Model comparison
Claude Sonnet 5 vs GLM-5.1
Claude Sonnet 5 is the stronger model overall, scoring 54.5 to 47.6 on the Noometry Index. GLM-5.1 costs 1.9× less per token, which makes it the better buy when Claude Sonnet 5's lead doesn't matter for your workload.
Last verified . 35 shared benchmarks.
Summary
- They share 35 benchmarks with published results for both. Claude Sonnet 5 scores higher in 7 categories and GLM-5.1 in 2 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Claude Sonnet 5 leads 42.7 to 24.8.
- The biggest single-benchmark swing is GBAEval: 65.3% for Claude Sonnet 5 and 0% for GLM-5.1.
- GLM-5.1 is cheaper at $1.40 / $4.40 per million input/output tokens, against $2 / $10 for Claude Sonnet 5.
- Claude Sonnet 5 accepts more context: 1M tokens versus 200K.
- GLM-5.1 has downloadable open weights; the other is API-only.
Side by side
| Claude Sonnet 5 | GLM-5.1 | |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 54.5 | 47.6 |
| Released | 2026-06-29 | 2026-04-07 |
| Weights | Proprietary | Open |
| Context window | 1M | 200K |
| Max output | 128K | 131K |
| Input $ / M tokens | $2 | $1.40 |
| Output $ / M tokens | $10 | $4.40 |
| Results tracked | 51 | 41 |
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Category by category
Coding Claude Sonnet 5 leads
Claude Sonnet 5: 55.5 (#20), GLM-5.1: 48.5 (#52)
| Benchmark | Claude Sonnet 5 | GLM-5.1 |
|---|---|---|
| LMArena WebDev | 1540 | 1509 |
| SciCode | 53.6% | 43.8% |
| WeirdML | 68.8% | 57.1% |
| LMArena Coding | 1483 | 1486 |
| ALE-Bench | 1,463 | 887.1 |
| SWE-bench Verified | — | 74.2% |
| DeepSWE | 53.8% | — |
| FrontierCode | 42.7% | — |
| CursorBench | 34.1% | — |
| GSO | 37.3% | — |
Agentic & Tool Use Claude Sonnet 5 leads
Claude Sonnet 5: 42.7 (#16), GLM-5.1: 24.8 (#106)
| Benchmark | Claude Sonnet 5 | GLM-5.1 |
|---|---|---|
| APEX-Agents | 54.5% | 40.9% |
| GBAEval | 65.3% | 0% |
| Vending-Bench 2 | 6,378 | 5,634 |
| ExploitBench | — | 18.1% |
| LMArena Search | 1194 | — |
Reasoning Claude Sonnet 5 leads
Claude Sonnet 5: 48.2 (#37), GLM-5.1: 38.2 (#57)
| Benchmark | Claude Sonnet 5 | GLM-5.1 |
|---|---|---|
| SimpleBench | 60.6% | 55.1% |
| NYT Connections (extended) | 75.1% | 77.7% |
| CritPt | 16.9% | 4.6% |
| Chess Puzzles | 35% | 19% |
| LMArena Hard Prompts | 1461 | 1472 |
| Epoch Capabilities Index | 156.34 | 149.86 |
| Thematic Generalization | — | 69.8% |
| Mystery Game Puzzles | 35% | — |
| DTBench | 92.5% | — |
| LMCA | 50% | — |
| Surface Evolver Bench | 60% | — |
| Bench to the Future 3 | 0.14 | — |
| ForecastBench | 61.1 | — |
Math Claude Sonnet 5 leads
Claude Sonnet 5: 66.1 (#21), GLM-5.1: 49.0 (#48)
| Benchmark | Claude Sonnet 5 | GLM-5.1 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 65.6% | 36.8% |
| OTIS Mock AIME 2024-2025 | 94.7% | 93.3% |
| ProofBench | 77% | 22.2% |
| LMArena Math | 1467 | 1472 |
| FrontierMath Tier 4 | 29.3% | — |
| MathArena Final-Answer Competitions | — | 67.1% |
| FrontierMath (Feb 2025 set) | — | 33.4% |
| FrontierMath Tier 4 (v1) | — | 12.5% |
Knowledge Too close to call
Claude Sonnet 5: 55.7 (#42), GLM-5.1: 55.0 (#45)
| Benchmark | Claude Sonnet 5 | GLM-5.1 |
|---|---|---|
| GPQA Diamond | 90.5% | 89.9% |
| SimpleQA Verified | 33.7% | 34% |
| LMArena Expert | 1491 | 1477 |
Multimodal Not comparable
Claude Sonnet 5: 42.4 (#26), GLM-5.1: —
| Benchmark | Claude Sonnet 5 | GLM-5.1 |
|---|---|---|
| LMArena Vision | 1275 | — |
| Blueprint-Bench 2 | 24.9% | — |
| LMArena Document | 1466 | — |
Multilingual GLM-5.1 leads
Claude Sonnet 5: 54.0 (#55), GLM-5.1: 55.2 (#34)
| Benchmark | Claude Sonnet 5 | GLM-5.1 |
|---|---|---|
| LMArena Non-English | 1431 | 1448 |
| LMArena Chinese | 1475 | 1516 |
| LMArena French | 1457 | 1478 |
| LMArena German | 1448 | 1466 |
| LMArena Japanese | 1422 | 1436 |
| LMArena Korean | 1411 | 1423 |
| LMArena Russian | 1452 | 1453 |
| LMArena Spanish | 1436 | 1467 |
Instruction Following Too close to call
Claude Sonnet 5: 76.6 (#39), GLM-5.1: 76.5 (#41)
| Benchmark | Claude Sonnet 5 | GLM-5.1 |
|---|---|---|
| LMArena Instruction Following | 1453 | 1451 |
Long Context Too close to call
Claude Sonnet 5: 44.8 (#53), GLM-5.1: 44.9 (#51)
| Benchmark | Claude Sonnet 5 | GLM-5.1 |
|---|---|---|
| LMArena Longer Query | 1464 | 1467 |
Writing & Preference Claude Sonnet 5 leads
Claude Sonnet 5: 69.4 (#24), GLM-5.1: 67.2 (#29)
| Benchmark | Claude Sonnet 5 | GLM-5.1 |
|---|---|---|
| LMArena Text | 1443 | 1462 |
| LMArena Creative Writing | 1416 | 1454 |
| EQ-Bench Creative Writing | 1794 | 1592 |
| LMArena Multi-Turn | 1454 | 1473 |
| EQ-Bench 4 | 1236 | — |
Frequently asked questions
Is Claude Sonnet 5 better than GLM-5.1?
Claude Sonnet 5 is the stronger model overall, scoring 54.5 to 47.6 on the Noometry Index. GLM-5.1 costs 1.9× less per token, which makes it the better buy when Claude Sonnet 5's lead doesn't matter for your workload.
Which is cheaper, Claude Sonnet 5 or GLM-5.1?
GLM-5.1 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; Claude Sonnet 5 lists at $2 and $10.
Is Claude Sonnet 5 or GLM-5.1 better for coding?
Claude Sonnet 5 scores higher on coding benchmarks: 55.5 versus 48.5 in the Noometry coding category.
Which has the bigger context window?
Claude Sonnet 5 does, with 1M tokens against 200K.
How many benchmarks do Claude Sonnet 5 and GLM-5.1 share?
35 benchmarks have published results for both models. Claude Sonnet 5 has 51 scored results on Noometry and GLM-5.1 has 41.