Model comparison
Claude Sonnet 5.5 vs GLM-5.3-Flash
Claude Sonnet 5.5 is the stronger model overall, scoring 61.9 to 51.8 on the Noometry Index. GLM-5.3-Flash costs 17× less per token, which makes it the better buy when Claude Sonnet 5.5's lead doesn't matter for your workload.
Last verified . 28 shared benchmarks.
Summary
- They share 28 benchmarks with published results for both. Claude Sonnet 5.5 scores higher in 9 categories and GLM-5.3-Flash in 1 category; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where Claude Sonnet 5.5 leads 87.9 to 53.3.
- The biggest single-benchmark swing is ProofBench: 100% for Claude Sonnet 5.5 and 21% for GLM-5.3-Flash.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $2 / $10 for Claude Sonnet 5.5.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 5.5 | GLM-5.3-Flash | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 61.9 | 51.8 |
| Released | 2026-09-28 | 2026-08-20 |
| Weights | Proprietary | Open |
| Context window | 1M | 1M |
| Max output | 128K | 131K |
| Input $ / M tokens | $2 | $0.15 |
| Output $ / M tokens | $10 | $0.50 |
| Results tracked | 32 | 40 |
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Category by category
Coding Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 67.3 (#6), GLM-5.3-Flash: 53.1 (#31)
| Benchmark | Claude Sonnet 5.5 | GLM-5.3-Flash |
|---|---|---|
| FrontierCode | 52.1% | 31.8% |
| CursorBench | 55.5% | 36.8% |
| LMArena WebDev | 1774 | 1609 |
| FrontierSWE | 61.9% | 18.1% |
| SciCode | 61% | 51.6% |
| LMArena Coding | 1513 | 1508 |
| ALE-Bench | 1,819 | 303.55 |
| DeepSWE | — | 63.4% |
Agentic & Tool Use Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 45.0 (#16), GLM-5.3-Flash: 34.2 (#47)
| Benchmark | Claude Sonnet 5.5 | GLM-5.3-Flash |
|---|---|---|
| APEX-Agents | 75.5% | 52.8% |
| GDP.pdf | — | 14% |
Reasoning Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 54.0 (#28), GLM-5.3-Flash: 48.0 (#42)
| Benchmark | Claude Sonnet 5.5 | GLM-5.3-Flash |
|---|---|---|
| CritPt | 31.4% | 15.4% |
| LMArena Hard Prompts | 1495 | 1491 |
| Mystery Game Puzzles | 65% | 8% |
| Epoch Capabilities Index | 165.03 | 151.88 |
| ARC-AGI-2 | — | 65.8% |
| NYT Connections (extended) | 80.5% | — |
| ARC-AGI-1 | — | 91% |
| Chess Puzzles | — | 14% |
| Surface Evolver Bench | — | 52.5% |
| Bench to the Future 3 | — | 0.15 |
Math Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 87.9 (#6), GLM-5.3-Flash: 53.3 (#47)
| Benchmark | Claude Sonnet 5.5 | GLM-5.3-Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | 88.8% | 55.8% |
| FrontierMath Tier 4 | 80.5% | 17.1% |
| OTIS Mock AIME 2024-2025 | 100% | 93.9% |
| ProofBench | 100% | 21% |
| LMArena Math | 1510 | 1500 |
| FrontierMath Erdős | 2.9% | — |
Knowledge Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 66.0 (#12), GLM-5.3-Flash: 58.4 (#36)
| Benchmark | Claude Sonnet 5.5 | GLM-5.3-Flash |
|---|---|---|
| GPQA Diamond | 95.6% | 90.2% |
| LMArena Expert | 1540 | 1513 |
| SimpleQA Verified | 46.5% | — |
Multimodal Claude Sonnet 5.5 leads
Claude Sonnet 5.5: 51.5 (#6), GLM-5.3-Flash: 42.8 (#27)
| Benchmark | Claude Sonnet 5.5 | GLM-5.3-Flash |
|---|---|---|
| LMArena Vision | 1289 | 1296 |
| Furniture Assembly | 75% | — |
Multilingual Too close to call
Claude Sonnet 5.5: 55.3 (#30), GLM-5.3-Flash: 56.0 (#25)
| Benchmark | Claude Sonnet 5.5 | GLM-5.3-Flash |
|---|---|---|
| LMArena Non-English | 1452 | 1462 |
| LMArena Chinese | 1522 | 1527 |
| LMArena Russian | 1451 | 1469 |
| LMArena French | — | 1496 |
| LMArena German | — | 1470 |
| LMArena Japanese | — | 1429 |
| LMArena Korean | — | 1446 |
| LMArena Spanish | — | 1471 |
Instruction Following Too close to call
Claude Sonnet 5.5: 78.3 (#11), GLM-5.3-Flash: 77.5 (#20)
| Benchmark | Claude Sonnet 5.5 | GLM-5.3-Flash |
|---|---|---|
| LMArena Instruction Following | 1495 | 1478 |
Long Context Too close to call
Claude Sonnet 5.5: 45.9 (#28), GLM-5.3-Flash: 45.4 (#39)
| Benchmark | Claude Sonnet 5.5 | GLM-5.3-Flash |
|---|---|---|
| LMArena Longer Query | 1498 | 1482 |
Writing & Preference Too close to call
Claude Sonnet 5.5: 66.0 (#40), GLM-5.3-Flash: 65.3 (#50)
| Benchmark | Claude Sonnet 5.5 | GLM-5.3-Flash |
|---|---|---|
| LMArena Text | 1471 | 1471 |
| LMArena Creative Writing | 1465 | 1442 |
| LMArena Multi-Turn | 1474 | 1467 |
Frequently asked questions
Is Claude Sonnet 5.5 better than GLM-5.3-Flash?
Claude Sonnet 5.5 is the stronger model overall, scoring 61.9 to 51.8 on the Noometry Index. GLM-5.3-Flash costs 17× 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-5.3-Flash?
GLM-5.3-Flash is cheaper. It lists at $0.15 per million input tokens and $0.50 per million output tokens; Claude Sonnet 5.5 lists at $2 and $10.
Is Claude Sonnet 5.5 or GLM-5.3-Flash better for coding?
Claude Sonnet 5.5 scores higher on coding benchmarks: 67.3 versus 53.1 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-5.3-Flash share?
28 benchmarks have published results for both models. Claude Sonnet 5.5 has 32 scored results on Noometry and GLM-5.3-Flash has 40.