Model comparison
Claude Sonnet 4.5 vs GLM-5V-Turbo
Claude Sonnet 4.5 and GLM-5V-Turbo score almost the same on the Noometry Index (44.0 vs 43.1), so choose on price, context window or the category you care about most.
Last verified . 18 shared benchmarks.
Summary
- They share 18 benchmarks with published results for both. Claude Sonnet 4.5 scores higher in 6 categories and GLM-5V-Turbo in 3 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Claude Sonnet 4.5 leads 48.4 to 39.9.
- GLM-5V-Turbo is cheaper at $1.20 / $4 per million input/output tokens, against $3 / $15 for Claude Sonnet 4.5.
- Claude Sonnet 4.5 accepts more context: 1M tokens versus 200K.
Side by side
| Claude Sonnet 4.5 | GLM-5V-Turbo | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 44.0 | 43.1 |
| Released | 2025-09-29 | 2026-04-01 |
| Weights | Proprietary | Proprietary |
| Context window | 1M | 200K |
| Max output | 64K | 131K |
| Input $ / M tokens | $3 | $1.20 |
| Output $ / M tokens | $15 | $4 |
| Results tracked | 73 | 19 |
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Category by category
Coding Claude Sonnet 4.5 leads
Claude Sonnet 4.5: 47.8 (#54), GLM-5V-Turbo: 41.8 (#105)
| Benchmark | Claude Sonnet 4.5 | GLM-5V-Turbo |
|---|---|---|
| LMArena WebDev | 1393 | 1400 |
| LMArena Coding | 1489 | 1467 |
| SWE-bench Verified | 71.3% | — |
| SWE-bench Verified (bash only) | 71.4% | — |
| SWE-bench Multilingual | 67% | — |
| SciCode | 44.7% | — |
| GSO | 14.7% | — |
| WeirdML | 47.7% | — |
| ALE-Bench | 796.15 | — |
| AlgoTune | 1.52 | — |
Agentic & Tool Use Not comparable
Claude Sonnet 4.5: 38.1 (#30), GLM-5V-Turbo: —
| Benchmark | Claude Sonnet 4.5 | GLM-5V-Turbo |
|---|---|---|
| Terminal-Bench | 46.5% | — |
| Berkeley Function Calling Leaderboard | 73.2% | — |
| GDPval | 42.5% | — |
| Remote Labor Index | 2.1% | — |
| τ²-bench Airline | 72% | — |
| τ²-bench Banking | 25.3% | — |
| τ²-bench Retail | 72.4% | — |
| τ²-bench Telecom | 84.9% | — |
| Cybench | 60% | — |
| DeepResearch Bench | 52.6% | — |
| OSWorld | 62.9% | — |
| LMArena Search | 1159 | — |
| METR Time Horizons | 67.4% | — |
| Vending-Bench 2 | 3,839 | — |
Reasoning GLM-5V-Turbo leads
Claude Sonnet 4.5: 26.9 (#113), GLM-5V-Turbo: 28.5 (#87)
| Benchmark | Claude Sonnet 4.5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Hard Prompts | 1462 | 1443 |
| ARC-AGI-2 | 13.6% | — |
| SimpleBench | 54.3% | — |
| Kagi LLM Benchmark | 57.9% | — |
| NYT Connections (extended) | 37.3% | — |
| ARC-AGI-1 | 63.7% | — |
| CritPt | 1.1% | — |
| Chess Puzzles | 12% | — |
| EnigmaEval | 6% | — |
| EBR-Bench | 2.4% | — |
| Mystery Game Puzzles | 17% | — |
| DTBench | 83.2% | — |
| LMCA | 38.8% | — |
| Epoch Capabilities Index | 146.84 | — |
| ForecastBench | 61.9 | — |
Math GLM-5V-Turbo leads
Claude Sonnet 4.5: 31.9 (#190), GLM-5V-Turbo: 36.6 (#109)
| Benchmark | Claude Sonnet 4.5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Math | 1448 | 1440 |
| FrontierMath (Tiers 1-3) | 23.9% | — |
