Model comparison
Claude 3.5 Sonnet vs GLM-5.3-Flash
GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 34.6 on the Noometry Index.
Last verified . 21 shared benchmarks.
Summary
- They share 21 benchmarks with published results for both. Claude 3.5 Sonnet scores higher in 0 categories and GLM-5.3-Flash in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3-Flash leads 53.3 to 19.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 8.5% for Claude 3.5 Sonnet and 93.9% for GLM-5.3-Flash.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.
Side by side
| Claude 3.5 Sonnet | GLM-5.3-Flash | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 34.6 | 51.8 |
| Released | 2024-06-20 | 2026-08-20 |
| Weights | Proprietary | Open |
| Context window | — | 1M |
| Max output | — | 131K |
| Input $ / M tokens | — | $0.15 |
| Output $ / M tokens | — | $0.50 |
| Results tracked | 60 | 40 |
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Category by category
Coding GLM-5.3-Flash leads
Claude 3.5 Sonnet: 39.0 (#165), GLM-5.3-Flash: 53.1 (#31)
| Benchmark | Claude 3.5 Sonnet | GLM-5.3-Flash |
|---|---|---|
| LMArena Coding | 1342 | 1508 |
| DeepSWE | — | 63.4% |
| FrontierCode | — | 31.8% |
| Aider Polyglot | 51.6% | — |
| CursorBench | — | 36.8% |
| LMArena WebDev | — | 1609 |
| FrontierSWE | — | 18.1% |
| SciCode | — | 51.6% |
| GSO | 4.6% | — |
| WeirdML | 40% | — |
| BigCodeBench Instruct | 46.8% | — |
| LiveBench Coding | 67.1% | — |
| BigCodeBench Complete | 58.6% | — |
| CadEval | 48% | — |
| ALE-Bench | — | 303.55 |
| HumanEval+ | 81.7% | — |
| MBPP+ | 74.3% | — |
Agentic & Tool Use GLM-5.3-Flash leads
Claude 3.5 Sonnet: 32.3 (#67), GLM-5.3-Flash: 34.2 (#47)
| Benchmark | Claude 3.5 Sonnet | GLM-5.3-Flash |
|---|---|---|
| APEX-Agents | — | 52.8% |
| TheAgentCompany | 24% | — |
| Cybench | 17.5% | — |
| BALROG | 32.6% | — |
| GDP.pdf | — | 14% |
| METR Time Horizons | 45.2% | — |
Reasoning GLM-5.3-Flash leads
Claude 3.5 Sonnet: 23.1 (#183), GLM-5.3-Flash: 48.0 (#42)
| Benchmark | Claude 3.5 Sonnet | GLM-5.3-Flash |
|---|---|---|
| LMArena Hard Prompts | 1305 | 1491 |
| Epoch Capabilities Index | 133.55 | 151.88 |
| ARC-AGI-2 | — | 65.8% |
| SimpleBench | 41.4% | — |
| ARC-AGI-1 | — | 91% |
| CritPt | — | 15.4% |
| Chess Puzzles | — | 14% |
| EnigmaEval | 0.9% | — |
| LiveBench Reasoning | 56.7% | — |
| Mystery Game Puzzles | — | 8% |
| DTBench | 67.8% | — |
| LiveBench Data Analysis | 55% | — |
| Surface Evolver Bench | — | 52.5% |
| Bench to the Future 3 | — | 0.15 |
| ForecastBench | 60.7 | — |
| LiveBench | 59% | — |
Math GLM-5.3-Flash leads
Claude 3.5 Sonnet: 19.2 (#288), GLM-5.3-Flash: 53.3 (#47)
| Benchmark | Claude 3.5 Sonnet | GLM-5.3-Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 8.5% | 93.9% |
| LMArena Math | 1307 | 1500 |
| FrontierMath (Tiers 1-3) | — | 55.8% |
| FrontierMath Tier 4 | — | 17.1% |
| ProofBench | — | 21% |
| Omni-MATH | 27.6% | — |
| LiveBench Math | 52.3% | — |
| MATH Level 5 | 56.9% | — |
| FrontierMath (Feb 2025 set) | 2.1% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge GLM-5.3-Flash leads
Claude 3.5 Sonnet: 28.6 (#245), GLM-5.3-Flash: 58.4 (#36)
| Benchmark | Claude 3.5 Sonnet | GLM-5.3-Flash |
|---|---|---|
| GPQA Diamond | 55.3% | 90.2% |
| LMArena Expert | 1265 | 1513 |
| Humanity's Last Exam | 4.1% | — |
| MMLU-Pro | 77.7% | — |
| Confabulations | 19.9% | — |
| GPQA (HELM) | 56.5% | — |
| MMLU | 87.3% | — |
Multimodal GLM-5.3-Flash leads
Claude 3.5 Sonnet: 26.5 (#120), GLM-5.3-Flash: 42.8 (#27)
| Benchmark | Claude 3.5 Sonnet | GLM-5.3-Flash |
|---|---|---|
| LMArena Vision | 1125 | 1296 |
| Video-MME | 60% | — |
| GeoBench | 62% | — |
| VPCT | 33% | — |
Multilingual GLM-5.3-Flash leads
Claude 3.5 Sonnet: 43.2 (#185), GLM-5.3-Flash: 56.0 (#25)
| Benchmark | Claude 3.5 Sonnet | GLM-5.3-Flash |
|---|---|---|
| LMArena Non-English | 1283 | 1462 |
| LMArena Chinese | 1272 | 1527 |
| LMArena French | 1305 | 1496 |
| LMArena German | 1297 | 1470 |
| LMArena Japanese | 1234 | 1429 |
| LMArena Korean | 1200 | 1446 |
| LMArena Russian | 1306 | 1469 |
| LMArena Spanish | 1290 | 1471 |
Instruction Following GLM-5.3-Flash leads
Claude 3.5 Sonnet: 68.8 (#182), GLM-5.3-Flash: 77.5 (#20)
| Benchmark | Claude 3.5 Sonnet | GLM-5.3-Flash |
|---|---|---|
| LMArena Instruction Following | 1297 | 1478 |
| LiveBench Instruction Following | 69.3% | — |
| IFEval | 85.5% | — |
Long Context GLM-5.3-Flash leads
Claude 3.5 Sonnet: 39.9 (#167), GLM-5.3-Flash: 45.4 (#39)
| Benchmark | Claude 3.5 Sonnet | GLM-5.3-Flash |
|---|---|---|
| LMArena Longer Query | 1311 | 1482 |
Writing & Preference GLM-5.3-Flash leads
Claude 3.5 Sonnet: 52.9 (#164), GLM-5.3-Flash: 65.3 (#50)
| Benchmark | Claude 3.5 Sonnet | GLM-5.3-Flash |
|---|---|---|
| LMArena Text | 1298 | 1471 |
| LMArena Creative Writing | 1292 | 1442 |
| LMArena Multi-Turn | 1326 | 1467 |
| Short-Story Creative Writing | 80.3% | — |
| EQ-Bench Creative Writing | 1451 | — |
| WildBench | 79.2% | — |
| LiveBench Language | 53.8% | — |
Frequently asked questions
Is Claude 3.5 Sonnet better than GLM-5.3-Flash?
GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 34.6 on the Noometry Index.
Is Claude 3.5 Sonnet or GLM-5.3-Flash better for coding?
GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 39.0 in the Noometry coding category.
How many benchmarks do Claude 3.5 Sonnet and GLM-5.3-Flash share?
21 benchmarks have published results for both models. Claude 3.5 Sonnet has 60 scored results on Noometry and GLM-5.3-Flash has 40.