Claude Sonnet 5.5 vs GLM 5.2
Updated October 21, 2026. 64 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Claude Sonnet 5.5 for coding: it scores 88.9 on the Vibe Coding Index against 57.7 for GLM 5.2.
Pick GLM 5.2 when output tokens cost 1.4x less, or when the context window is larger, 1.05M against 1M tokens.
- Shared results
- 64
- Claude Sonnet 5.5 only
- 31
- GLM 5.2 only
- 33
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, four public coding benchmarks
Claude Sonnet 5.5
Claude Sonnet 5.5 scores 88.9 against 57.7.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Claude Sonnet 5.5
Claude Sonnet 5.5 leads, 56.0 against 33.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GLM 5.2 has a AA Agentic Index result, 38.4.
Directional only
Reasoning
GPQA Diamond
No call
Only GLM 5.2 has a GPQA Diamond result, 85.6%.
Directional only
Knowledge
MMLU Pro
No call
Only GLM 5.2 has a MMLU Pro result, 86.7%.
Directional only
Web design
Design Arena: websites
Claude Sonnet 5.5
Claude Sonnet 5.5 leads, 1326 against 1285.
Same board, both measured
General
Vals Index
No call
Only Claude Sonnet 5.5 has a Vals Index result, 70.8%.
Directional only
Long documents
Listed context window
GLM 5.2
GLM 5.2 takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.2
Claude Sonnet 5.5 $0.0070, GLM 5.2 $0.0035 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GLM 5.2 has the number, $0.86.
Directional only
At a glance
- Coding index
- Claude Sonnet 5.5 88.9 from 2 benchmarks, GLM 5.2 57.7 from 1 benchmark.
- Widest category
- Math, 27.5 points apart on average over 6 shared benchmarks.
- Widest single gap
- ProofBench: Claude Sonnet 5.5 100.0% against GLM 5.2 35.0%, 65.0 points apart on a 0 to 100 scale.
- Output price
- Claude Sonnet 5.5 $10.00 against GLM 5.2 $7.00 per million output tokens, 1.4x apart.
- Context window
- Claude Sonnet 5.5 takes 1M tokens, GLM 5.2 1.05M.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Claude Sonnet 5.5 | Bars | GLM 5.2 | Ties |
|---|---|---|---|---|
| Coding | 12 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 8 | 0 | ||
| Reasoning | 7 | 0 | ||
| Math | 6 | 0 | ||
| Knowledge | 3 | 3 | ||
| Web design | 6 | 0 | ||
| General | 13 | 4 | ||
| All shared boards | 57 | 7 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index120
| Benchmark | Claude Sonnet 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| LiveBench coding | 94.7% | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena WebDev | 1768 | 1604 | Claude Sonnet 5.5 |
| AA Coding Index | Not measured | 68.8 | Only GLM 5.2 measured |
| LiveCodeBench (Vals AI) | Not measured | 69.5% | Only GLM 5.2 measured |
| SWE-bench Verified (Vals AI) | Not measured | 82.8% | Only GLM 5.2 measured |
| Terminal-Bench 4 (Vals AI) | 64.1% | Not measured | Only Claude Sonnet 5.5 measured |
| Vibe Code Bench (Vals AI) | 92.4% | 64.0% | Claude Sonnet 5.5 |
| Code migration (Vals AI) | 69.8% | 37.9% | Claude Sonnet 5.5 |
| ProgramBench (Vals AI) | 6.5% | 0.5% | Claude Sonnet 5.5 |
| IOI (Vals AI) | 83.1% | Not measured | Only Claude Sonnet 5.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 83.2% | 67.8% | Claude Sonnet 5.5 |
| SWE-bench Multimodal (Vals AI) | 58.3% | Not measured | Only Claude Sonnet 5.5 measured |
| SkillsBench (Vals AI) | Not measured | 45.1% | Only GLM 5.2 measured |
| CyberBench (Vals AI) | 59.6% | Not measured | Only Claude Sonnet 5.5 measured |
