Claude Opus 5.5 vs GLM 5.2
Claude Opus 5.5 leads GLM 5.2 on coding, 88.8 to 61.1 on the Vibe Coding Index, and GLM 5.2 costs 4.5x less per output token ($4.40 vs $20.00 per million). Updated October 22, 2026; 69 benchmarks have a result for both.
Claude Opus 5.5 or GLM 5.2: which to pick
Pick Claude Opus 5.5 for coding: it scores 88.8 on the Vibe Coding Index against 61.1 for GLM 5.2.
Pick GLM 5.2 for output tokens 4.5x cheaper ($4.40 vs $20.00 per million) and a larger context window (1.05M against 1M tokens).
- Shared results
- 69
- Claude Opus 5.5 only
- 40
- GLM 5.2 only
- 29
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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, six public coding benchmarks
Claude Opus 5.5
Claude Opus 5.5 scores 88.8 against 61.1.
5 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
Claude Opus 5.5
Claude Opus 5.5 leads, 57.6 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 Opus 5.5
Claude Opus 5.5 leads, 1335 against 1285.
Same board, both measured
General
Vals Index
No call
Only Claude Opus 5.5 has a Vals Index result, 70.2%.
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 Opus 5.5 $0.014, GLM 5.2 $0.0036 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 Opus 5.5 88.8 from 5 benchmarks, GLM 5.2 61.1 from 4 benchmarks.
- Widest category
- Math, 31.1 points apart on average over 6 shared benchmarks.
- Widest single gap
- ARC-AGI-2: Claude Opus 5.5 93.3% against GLM 5.2 22.8%, 70.6 points apart on a 0 to 100 scale.
- Output price
- Claude Opus 5.5 $20.00 against GLM 5.2 $4.40 per million output tokens, 4.5x apart.
- Context window
- Claude Opus 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 Opus 5.5 | Bars | GLM 5.2 | Ties |
|---|---|---|---|---|
| Coding | 12 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 8 | 0 | ||
| Reasoning | 9 | 1 | ||
| Math | 6 | 0 | ||
| Knowledge | 6 | 0 | ||
| Web design | 7 | 0 | ||
| General | 18 | 0 | ||
| All shared boards | 68 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index120
| Benchmark | Claude Opus 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| LiveBench coding | 96.3% | Not measured | Only Claude Opus 5.5 measured |
| LMArena WebDev | 1807 | 1604 | Claude Opus 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) | 65.2% | Not measured | Only Claude Opus 5.5 measured |
| Vibe Code Bench (Vals AI) | 90.3% | 64.0% | Claude Opus 5.5 |
| Code migration (Vals AI) | 66.7% | 37.9% | Claude Opus 5.5 |
| ProgramBench (Vals AI) | 18.5% | 0.5% | Claude Opus 5.5 |
| IOI (Vals AI) | 95.1% | Not measured | Only Claude Opus 5.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 87.6% | 67.8% | Claude Opus 5.5 |
| SWE-bench Multimodal (Vals AI) | 70.2% | Not measured | Only Claude Opus 5.5 measured |
| Vibe Code Bench 1-100 (Vals AI) | 30.4% | Not measured | Only Claude Opus 5.5 measured |
| SkillsBench (Vals AI) | Not measured | 45.1% | Only GLM 5.2 measured |
| CyberBench (Vals AI) | 74.6% | Not measured | Only Claude Opus 5.5 measured |
| SciCode | 66.9% | 51.2% | Claude Opus 5.5 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 50.8% | Only GLM 5.2 measured |
| FrontierCode | 54.6% | 24.5% | Claude Opus 5.5 |
| FrontierSWE | 62.3% | Not measured | Only Claude Opus 5.5 measured |
| WeirdML | Not measured | 70.1% | Only GLM 5.2 measured |
| MirrorCode | 77.4% | Not measured | Only Claude Opus 5.5 measured |
| ALE-Bench | 2147.4 | 1047.0 | Claude Opus 5.5 |
| LMArena Text: coding | 1545 | 1487 | Claude Opus 5.5 |
| LMArena Text: software and IT | 1538 | 1486 | Claude Opus 5.5 |
| LMArena WebDev: React | 1855 | 1617 | Claude Opus 5.5 |
| LMArena WebDev: HTML | 1753 | 1565 | Claude Opus 5.5 |
| LMArena WebDev: from an image | 1753 | Not measured | Only Claude Opus 5.5 measured |
| SciCode | 18.5% | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 11 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Claude Opus 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| AA Intelligence Index | 57.6 | 33.7 | Claude Opus 5.5 |
| Epoch Capabilities Index | 168.8 | 151.9 | Claude Opus 5.5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | Claude Opus 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 38.4 | Only GLM 5.2 measured |
| Design Arena: agents building web apps | 1316 | 1222 | Claude Opus 5.5 |
| Design Arena: agents building full-stack apps | Not measured | 1241 | Only GLM 5.2 measured |