| FrontierMath Tier 4 | 2.4% | — |
| OTIS Mock AIME 2024-2025 | 77.8% | — |
| ProofBench | 19% | — |
| Omni-MATH | 55.3% | — |
| MATH Level 5 | 97.7% | — |
| FrontierMath (Feb 2025 set) | 15.2% | — |
| FrontierMath Tier 4 (v1) | 4.2% | — |
Knowledge Claude Sonnet 4.5 leads
Claude Sonnet 4.5: 48.4 (#70), GLM-5V-Turbo: 39.9 (#113)
| Benchmark | Claude Sonnet 4.5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Expert | 1483 | 1451 |
| GPQA Diamond | 82.3% | — |
| Humanity's Last Exam | 13.7% | — |
| SimpleQA Verified | 30.7% | — |
| MMLU-Pro | 86.9% | — |
| Vectara Hallucination Rate | 12% | — |
| GPQA (HELM) | 68.6% | — |
Multimodal GLM-5V-Turbo leads
Claude Sonnet 4.5: 34.1 (#84), GLM-5V-Turbo: 40.1 (#41)
| Benchmark | Claude Sonnet 4.5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Document | 1450 | 1416 |
| LMArena Vision | — | 1264 |
| VPCT | 39.8% | — |
Multilingual Too close to call
Claude Sonnet 4.5: 53.6 (#65), GLM-5V-Turbo: 53.2 (#69)
| Benchmark | Claude Sonnet 4.5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Non-English | 1425 | 1420 |
| LMArena Chinese | 1459 | 1488 |
| LMArena French | 1459 | 1443 |
| LMArena German | 1427 | 1422 |
| LMArena Korean | 1403 | 1399 |
| LMArena Russian | 1436 | 1432 |
| LMArena Spanish | 1457 | 1446 |
| LMArena Japanese | 1390 | — |
Instruction Following Too close to call
Claude Sonnet 4.5: 75.2 (#74), GLM-5V-Turbo: 75.1 (#75)
| Benchmark | Claude Sonnet 4.5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Instruction Following | 1459 | 1422 |
| IFEval | 85% | — |
Long Context Claude Sonnet 4.5 leads
Claude Sonnet 4.5: 45.2 (#45), GLM-5V-Turbo: 44.0 (#76)
| Benchmark | Claude Sonnet 4.5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Longer Query | 1476 | 1439 |
Writing & Preference Claude Sonnet 4.5 leads
Claude Sonnet 4.5: 66.7 (#33), GLM-5V-Turbo: 62.6 (#69)
| Benchmark | Claude Sonnet 4.5 | GLM-5V-Turbo |
|---|---|---|
| LMArena Text | 1439 | 1437 |
| LMArena Creative Writing | 1442 | 1414 |
| LMArena Multi-Turn | 1465 | 1432 |
| EQ-Bench Creative Writing | 1678 | — |
| WildBench | 85.4% | — |
Frequently asked questions
Is Claude Sonnet 4.5 better than GLM-5V-Turbo?
Claude Sonnet 4.5 and GLM-5V-Turbo score almost the same on the Noometry Index (44.0 vs 43.1), so choose on price, context window or the category you care about most.
Which is cheaper, Claude Sonnet 4.5 or GLM-5V-Turbo?
GLM-5V-Turbo is cheaper. It lists at $1.20 per million input tokens and $4 per million output tokens; Claude Sonnet 4.5 lists at $3 and $15.
Is Claude Sonnet 4.5 or GLM-5V-Turbo better for coding?
Claude Sonnet 4.5 scores higher on coding benchmarks: 47.8 versus 41.8 in the Noometry coding category.
Which has the bigger context window?
Claude Sonnet 4.5 does, with 1M tokens against 200K.
How many benchmarks do Claude Sonnet 4.5 and GLM-5V-Turbo share?
18 benchmarks have published results for both models. Claude Sonnet 4.5 has 73 scored results on Noometry and GLM-5V-Turbo has 19.