Model comparison
GLM-5.2 vs Grok 3
GLM-5.2 is the stronger model overall, scoring 50.9 to 39.6 on the Noometry Index.
Last verified . 26 shared benchmarks.
Summary
- They share 26 benchmarks with published results for both. GLM-5.2 scores higher in 9 categories and Grok 3 in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-5.2 leads 42.1 to 13.8.
- The biggest single-benchmark swing is ARC-AGI-1: 77% for GLM-5.2 and 5.5% for Grok 3.
- GLM-5.2 has downloadable open weights; the other is API-only.
Side by side
| GLM-5.2 | Grok 3 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | xAI |
| Noometry Index | 50.9 | 39.6 |
| Released | 2026-06-13 | 2025-04-09 |
| Weights | Open | Proprietary |
| Context window | 1M | — |
| Max output | 131K | — |
| Input $ / M tokens | $1.40 | — |
| Output $ / M tokens | $4.40 | — |
| Results tracked | 50 | 40 |
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Category by category
Coding GLM-5.2 leads
GLM-5.2: 50.9 (#37), Grok 3: 41.5 (#113)
| Benchmark | GLM-5.2 | Grok 3 |
|---|---|---|
| WeirdML | 70.1% | 37.2% |
| LMArena Coding | 1484 | 1432 |
| SWE-bench Verified | 78.7% | — |
| DeepSWE | 43.8% | — |
| FrontierCode | 24.5% | — |
| Aider Polyglot | — | 53.3% |
| LMArena WebDev | 1604 | — |
| SciCode | 50.5% | — |
| ALE-Bench | 1,047 | — |
Agentic & Tool Use GLM-5.2 leads
GLM-5.2: 31.6 (#63), Grok 3: 30.2 (#69)
| Benchmark | GLM-5.2 | Grok 3 |
|---|---|---|
| τ²-bench Banking | 37.1% | — |
| PostTrainBench | 31.7% | — |
| BALROG | — | 29.5% |
| GBAEval | 0% | — |
| Vending-Bench 2 | 8,314 | — |
Reasoning GLM-5.2 leads
GLM-5.2: 42.1 (#46), Grok 3: 13.8 (#322)
| Benchmark | GLM-5.2 | Grok 3 |
|---|---|---|
| ARC-AGI-2 | 22.8% | 0% |
| SimpleBench | 58.8% | 36.1% |
| Kagi LLM Benchmark | 62.6% | 61.3% |
| ARC-AGI-1 | 77% | 5.5% |
| LMArena Hard Prompts | 1480 | 1433 |
| Epoch Capabilities Index | 151.76 | 138.34 |
| NYT Connections (extended) | 74.3% | — |
| CritPt | 20.9% | — |
| Chess Puzzles | 21% | — |
| EBR-Bench | 9.5% | — |
| Mystery Game Puzzles | 19% | — |
| DTBench | 93.6% | — |
| LMCA | 45.8% | — |
| Surface Evolver Bench | 55.6% | — |
Math GLM-5.2 leads
GLM-5.2: 55.4 (#35), Grok 3: 36.2 (#122)
| Benchmark | GLM-5.2 | Grok 3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 86.4% | 55.6% |
| LMArena Math | 1482 | 1390 |
| FrontierMath (Tiers 1-3) | 59.2% | — |
| FrontierMath Tier 4 | 29.3% | — |
| MathArena Final-Answer Competitions | 67.6% | — |
| ProofBench | 35% | — |
| Omni-MATH | — | 46.4% |
| MATH Level 5 | — | 88.7% |
| FrontierMath (Feb 2025 set) | — | 3.8% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge GLM-5.2 leads
GLM-5.2: 57.1 (#36), Grok 3: 46.0 (#76)
| Benchmark | GLM-5.2 | Grok 3 |
|---|---|---|
| GPQA Diamond | 91.9% | 75.8% |
| LMArena Expert | 1484 | 1420 |
| SimpleQA Verified | 34.2% | — |
| MMLU-Pro | — | 78.8% |
| Confabulations | — | 14.2% |
| Vectara Hallucination Rate | — | 5.8% |
| GPQA (HELM) | — | 65% |
Multilingual GLM-5.2 leads
GLM-5.2: 56.0 (#25), Grok 3: 52.5 (#81)
| Benchmark | GLM-5.2 | Grok 3 |
|---|---|---|
| LMArena Non-English | 1459 | 1411 |
| LMArena Chinese | 1518 | 1448 |
| LMArena French | 1476 | 1460 |
| LMArena German | 1470 | 1431 |
| LMArena Japanese | 1451 | 1389 |
| LMArena Korean | 1445 | 1374 |
| LMArena Russian | 1467 | 1416 |
| LMArena Spanish | 1477 | 1417 |
Instruction Following GLM-5.2 leads
GLM-5.2: 77.1 (#32), Grok 3: 75.2 (#69)
| Benchmark | GLM-5.2 | Grok 3 |
|---|---|---|
| LMArena Instruction Following | 1465 | 1409 |
| IFEval | — | 88.4% |
Long Context GLM-5.2 leads
GLM-5.2: 45.3 (#43), Grok 3: 38.7 (#187)
| Benchmark | GLM-5.2 | Grok 3 |
|---|---|---|
| LMArena Longer Query | 1479 | 1439 |
| Fiction.LiveBench | — | 58.3% |
Writing & Preference GLM-5.2 leads
GLM-5.2: 70.7 (#20), Grok 3: 56.0 (#136)
| Benchmark | GLM-5.2 | Grok 3 |
|---|---|---|
| LMArena Text | 1470 | 1426 |
| LMArena Creative Writing | 1465 | 1414 |
| EQ-Bench Creative Writing | 1757 | 1186 |
| LMArena Multi-Turn | 1468 | 1424 |
| Short-Story Creative Writing | — | 76.4% |
| WildBench | — | 84.9% |
| EQ-Bench 4 | 1222 | — |
Frequently asked questions
Is GLM-5.2 better than Grok 3?
GLM-5.2 is the stronger model overall, scoring 50.9 to 39.6 on the Noometry Index.
Is GLM-5.2 or Grok 3 better for coding?
GLM-5.2 scores higher on coding benchmarks: 50.9 versus 41.5 in the Noometry coding category.
How many benchmarks do GLM-5.2 and Grok 3 share?
26 benchmarks have published results for both models. GLM-5.2 has 50 scored results on Noometry and Grok 3 has 40.