Model comparison
Claude Sonnet 5.5 vs GLM-5.2
Claude Sonnet 5.5 is the stronger model overall, scoring 61.9 to 51.1 on the Noometry Index. GLM-5.2 costs 1.9× less per token, which makes it the better buy when Claude Sonnet 5.5's lead doesn't matter for your workload.
Last verified . 27 shared benchmarks.
Summary
- They share 27 benchmarks with published results for both. Claude Sonnet 5.5 scores higher in 7 categories and GLM-5.2 in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Sonnet 5.5 leads 87.9 to 55.7.
- The biggest single-benchmark swing is ProofBench: 100% for Claude Sonnet 5.5 and 35% for GLM-5.2.
- GLM-5.2 is cheaper at $1.40 / $4.40 per million input/output tokens, against $2 / $10 for Claude Sonnet 5.5.
- GLM-5.2 has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 5.5 | GLM-5.2 | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 61.9 | 51.1 |
| Released | 2026-09-28 | 2026-06-13 |
| Weights | Proprietary | Open |
| Context window | 1M | 1M |
| Max output | 128K | 131K |
| Input $ / M tokens | $2 | $1.40 |
| Output $ / M tokens | $10 | $4.40 |
| Results tracked | 32 | 51 |
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Category by category
Coding Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 67.3 (#6), GLM-5.2: 51.3 (#41)
| Benchmark | Claude Sonnet 5.5 | GLM-5.2 |
|---|---|---|
| FrontierCode | 52.1% | 24.5% |
| LMArena WebDev | 1774 | 1603 |
| SciCode | 61% | 50.5% |
| LMArena Coding | 1513 | 1485 |
| ALE-Bench | 1,819 | 1,047 |
| SWE-bench Verified | — | 78.7% |
| DeepSWE | — | 43.8% |
| CursorBench | 55.5% | — |
| FrontierSWE | 61.9% | — |
| WeirdML | — | 70.1% |
Agentic & Tool Use Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 45.0 (#16), GLM-5.2: 32.4 (#63)
| Benchmark | Claude Sonnet 5.5 | GLM-5.2 |
|---|---|---|
| APEX-Agents | 75.5% | 45.2% |
| τ²-bench Banking | — | 37.1% |
| PostTrainBench | — | 31.7% |
| GBAEval | — | 0% |
| Vending-Bench 2 | — | 8,314 |
Reasoning Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 54.0 (#28), GLM-5.2: 42.3 (#52)
| Benchmark | Claude Sonnet 5.5 | GLM-5.2 |
|---|---|---|
| NYT Connections (extended) | 80.5% | 74.3% |
| CritPt | 31.4% | 20.9% |
| LMArena Hard Prompts | 1495 | 1480 |
| Mystery Game Puzzles | 65% | 19% |
| Epoch Capabilities Index | 165.03 | 151.78 |
| ARC-AGI-2 | — | 22.8% |
| SimpleBench | — | 58.8% |
| Kagi LLM Benchmark | — | 62.6% |
| ARC-AGI-1 | — | 77% |
| Chess Puzzles | — | 21% |
| EBR-Bench | — | 9.5% |
| DTBench | — | 93.6% |
| LMCA | — | 45.8% |
| Surface Evolver Bench | — | 55.6% |
Math Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 87.9 (#6), GLM-5.2: 55.7 (#43)
| Benchmark | Claude Sonnet 5.5 | GLM-5.2 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 88.8% | 59.2% |
| FrontierMath Tier 4 | 80.5% | 29.3% |
| OTIS Mock AIME 2024-2025 | 100% | 86.4% |
| ProofBench | 100% | 35% |
| LMArena Math | 1510 | 1482 |
| MathArena Final-Answer Competitions | — | 67.6% |
| FrontierMath Erdős | 2.9% | — |
Knowledge Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 66.0 (#12), GLM-5.2: 57.1 (#40)
| Benchmark | Claude Sonnet 5.5 | GLM-5.2 |
|---|---|---|
| GPQA Diamond | 95.6% | 91.9% |
| SimpleQA Verified | 46.5% | 34.2% |
| LMArena Expert | 1540 | 1486 |
Multimodal Not comparable
Claude Sonnet 5.5: 51.5 (#6), GLM-5.2: —
| Benchmark | Claude Sonnet 5.5 | GLM-5.2 |
|---|---|---|
| LMArena Vision | 1289 | — |
| Furniture Assembly | 75% | — |
Multilingual Too close to call
Claude Sonnet 5.5: 55.3 (#30), GLM-5.2: 55.8 (#26)
| Benchmark | Claude Sonnet 5.5 | GLM-5.2 |
|---|---|---|
| LMArena Non-English | 1452 | 1459 |
| LMArena Chinese | 1522 | 1519 |
| LMArena Russian | 1451 | 1466 |
| LMArena French | — | 1479 |
| LMArena German | — | 1468 |
| LMArena Japanese | — | 1451 |
| LMArena Korean | — | 1445 |
| LMArena Spanish | — | 1477 |
Instruction Following Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 78.3 (#11), GLM-5.2: 76.9 (#34)
| Benchmark | Claude Sonnet 5.5 | GLM-5.2 |
|---|---|---|
| LMArena Instruction Following | 1495 | 1465 |
Long Context Too close to call
Claude Sonnet 5.5: 45.9 (#28), GLM-5.2: 45.3 (#43)
| Benchmark | Claude Sonnet 5.5 | GLM-5.2 |
|---|---|---|
| LMArena Longer Query | 1498 | 1479 |
Writing & Preference GLM-5.2 leads
Claude Sonnet 5.5: 66.0 (#40), GLM-5.2: 70.4 (#21)
| Benchmark | Claude Sonnet 5.5 | GLM-5.2 |
|---|---|---|
| LMArena Text | 1471 | 1470 |
| LMArena Creative Writing | 1465 | 1462 |
| LMArena Multi-Turn | 1474 | 1469 |
| EQ-Bench Creative Writing | — | 1757 |
| EQ-Bench 4 | — | 1222 |
Frequently asked questions
Is Claude Sonnet 5.5 better than GLM-5.2?
Claude Sonnet 5.5 is the stronger model overall, scoring 61.9 to 51.1 on the Noometry Index. GLM-5.2 costs 1.9× less per token, which makes it the better buy when Claude Sonnet 5.5's lead doesn't matter for your workload.
Which is cheaper, Claude Sonnet 5.5 or GLM-5.2?
GLM-5.2 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; Claude Sonnet 5.5 lists at $2 and $10.
Is Claude Sonnet 5.5 or GLM-5.2 better for coding?
Claude Sonnet 5.5 scores higher on coding benchmarks: 67.3 versus 51.3 in the Noometry coding category.
Which has the bigger context window?
Both accept 1M tokens.
How many benchmarks do Claude Sonnet 5.5 and GLM-5.2 share?
27 benchmarks have published results for both models. Claude Sonnet 5.5 has 32 scored results on Noometry and GLM-5.2 has 51.