
| Benchmark | GLM-5.1 | GPT-5.3 Chat |
|---|---|---|
| APEX-Agents | 40.9% | — |
| ExploitBench | 18.1% | — |
| GBAEval | 0% | — |
| Vending-Bench 2 | 5,634 | — |
Reasoning GLM-5.1 leads
GLM-5.1: 39.1 (#60), GPT-5.3 Chat: 28.5 (#102)
| Benchmark | GLM-5.1 | GPT-5.3 Chat |
|---|---|---|
| LMArena Hard Prompts | 1472 | 1399 |
| SimpleBench | 55.1% | — |
| NYT Connections (extended) | 77.7% | — |
| CritPt | 4.6% | — |
| Chess Puzzles | 19% | — |
| Thematic Generalization | 69.8% | — |
| Epoch Capabilities Index | 149.84 | — |
Math GLM-5.1 leads
GLM-5.1: 49.7 (#60), GPT-5.3 Chat: 38.2 (#142)
| Benchmark | GLM-5.1 | GPT-5.3 Chat |
|---|---|---|
| LMArena Math | 1473 | 1389 |
| FrontierMath (Tiers 1-3) | 36.8% | — |
| MathArena Final-Answer Competitions | 67.1% | — |
| OTIS Mock AIME 2024-2025 | 93.3% | — |
| ProofBench | 22.2% | — |
| FrontierMath (Feb 2025 set) | 33.4% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge GLM-5.1 leads
GLM-5.1: 54.9 (#50), GPT-5.3 Chat: 38.8 (#140)
| Benchmark | GLM-5.1 | GPT-5.3 Chat |
|---|---|---|
| LMArena Expert | 1476 | 1397 |
| GPQA Diamond | 89.9% | — |
| SimpleQA Verified | 34% | — |
Multilingual GLM-5.1 leads
GLM-5.1: 55.0 (#36), GPT-5.3 Chat: 50.3 (#124)
| Benchmark | GLM-5.1 | GPT-5.3 Chat |
|---|---|---|
| LMArena Non-English | 1447 | 1382 |
| LMArena Chinese | 1515 | 1432 |
| LMArena French | 1474 | 1397 |
| LMArena German | 1465 | 1384 |
| LMArena Japanese | 1434 | 1352 |
| LMArena Korean | 1418 | 1346 |
| LMArena Russian | 1454 | 1400 |
| LMArena Spanish | 1469 | 1371 |
Instruction Following GLM-5.1 leads
GLM-5.1: 76.3 (#42), GPT-5.3 Chat: 72.8 (#129)
| Benchmark | GLM-5.1 | GPT-5.3 Chat |
|---|---|---|
| LMArena Instruction Following | 1451 | 1378 |
Long Context GLM-5.1 leads
GLM-5.1: 44.9 (#53), GPT-5.3 Chat: 42.6 (#120)
| Benchmark | GLM-5.1 | GPT-5.3 Chat |
|---|---|---|
| LMArena Longer Query | 1466 | 1396 |
Writing & Preference GLM-5.1 leads
GLM-5.1: 66.9 (#31), GPT-5.3 Chat: 63.1 (#68)
| Benchmark | GLM-5.1 | GPT-5.3 Chat |
|---|---|---|
| LMArena Text | 1461 | 1389 |
| LMArena Creative Writing | 1453 | 1355 |
| EQ-Bench Creative Writing | 1592 | 1690 |
| LMArena Multi-Turn | 1472 | 1412 |
Frequently asked questions
Is GLM-5.1 better than GPT-5.3 Chat?
GLM-5.1 is the stronger model overall, scoring 47.8 to 42.8 on the Noometry Index.
Which is cheaper, GLM-5.1 or GPT-5.3 Chat?
GLM-5.1 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.
Is GLM-5.1 or GPT-5.3 Chat better for coding?
GLM-5.1 scores higher on coding benchmarks: 48.7 versus 41.4 in the Noometry coding category.
Which has the bigger context window?
GLM-5.1 does, with 200K tokens against 128K.
How many benchmarks do GLM-5.1 and GPT-5.3 Chat share?
18 benchmarks have published results for both models. GLM-5.1 has 41 scored results on Noometry and GPT-5.3 Chat has 18.