Model comparison
Claude Sonnet 4 vs GLM-4.7
GLM-4.7 is the stronger model overall, scoring 42.0 to 40.8 on the Noometry Index.
Last verified . 28 shared benchmarks.
Summary
- They share 28 benchmarks with published results for both. Claude Sonnet 4 scores higher in 2 categories and GLM-4.7 in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Claude Sonnet 4 leads 38.5 to 26.5.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 71.1% for Claude Sonnet 4 and 83.3% for GLM-4.7.
- GLM-4.7 is cheaper at $0.60 / $2.20 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.
- GLM-4.7 accepts more context: 205K tokens versus 200K.
- GLM-4.7 has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 4 | GLM-4.7 | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 40.8 | 42.0 |
| Released | 2025-05-22 | 2025-12-22 |
| Weights | Proprietary | Open |
| Context window | 200K | 205K |
| Max output | 64K | 131K |
| Input $ / M tokens | $3 | $0.60 |
| Output $ / M tokens | $15 | $2.20 |
| Results tracked | 58 | 36 |
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Category by category
Coding Too close to call
Claude Sonnet 4: 43.5 (#88), GLM-4.7: 44.0 (#79)
| Benchmark | Claude Sonnet 4 | GLM-4.7 |
|---|---|---|
| SciCode | 40% | 45.1% |
| LMArena Coding | 1414 | 1454 |
| ALE-Bench | 655.35 | 399.48 |
| SWE-bench Verified (bash only) | 64.9% | — |
| Aider Polyglot | 61.3% | — |
| LMArena WebDev | — | 1435 |
| GSO | 4.9% | — |
| WeirdML | 46.1% | — |
Agentic & Tool Use Claude Sonnet 4 leads
Claude Sonnet 4: 38.5 (#31), GLM-4.7: 26.5 (#103)
| Benchmark | Claude Sonnet 4 | GLM-4.7 |
|---|---|---|
| Terminal-Bench | — | 33.4% |
| TheAgentCompany | 33.1% | — |
| Cybench | 35% | — |
| DeepResearch Bench | 46.6% | — |
| OSWorld | 43.9% | — |
| METR Time Horizons | 62% | — |
| Vending-Bench 2 | — | 2,377 |
Reasoning GLM-4.7 leads
Claude Sonnet 4: 22.9 (#187), GLM-4.7: 24.3 (#164)
| Benchmark | Claude Sonnet 4 | GLM-4.7 |
|---|---|---|
| SimpleBench | 45.5% | 47.7% |
| CritPt | 0.3% | 1.7% |
| LMArena Hard Prompts | 1372 | 1443 |
| Epoch Capabilities Index | 141.69 | 143.51 |
| ARC-AGI-2 | 5.9% | — |
| Kagi LLM Benchmark | 73% | — |
| ARC-AGI-1 | 40% | — |
| Chess Puzzles | — | 6% |
| EnigmaEval | 3.1% | — |
| DTBench | 77.1% | — |
| LMCA | 29% | — |
| ForecastBench | 60.2 | — |
Math Claude Sonnet 4 leads
Claude Sonnet 4: 43.3 (#80), GLM-4.7: 38.6 (#135)
| Benchmark | Claude Sonnet 4 | GLM-4.7 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 71.1% | 83.3% |
| LMArena Math | 1375 | 1423 |
| FrontierMath (Feb 2025 set) | 4.1% | 2.4% |
| FrontierMath Tier 4 (v1) | 0% | 0% |
| ProofBench | — | 6% |
| Omni-MATH | 60.2% | — |
| MATH Level 5 | 84.4% | — |
Knowledge GLM-4.7 leads
Claude Sonnet 4: 41.8 (#108), GLM-4.7: 47.0 (#80)
| Benchmark | Claude Sonnet 4 | GLM-4.7 |
|---|---|---|
| GPQA Diamond | 79.2% | 83.3% |
| Vectara Hallucination Rate | 10.3% | 11.7% |
| LMArena Expert | 1372 | 1424 |
| Humanity's Last Exam | 7.8% | — |
| SimpleQA Verified | — | 32.2% |
| MMLU-Pro | 84.3% | — |
| Confabulations | 13.2% | — |
| GPQA (HELM) | 70.6% | — |
Multimodal Not comparable
Claude Sonnet 4: 26.2 (#121), GLM-4.7: —
| Benchmark | Claude Sonnet 4 | GLM-4.7 |
|---|---|---|
| LMArena Vision | 1191 | — |
| GeoBench | 37% | — |
| VPCT | 34% | — |
| MindCube | 44.8% | — |
Multilingual GLM-4.7 leads
Claude Sonnet 4: 46.7 (#156), GLM-4.7: 52.8 (#79)
| Benchmark | Claude Sonnet 4 | GLM-4.7 |
|---|---|---|
| LMArena Non-English | 1333 | 1417 |
| LMArena Chinese | 1350 | 1495 |
| LMArena French | 1363 | 1432 |
| LMArena German | 1331 | 1424 |
| LMArena Japanese | 1302 | 1439 |
| LMArena Korean | 1291 | 1399 |
| LMArena Russian | 1355 | 1423 |
| LMArena Spanish | 1357 | 1434 |
Instruction Following GLM-4.7 leads
Claude Sonnet 4: 71.7 (#145), GLM-4.7: 74.4 (#95)
| Benchmark | Claude Sonnet 4 | GLM-4.7 |
|---|---|---|
| LMArena Instruction Following | 1376 | 1411 |
| IFEval | 84% | — |
Long Context GLM-4.7 leads
Claude Sonnet 4: 33.7 (#259), GLM-4.7: 42.8 (#116)
| Benchmark | Claude Sonnet 4 | GLM-4.7 |
|---|---|---|
| LMArena Longer Query | 1398 | 1432 |
| Fiction.LiveBench | 46.9% | — |
| CL-bench | — | 15.9% |
| CL-bench Life | — | 10.9% |
Writing & Preference GLM-4.7 leads
Claude Sonnet 4: 57.1 (#132), GLM-4.7: 60.9 (#93)
| Benchmark | Claude Sonnet 4 | GLM-4.7 |
|---|---|---|
| LMArena Text | 1351 | 1435 |
| LMArena Creative Writing | 1345 | 1401 |
| EQ-Bench Creative Writing | 1483 | 1413 |
| LMArena Multi-Turn | 1376 | 1446 |
| Short-Story Creative Writing | 81.4% | — |
| WildBench | 83.8% | — |
Frequently asked questions
Is Claude Sonnet 4 better than GLM-4.7?
GLM-4.7 is the stronger model overall, scoring 42.0 to 40.8 on the Noometry Index.
Which is cheaper, Claude Sonnet 4 or GLM-4.7?
GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Claude Sonnet 4 lists at $3 and $15.
Is Claude Sonnet 4 or GLM-4.7 better for coding?
They score almost the same on coding (43.5 vs 44.0); test both on your own repository before choosing.
Which has the bigger context window?
GLM-4.7 does, with 205K tokens against 200K.
How many benchmarks do Claude Sonnet 4 and GLM-4.7 share?
28 benchmarks have published results for both models. Claude Sonnet 4 has 58 scored results on Noometry and GLM-4.7 has 36.