| SciCode | 61.0% | 51.2% | Claude Sonnet 5.5 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 50.8% | Only GLM 5.2 measured |
| FrontierCode | 52.1% | 24.5% | Claude Sonnet 5.5 |
| FrontierSWE | 61.9% | Not measured | Only Claude Sonnet 5.5 measured |
| WeirdML | Not measured | 70.1% | Only GLM 5.2 measured |
| ALE-Bench | 1819.1 | 1047.0 | Claude Sonnet 5.5 |
| LMArena Text: coding | 1513 | 1487 | Claude Sonnet 5.5 |
| LMArena Text: software and IT | 1504 | 1486 | Claude Sonnet 5.5 |
| LMArena WebDev: React | 1817 | 1617 | Claude Sonnet 5.5 |
| LMArena WebDev: HTML | 1741 | 1565 | Claude Sonnet 5.5 |
| LMArena WebDev: from an image | 1737 | Not measured | Only Claude Sonnet 5.5 measured |
| Neither model has a result on the other 13 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Claude Sonnet 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| AA Intelligence Index | 56.0 | 33.7 | Claude Sonnet 5.5 |
| Epoch Capabilities Index | 166.2 | 151.9 | Claude Sonnet 5.5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | Claude Sonnet 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 38.4 | Only GLM 5.2 measured |
| Design Arena: agents building web apps | 1303 | 1222 | Claude Sonnet 5.5 |
| Design Arena: agents building full-stack apps | Not measured | 1241 | Only GLM 5.2 measured |
| Design Arena: agents building mobile apps | 1265 | 1160 | Claude Sonnet 5.5 |
| Design Arena: agents building Android apps | Not measured | 1184 | Only GLM 5.2 measured |
| Design Arena: agents building Godot games | Not measured | 1142 | Only GLM 5.2 measured |
| Design Arena: agents building games | Not measured | 1206 | Only GLM 5.2 measured |
| Design Arena: HTML slides | Not measured | 1175 | Only GLM 5.2 measured |
| Design Arena: PowerPoint slides | Not measured | 1195 | Only GLM 5.2 measured |
| Design Arena: spreadsheets | 1245 | Not measured | Only Claude Sonnet 5.5 measured |
| LiveBench research | 83.6% | Not measured | Only Claude Sonnet 5.5 measured |
| LiveBench browser | 84.0% | Not measured | Only Claude Sonnet 5.5 measured |
| LiveBench long agentic | 78.8% | Not measured | Only Claude Sonnet 5.5 measured |
| SREBench (Vals AI) | 30.1% | 0.0% | Claude Sonnet 5.5 |
| Finance Agent (Vals AI) | 58.1% | 49.7% | Claude Sonnet 5.5 |
| Tax Agent Bench (Vals AI) | 42.0% | Not measured | Only Claude Sonnet 5.5 measured |
| Legal Research Bench (Vals AI) | 48.1% | 31.3% | Claude Sonnet 5.5 |
| Harvey's Legal Agent Benchmark (Vals AI) | 10.4% | Not measured | Only Claude Sonnet 5.5 measured |
| Excel Modeling Benchmark (Vals AI) | 75.7% | 61.5% | Claude Sonnet 5.5 |
| BioMysteryBench (Vals AI) | 81.1% | Not measured | Only Claude Sonnet 5.5 measured |
| Terminal-Bench-Science (Vals AI) | 47.1% | Not measured | Only Claude Sonnet 5.5 measured |
| Vals Science Index | 59.1% | Not measured | Only Claude Sonnet 5.5 measured |
| τ²-Bench Telecom | Not measured | 99.1% | Only GLM 5.2 measured |
| APEX-Agents | 75.5% | 45.2% | Claude Sonnet 5.5 |
| PostTrainBench | Not measured | 31.7% | Only GLM 5.2 measured |
| SpireClimb | 1.3% | Not measured | Only Claude Sonnet 5.5 measured |
| Vending-Bench 2 | $11,165 | $8,314 | Claude Sonnet 5.5 |
| Neither model has a result on the other 12 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | Claude Sonnet 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 85.6% | Only GLM 5.2 measured |
| LiveBench reasoning | 91.6% | Not measured | Only Claude Sonnet 5.5 measured |
