Model comparison
Claude 3.7 Sonnet vs GLM-4.6
GLM-4.6 is the stronger model overall, scoring 40.9 to 39.4 on the Noometry Index.
Last verified . 20 shared benchmarks.
Summary
- They share 20 benchmarks with published results for both. Claude 3.7 Sonnet scores higher in 4 categories and GLM-4.6 in 5 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.6 leads 53.6 to 44.3.
- GLM-4.6 has downloadable open weights; the other is API-only.
Side by side
| Claude 3.7 Sonnet | GLM-4.6 | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 39.4 | 40.9 |
| Released | 2025-02-24 | 2025-09-30 |
| Weights | Proprietary | Open |
| Context window | — | 205K |
| Max output | — | 131K |
| Input $ / M tokens | — | $0.60 |
| Output $ / M tokens | — | $2.20 |
| Results tracked | 58 | 29 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 41.1 (#120), GLM-4.6: 39.9 (#137)
| Benchmark | Claude 3.7 Sonnet | GLM-4.6 |
|---|---|---|
| SWE-bench Verified (bash only) | 52.8% | 55.4% |
| LMArena Coding | 1361 | 1449 |
| SWE-bench Verified | 61% | — |
| Aider Polyglot | 64.9% | — |
| LMArena WebDev | — | 1339 |
| SciCode | — | 38.4% |
| GSO | 3.8% | — |
| LiveBench Coding | 74.5% | — |
| CadEval | 54% | — |
| ALE-Bench | — | 340.82 |
Agentic & Tool Use Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 33.9 (#46), GLM-4.6: 32.1 (#60)
| Benchmark | Claude 3.7 Sonnet | GLM-4.6 |
|---|---|---|
| Terminal-Bench | — | 24.5% |
| Berkeley Function Calling Leaderboard | — | 72.4% |
| TheAgentCompany | 30.9% | — |
| Cybench | 20% | — |
| DeepResearch Bench | 43.6% | — |
| OSWorld | 35.8% | — |
| METR Time Horizons | 60% | — |
Reasoning GLM-4.6 leads
Claude 3.7 Sonnet: 18.7 (#252), GLM-4.6: 23.1 (#168)
| Benchmark | Claude 3.7 Sonnet | GLM-4.6 |
|---|---|---|
| LMArena Hard Prompts | 1333 | 1440 |
| ARC-AGI-2 | 0.9% | — |
| SimpleBench | 46.4% | — |
| Kagi LLM Benchmark | — | 47.4% |
| ARC-AGI-1 | 28.6% | — |
| CritPt | — | 1.1% |
| EnigmaEval | 4.2% | — |
| LiveBench Reasoning | 87.8% | — |
| LiveBench Data Analysis | 74% | — |
| Epoch Capabilities Index | 141.16 | — |
| ForecastBench | 61.8 | — |
| LiveBench | 76.1% | — |
Math Too close to call
Claude 3.7 Sonnet: 35.7 (#137), GLM-4.6: 36.4 (#115)
| Benchmark | Claude 3.7 Sonnet | GLM-4.6 |
|---|---|---|
| LMArena Math | 1336 | 1431 |
| FrontierMath (Feb 2025 set) | 4.1% | 3.8% |
| OTIS Mock AIME 2024-2025 | 57.8% | — |
| Omni-MATH | 33% | — |
| LiveBench Math | 79% | — |
| MATH Level 5 | 91.2% | — |
| FrontierMath Tier 4 (v1) | — | 2.1% |
Knowledge Too close to call
Claude 3.7 Sonnet: 39.7 (#117), GLM-4.6: 39.6 (#118)
| Benchmark | Claude 3.7 Sonnet | GLM-4.6 |
|---|---|---|
| LMArena Expert | 1321 | 1432 |
| GPQA Diamond | 79.7% | — |
| Humanity's Last Exam | 8% | — |
| MMLU-Pro | 78.4% | — |
| Confabulations | 14.7% | — |
| Vectara Hallucination Rate | — | 9.5% |
| GPQA (HELM) | 60.8% | — |
Multimodal Not comparable
Claude 3.7 Sonnet: 33.1 (#90), GLM-4.6: —
| Benchmark | Claude 3.7 Sonnet | GLM-4.6 |
|---|---|---|
| LMArena Vision | 1169 | — |
| GeoBench | 68% | — |
| VPCT | 39% | — |
| SpatialViz-Bench | 33.9% | — |
Multilingual GLM-4.6 leads
Claude 3.7 Sonnet: 44.3 (#174), GLM-4.6: 53.6 (#62)
| Benchmark | Claude 3.7 Sonnet | GLM-4.6 |
|---|---|---|
| LMArena Non-English | 1296 | 1426 |
| LMArena Chinese | 1299 | 1500 |
| LMArena French | 1302 | 1459 |
| LMArena German | 1301 | 1447 |
| LMArena Japanese | 1268 | 1394 |
| LMArena Korean | 1249 | 1401 |
| LMArena Russian | 1311 | 1418 |
| LMArena Spanish | 1299 | 1436 |
Instruction Following GLM-4.6 leads
Claude 3.7 Sonnet: 73.1 (#120), GLM-4.6: 74.5 (#93)
| Benchmark | Claude 3.7 Sonnet | GLM-4.6 |
|---|---|---|
| LMArena Instruction Following | 1352 | 1410 |
| LiveBench Instruction Following | 81.3% | — |
| IFEval | 83.4% | — |
Long Context Claude 3.7 Sonnet leads
Claude 3.7 Sonnet: 50.2 (#10), GLM-4.6: 43.4 (#91)
| Benchmark | Claude 3.7 Sonnet | GLM-4.6 |
|---|---|---|
| LMArena Longer Query | 1373 | 1423 |
| Fiction.LiveBench | 83.3% | — |
Writing & Preference GLM-4.6 leads
Claude 3.7 Sonnet: 54.6 (#145), GLM-4.6: 61.3 (#86)
| Benchmark | Claude 3.7 Sonnet | GLM-4.6 |
|---|---|---|
| LMArena Text | 1314 | 1440 |
| LMArena Creative Writing | 1332 | 1411 |
| EQ-Bench Creative Writing | 1412 | 1411 |
| LMArena Multi-Turn | 1339 | 1427 |
| Short-Story Creative Writing | 81.1% | — |
| WildBench | 81.4% | — |
| LiveBench Language | 59.9% | — |
Frequently asked questions
Is Claude 3.7 Sonnet better than GLM-4.6?
GLM-4.6 is the stronger model overall, scoring 40.9 to 39.4 on the Noometry Index.
Is Claude 3.7 Sonnet or GLM-4.6 better for coding?
Claude 3.7 Sonnet scores higher on coding benchmarks: 41.1 versus 39.9 in the Noometry coding category.
How many benchmarks do Claude 3.7 Sonnet and GLM-4.6 share?
20 benchmarks have published results for both models. Claude 3.7 Sonnet has 58 scored results on Noometry and GLM-4.6 has 29.