Model comparison
GLM-5.3-Flash vs Grok 3
GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 39.9 on the Noometry Index.
Last verified . 22 shared benchmarks.
Summary
- They share 22 benchmarks with published results for both. GLM-5.3-Flash 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-5.3-Flash leads 48.0 to 13.7.
- The biggest single-benchmark swing is ARC-AGI-1: 91% for GLM-5.3-Flash and 5.5% for Grok 3.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.
Side by side
| GLM-5.3-Flash | Grok 3 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | xAI |
| Noometry Index | 51.8 | 39.9 |
| Released | 2026-08-20 | 2025-04-09 |
| Weights | Open | Proprietary |
| Context window | 1M | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.15 | — |
| Output $ / M tokens | $0.50 | — |
| Results tracked | 40 | 40 |
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Category by category
Coding GLM-5.3-Flash leads
GLM-5.3-Flash: 53.1 (#31), Grok 3: 41.9 (#115)
| Benchmark | GLM-5.3-Flash | Grok 3 |
|---|---|---|
| LMArena Coding | 1508 | 1432 |
| DeepSWE | 63.4% | — |
| FrontierCode | 31.8% | — |
| Aider Polyglot | — | 53.3% |
| CursorBench | 36.8% | — |
| LMArena WebDev | 1609 | — |
| FrontierSWE | 18.1% | — |
| SciCode | 51.6% | — |
| WeirdML | — | 37.2% |
| ALE-Bench | 303.55 | — |
Agentic & Tool Use GLM-5.3-Flash leads
GLM-5.3-Flash: 34.2 (#47), Grok 3: 30.5 (#76)
| Benchmark | GLM-5.3-Flash | Grok 3 |
|---|---|---|
| APEX-Agents | 52.8% | — |
| BALROG | — | 29.5% |
| GDP.pdf | 14% | — |
Reasoning GLM-5.3-Flash leads
GLM-5.3-Flash: 48.0 (#42), Grok 3: 13.7 (#333)
| Benchmark | GLM-5.3-Flash | Grok 3 |
|---|---|---|
| ARC-AGI-2 | 65.8% | 0% |
| ARC-AGI-1 | 91% | 5.5% |
| LMArena Hard Prompts | 1491 | 1434 |
| Epoch Capabilities Index | 151.88 | 138.33 |
| SimpleBench | — | 36.1% |
| Kagi LLM Benchmark | — | 61.3% |
| CritPt | 15.4% | — |
| Chess Puzzles | 14% | — |
| 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), Grok 3: 38.0 (#145)
| Benchmark | GLM-5.3-Flash | Grok 3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 93.9% | 55.6% |
| LMArena Math | 1500 | 1391 |
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 17.1% | — |
| ProofBench | 21% | — |
| Omni-MATH | — | 46.4% |
| MATH Level 5 | — | 88.7% |
| FrontierMath (Feb 2025 set) | — | 3.8% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge GLM-5.3-Flash leads
GLM-5.3-Flash: 58.4 (#36), Grok 3: 46.2 (#82)
| Benchmark | GLM-5.3-Flash | Grok 3 |
|---|---|---|
| GPQA Diamond | 90.2% | 75.8% |
| LMArena Expert | 1513 | 1421 |
| MMLU-Pro | — | 78.8% |
| Confabulations | — | 14.2% |
| Vectara Hallucination Rate | — | 5.8% |
| GPQA (HELM) | — | 65% |
Multimodal Not comparable
GLM-5.3-Flash: 42.8 (#27), Grok 3: —
| Benchmark | GLM-5.3-Flash | Grok 3 |
|---|---|---|
| LMArena Vision | 1296 | — |
Multilingual GLM-5.3-Flash leads
GLM-5.3-Flash: 56.0 (#25), Grok 3: 52.3 (#87)
| Benchmark | GLM-5.3-Flash | Grok 3 |
|---|---|---|
| LMArena Non-English | 1462 | 1410 |
| LMArena Chinese | 1527 | 1448 |
| LMArena French | 1496 | 1460 |
| LMArena German | 1470 | 1431 |
| LMArena Japanese | 1429 | 1387 |
| LMArena Korean | 1446 | 1373 |
| LMArena Russian | 1469 | 1416 |
| LMArena Spanish | 1471 | 1417 |
Instruction Following GLM-5.3-Flash leads
GLM-5.3-Flash: 77.5 (#20), Grok 3: 75.0 (#73)
| Benchmark | GLM-5.3-Flash | Grok 3 |
|---|---|---|
| LMArena Instruction Following | 1478 | 1409 |
| IFEval | — | 88.4% |
Long Context GLM-5.3-Flash leads
GLM-5.3-Flash: 45.4 (#39), Grok 3: 38.7 (#192)
| Benchmark | GLM-5.3-Flash | Grok 3 |
|---|---|---|
| LMArena Longer Query | 1482 | 1439 |
| Fiction.LiveBench | — | 58.3% |
Writing & Preference GLM-5.3-Flash leads
GLM-5.3-Flash: 65.3 (#50), Grok 3: 55.8 (#141)
| Benchmark | GLM-5.3-Flash | Grok 3 |
|---|---|---|
| LMArena Text | 1471 | 1426 |
| LMArena Creative Writing | 1442 | 1414 |
| LMArena Multi-Turn | 1467 | 1425 |
| Short-Story Creative Writing | — | 76.4% |
| EQ-Bench Creative Writing | — | 1186 |
| WildBench | — | 84.9% |
Frequently asked questions
Is GLM-5.3-Flash better than Grok 3?
GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 39.9 on the Noometry Index.
Is GLM-5.3-Flash or Grok 3 better for coding?
GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 41.9 in the Noometry coding category.
How many benchmarks do GLM-5.3-Flash and Grok 3 share?
22 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and Grok 3 has 40.