| MysteryMechanism (Vals AI) | 49.1% | Not measured | Only Claude Sonnet 5.5 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.5% | Only GLM 5.2 measured |
| Humanity's Last Exam (Artificial Analysis run) | 55.0% | 41.1% | Claude Sonnet 5.5 |
| GPQA Diamond (Epoch AI run) | 95.6% | 91.9% | Claude Sonnet 5.5 |
| ARC-AGI | Not measured | 77.0% | Only GLM 5.2 measured |
| ARC-AGI-2 | Not measured | 22.8% | Only GLM 5.2 measured |
| SimpleBench | Not measured | 58.8% | Only GLM 5.2 measured |
| Chess puzzles | 59.0% | 22.0% | Claude Sonnet 5.5 |
| Mystery game puzzles | 65.0% | 19.0% | Claude Sonnet 5.5 |
| EBR-bench | Not measured | 9.5% | Only GLM 5.2 measured |
| LMArena Text: hard prompts | 1494 | 1481 | Claude Sonnet 5.5 |
| LMArena Text: expert | 1531 | 1487 | Claude Sonnet 5.5 |
| LMArena Text: hard prompts in English | 1502 | 1481 | Claude Sonnet 5.5 |
| LMArena Vision: diagrams | 1329 | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena Vision: homework | 1331 | Not measured | Only Claude Sonnet 5.5 measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Claude Sonnet 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | 86.4% | Claude Sonnet 5.5 |
| FrontierMath, tiers 1 to 3 | 88.8% | 59.2% | Claude Sonnet 5.5 |
| FrontierMath, tier 4 | 80.5% | 29.3% | Claude Sonnet 5.5 |
| ProofBench | 100.0% | 35.0% | Claude Sonnet 5.5 |
| LMArena Text: math | 1497 | 1483 | Claude Sonnet 5.5 |
| LMArena Text: mathematical work | 1510 | 1489 | Claude Sonnet 5.5 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index33
| Benchmark | Claude Sonnet 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 86.7% | Only GLM 5.2 measured |
| LegalBench (Vals AI) | Not measured | 84.1% | Only GLM 5.2 measured |
| CorpFin (Vals AI) | Not measured | 66.1% | Only GLM 5.2 measured |
| TaxEval (Vals AI) | Not measured | 73.3% | Only GLM 5.2 measured |
| MedCode (Vals AI) | 52.9% | 40.8% | Claude Sonnet 5.5 |
| SimpleQA Verified | 46.5% | 34.2% | Claude Sonnet 5.5 |
| LMArena Text: science | 1483 | 1489 | GLM 5.2 |
| LMArena Text: medicine and healthcare | 1464 | 1475 | GLM 5.2 |
| LMArena Text: legal and government | 1483 | 1486 | GLM 5.2 |
| LMArena Text: business and finance | 1468 | 1451 | Claude Sonnet 5.5 |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Claude Sonnet 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| Design Arena: websites | 1326 | 1285 | Claude Sonnet 5.5 |
| Design Arena: UI components | 1367 | 1296 | Claude Sonnet 5.5 |
| Design Arena: game dev | 1469 | 1268 | Claude Sonnet 5.5 |
| Design Arena: data viz | 1389 | 1285 | Claude Sonnet 5.5 |
| Design Arena: 3D | 1458 | 1288 | Claude Sonnet 5.5 |
| Design Arena: all code categories | 1364 | 1288 | Claude Sonnet 5.5 |
| Design Arena: SVG | Not measured | 1214 | Only GLM 5.2 measured |
| Design Arena: ASCII art | Not measured | 1190 | Only GLM 5.2 measured |
| LiveBench design | 85.0% | Not measured | Only Claude Sonnet 5.5 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index134
| Benchmark | Claude Sonnet 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| Vals Index | 70.8% | Not measured | Only Claude Sonnet 5.5 measured |
| LiveBench data analysis | 59.5% | Not measured | Only Claude Sonnet 5.5 measured |
| Public Benefits Bench (Vals AI) | 67.2% | Not measured | Only Claude Sonnet 5.5 measured |
| SAGE (Vals AI) | 51.8% | Not measured | Only Claude Sonnet 5.5 measured |
| MedScribe (Vals AI) | 91.1% | 83.5% | Claude Sonnet 5.5 |
