Model comparison
Claude Sonnet 4.6 vs GLM-5.3-Flash
Claude Sonnet 4.6 and GLM-5.3-Flash score almost the same on the Noometry Index (50.1 vs 49.6), so choose on price, context window or the category you care about most.
Last verified . 32 shared benchmarks.
Summary
- They share 32 benchmarks with published results for both. Claude Sonnet 4.6 scores higher in 3 categories and GLM-5.3-Flash in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Claude Sonnet 4.6 leads 46.1 to 31.7.
- The biggest single-benchmark swing is DeepSWE: 29.9% for Claude Sonnet 4.6 and 63.4% for GLM-5.3-Flash.
- GLM-5.3-Flash is cheaper at $0.15 / $0.50 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.6.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 4.6 | GLM-5.3-Flash | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 50.1 | 49.6 |
| Released | 2026-02-17 | 2026-08-20 |
| Weights | Proprietary | Open |
| Context window | 1M | 1M |
| Max output | 128K | 131K |
| Input $ / M tokens | $3 | $0.15 |
| Output $ / M tokens | $15 | $0.50 |
| Results tracked | 57 | 36 |
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Category by category
Coding GLM-5.3-Flash leads
Claude Sonnet 4.6: 46.0 (#62), GLM-5.3-Flash: 53.7 (#26)
| Benchmark | Claude Sonnet 4.6 | GLM-5.3-Flash |
|---|---|---|
| DeepSWE | 29.9% | 63.4% |
| FrontierCode | 24.3% | 31.8% |
| LMArena WebDev | 1521 | 1614 |
| SciCode | 46.8% | 51.6% |
| LMArena Coding | 1504 | 1506 |
| ALE-Bench | 1,327 | 303.55 |
| SWE-bench Verified | 75.2% | — |
| WeirdML | 66.1% | — |
Agentic & Tool Use Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 39.1 (#26), GLM-5.3-Flash: 34.3 (#41)
| Benchmark | Claude Sonnet 4.6 | GLM-5.3-Flash |
|---|---|---|
| APEX-Agents | 43% | 52.8% |
| GDP.pdf | 18% | 14% |
| Terminal-Bench | 53.4% | — |
| OSWorld 2.0 | 9.3% | — |
| DeepResearch Bench | 54.9% | — |
| OSWorld | 72.1% | — |
| ExploitBench | 23.6% | — |
| GBAEval | 48.8% | — |
| LMArena Search | 1221 | — |
| Vending-Bench 2 | 7,204 | — |
Reasoning Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 46.1 (#40), GLM-5.3-Flash: 31.7 (#69)
| Benchmark | Claude Sonnet 4.6 | GLM-5.3-Flash |
|---|---|---|
| CritPt | 3.1% | 15.4% |
| Chess Puzzles | 13% | 14% |
| LMArena Hard Prompts | 1485 | 1490 |
| Mystery Game Puzzles | 16% | 8% |
| Epoch Capabilities Index | 152.25 | 151.9 |
| ARC-AGI-2 | 60.4% | — |
| NYT Connections (extended) | 80.9% | — |
| ARC-AGI-1 | 86.5% | — |
| Thematic Generalization | 76.3% | — |
| DTBench | 89.9% | — |
| LMCA | 46.5% | — |
| Surface Evolver Bench | — | 52.5% |
| Bench to the Future 3 | — | 0.15 |
| ForecastBench | 62 | — |
Math GLM-5.3-Flash leads
Claude Sonnet 4.6: 51.9 (#41), GLM-5.3-Flash: 53.1 (#38)
| Benchmark | Claude Sonnet 4.6 | GLM-5.3-Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 85.8% | 93.9% |
| ProofBench | 45% | 21% |
| LMArena Math | 1463 | 1499 |
| FrontierMath (Tiers 1-3) | — | 55.8% |
| FrontierMath Tier 4 | — | 17.1% |
| FrontierMath (Feb 2025 set) | 32.4% | — |
| FrontierMath Tier 4 (v1) | 8.3% | — |
Knowledge GLM-5.3-Flash leads
Claude Sonnet 4.6: 51.6 (#60), GLM-5.3-Flash: 58.4 (#33)
| Benchmark | Claude Sonnet 4.6 | GLM-5.3-Flash |
|---|---|---|
| GPQA Diamond | 87.4% | 90.2% |
| LMArena Expert | 1500 | 1512 |
| SimpleQA Verified | 35.5% | — |
| Vectara Hallucination Rate | 10.6% | — |
Multimodal GLM-5.3-Flash leads
Claude Sonnet 4.6: 38.0 (#61), GLM-5.3-Flash: 42.6 (#25)
| Benchmark | Claude Sonnet 4.6 | GLM-5.3-Flash |
|---|---|---|
| LMArena Vision | 1283 | 1304 |
| Blueprint-Bench 2 | 6.7% | — |
| LMArena Document | 1482 | — |
Multilingual GLM-5.3-Flash leads
Claude Sonnet 4.6: 54.6 (#39), GLM-5.3-Flash: 56.2 (#24)
| Benchmark | Claude Sonnet 4.6 | GLM-5.3-Flash |
|---|---|---|
| LMArena Non-English | 1440 | 1462 |
| LMArena Chinese | 1491 | 1529 |
| LMArena French | 1465 | 1495 |
| LMArena German | 1428 | 1457 |
| LMArena Japanese | 1419 | 1420 |
| LMArena Korean | 1411 | 1443 |
| LMArena Russian | 1440 | 1472 |
| LMArena Spanish | 1465 | 1471 |
Instruction Following Too close to call
Claude Sonnet 4.6: 77.6 (#23), GLM-5.3-Flash: 77.8 (#17)
| Benchmark | Claude Sonnet 4.6 | GLM-5.3-Flash |
|---|---|---|
| LMArena Instruction Following | 1476 | 1480 |
Long Context Too close to call
Claude Sonnet 4.6: 45.3 (#40), GLM-5.3-Flash: 45.3 (#41)
| Benchmark | Claude Sonnet 4.6 | GLM-5.3-Flash |
|---|---|---|
| LMArena Longer Query | 1479 | 1479 |
Writing & Preference Claude Sonnet 4.6 leads
Claude Sonnet 4.6: 70.4 (#22), GLM-5.3-Flash: 65.4 (#49)
| Benchmark | Claude Sonnet 4.6 | GLM-5.3-Flash |
|---|---|---|
| LMArena Text | 1458 | 1471 |
| LMArena Creative Writing | 1435 | 1440 |
| LMArena Multi-Turn | 1464 | 1471 |
| EQ-Bench Creative Writing | 1810 | — |
| EQ-Bench 4 | 1207 | — |
Frequently asked questions
Is Claude Sonnet 4.6 better than GLM-5.3-Flash?
Claude Sonnet 4.6 and GLM-5.3-Flash score almost the same on the Noometry Index (50.1 vs 49.6), so choose on price, context window or the category you care about most.
Which is cheaper, Claude Sonnet 4.6 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 4.6 lists at $3 and $15.
Is Claude Sonnet 4.6 or GLM-5.3-Flash better for coding?
GLM-5.3-Flash scores higher on coding benchmarks: 53.7 versus 46.0 in the Noometry coding category.
Which has the bigger context window?
Both accept 1M tokens.
How many benchmarks do Claude Sonnet 4.6 and GLM-5.3-Flash share?
32 benchmarks have published results for both models. Claude Sonnet 4.6 has 57 scored results on Noometry and GLM-5.3-Flash has 36.