| IFBench | Not measured | 73.3% | Only GLM 5.2 measured |
| Long context reasoning (AA-LCR) | 82.7% | 78.3% | Claude Sonnet 5.5 |
| DTBench | 97.3% | 93.6% | Claude Sonnet 5.5 |
| LMCA | 68.3% | 45.8% | Claude Sonnet 5.5 |
| Surface Evolver Bench | Not measured | 55.6% | Only GLM 5.2 measured |
| Furniture assembly | 75.0% | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena Text | 1473 | 1470 | Claude Sonnet 5.5 |
| LMArena Text: instruction following | 1492 | 1466 | Claude Sonnet 5.5 |
| LMArena Text: creative writing | 1467 | 1463 | Claude Sonnet 5.5 |
| LMArena Vision | 1287 | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena Text: English | 1484 | 1475 | Claude Sonnet 5.5 |
| LMArena Text: non-English | 1456 | 1459 | GLM 5.2 |
| LMArena Text: Chinese | 1535 | 1522 | Claude Sonnet 5.5 |
| LMArena Text: German | Not measured | 1470 | Only GLM 5.2 measured |
| LMArena Text: Japanese | Not measured | 1450 | Only GLM 5.2 measured |
| LMArena Text: Korean | Not measured | 1440 | Only GLM 5.2 measured |
| LMArena Text: French | 1499 | 1479 | Claude Sonnet 5.5 |
| LMArena Text: Spanish | 1451 | 1478 | GLM 5.2 |
| LMArena Text: Russian | 1454 | 1468 | GLM 5.2 |
| LMArena Text: Polish | Not measured | 1456 | Only GLM 5.2 measured |
| LMArena Text: multi-turn | 1465 | 1469 | GLM 5.2 |
| LMArena Text: longer queries | 1495 | 1480 | Claude Sonnet 5.5 |
| LMArena Text: writing and language | 1474 | 1463 | Claude Sonnet 5.5 |
| LMArena Text: entertainment and media | 1461 | 1450 | Claude Sonnet 5.5 |
| LMArena Vision: English | 1289 | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena Vision: reading text | 1297 | Not measured | Only Claude Sonnet 5.5 measured |
| LMArena Vision: creative writing | 1242 | Not measured | Only Claude Sonnet 5.5 measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Sonnet 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
GLM 5.2 costs less
Repository review
50K input + 3K output tokens
GLM 5.2 costs less
Agent loop
200K input + 10K output tokens
GLM 5.2 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Anthropic Claude Sonnet 5.5 | Z.ai GLM 5.2 |
|---|---|---|
| Maker | Anthropic | Z.ai |
| Weights | No public weights listed | Open weights |
| Released | September 28, 2026 | June 16, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $2.00 | $0.0341 |
| Output $/Mtok | $10.00 | $7.00 |
| Coding index | 88.9 | 57.7 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | Not computable | $0.86 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Sonnet 5.5 better than GLM 5.2 for coding?
Pick Claude Sonnet 5.5 for coding: it scores 88.9 on the Vibe Coding Index against 57.7 for GLM 5.2. Pick GLM 5.2 when output tokens cost 1.4x less, or when the context window is larger, 1.05M against 1M tokens.
Which is cheaper, Claude Sonnet 5.5 or GLM 5.2?
Claude Sonnet 5.5 costs $2.00 per million input tokens and $10.00 per million output tokens; GLM 5.2 costs $0.0341 and $7.00. Cost per solved task is known for GLM 5.2 only.
Which has the bigger context window, Claude Sonnet 5.5 or GLM 5.2?
GLM 5.2, with 1.05M tokens against 1M.
How many benchmarks is the Claude Sonnet 5.5 vs GLM 5.2 comparison based on?
64 benchmarks have a result for both models as of October 21, 2026. Claude Sonnet 5.5's coding index rests on 2 independent benchmarks and GLM 5.2's on 1. Where only one model has a result, the page says so instead of naming a winner.