| Design Arena: agents building mobile apps | 1308 | 1159 | Claude Opus 5.5 |
| Design Arena: agents building Android apps | Not measured | 1178 | 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 | 1125 | Only GLM 5.2 measured |
| Design Arena: PowerPoint slides | Not measured | 1170 | Only GLM 5.2 measured |
| Design Arena: spreadsheets | 1368 | Not measured | Only Claude Opus 5.5 measured |
| LiveBench research | 85.0% | Not measured | Only Claude Opus 5.5 measured |
| LiveBench browser | 80.0% | Not measured | Only Claude Opus 5.5 measured |
| LiveBench long agentic | 85.0% | Not measured | Only Claude Opus 5.5 measured |
| SREBench (Vals AI) | 33.6% | 0.0% | Claude Opus 5.5 |
| Finance Agent (Vals AI) | 58.6% | 49.7% | Claude Opus 5.5 |
| Tax Agent Bench (Vals AI) | 45.6% | Not measured | Only Claude Opus 5.5 measured |
| Legal Research Bench (Vals AI) | 50.5% | 31.3% | Claude Opus 5.5 |
| Harvey's Legal Agent Benchmark (Vals AI) | 9.2% | Not measured | Only Claude Opus 5.5 measured |
| Excel Modeling Benchmark (Vals AI) | 75.9% | 61.5% | Claude Opus 5.5 |
| BioMysteryBench (Vals AI) | 79.3% | Not measured | Only Claude Opus 5.5 measured |
| Terminal-Bench-Science (Vals AI) | 47.1% | Not measured | Only Claude Opus 5.5 measured |
| Vals Science Index | 58.7% | Not measured | Only Claude Opus 5.5 measured |
| Time Horizon Index (Vals AI) | 91.3% | Not measured | Only Claude Opus 5.5 measured |
| CUA-bench (Vals AI) | 14.0% | Not measured | Only Claude Opus 5.5 measured |
| Robo-bench (Vals AI) | 14.6% | Not measured | Only Claude Opus 5.5 measured |
| τ²-Bench Telecom | Not measured | 99.1% | Only GLM 5.2 measured |
| APEX-Agents | 73.5% | 45.2% | Claude Opus 5.5 |
| Remote Labor Index | 21.3% | Not measured | Only Claude Opus 5.5 measured |
| PostTrainBench | Not measured | 31.7% | Only GLM 5.2 measured |
| SpireClimb | 3.3% | Not measured | Only Claude Opus 5.5 measured |
| Vending-Bench 2 | $9,235 | $8,314 | Claude Opus 5.5 |
| LMArena Search | 1213 | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 9 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index91
| Benchmark | Claude Opus 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 85.6% | Only GLM 5.2 measured |
| LiveBench reasoning | 92.2% | Not measured | Only Claude Opus 5.5 measured |
| MysteryMechanism (Vals AI) | 49.5% | Not measured | Only Claude Opus 5.5 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.5% | Only GLM 5.2 measured |
| Humanity's Last Exam (Artificial Analysis run) | 61.4% | 41.1% | Claude Opus 5.5 |
| GPQA Diamond (Epoch AI run) | 90.6% | 91.9% | GLM 5.2 |
| ARC-AGI | 98.5% | 77.0% | Claude Opus 5.5 |
| ARC-AGI-2 | 93.3% | 22.8% | Claude Opus 5.5 |
| SimpleBench | Not measured | 58.8% | Only GLM 5.2 measured |
| Chess puzzles | 67.0% | 22.0% | Claude Opus 5.5 |
| Mystery game puzzles | 71.0% | 19.0% | Claude Opus 5.5 |
| EBR-bench | 71.4% | 9.5% | Claude Opus 5.5 |
| LMArena Text: hard prompts | 1536 | 1481 | Claude Opus 5.5 |
| LMArena Text: expert | 1549 | 1487 | Claude Opus 5.5 |
| LMArena Text: hard prompts in English | 1535 | 1481 | Claude Opus 5.5 |
| LMArena Vision: diagrams | 1345 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: homework | 1362 | Not measured | Only Claude Opus 5.5 measured |
| Kagi LLM Benchmark | Not measured | 62.6% | Only GLM 5.2 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 Opus 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | 86.4% | Claude Opus 5.5 |
| FrontierMath, tiers 1 to 3 | 91.2% | 59.2% | Claude Opus 5.5 |
| FrontierMath, tier 4 | 95.0% | 29.3% | Claude Opus 5.5 |
| ProofBench | 100.0% | 35.0% | Claude Opus 5.5 |
| LMArena Text: math | 1518 | 1483 | Claude Opus 5.5 |
| LMArena Text: mathematical work | 1516 | 1489 | Claude Opus 5.5 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Claude Opus 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) | 49.8% | 40.8% | Claude Opus 5.5 |
| SimpleQA Verified | 72.2% | 34.2% | Claude Opus 5.5 |
| LMArena Text: science | 1524 | 1489 | Claude Opus 5.5 |
| LMArena Text: medicine and healthcare | 1509 | 1475 | Claude Opus 5.5 |
| LMArena Text: legal and government | 1518 | 1486 | Claude Opus 5.5 |
| LMArena Text: business and finance | 1494 | 1451 | Claude Opus 5.5 |
| FACTS Benchmark Suite | 65.3% | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | Claude Opus 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| Design Arena: websites | 1335 | 1285 | Claude Opus 5.5 |
| Design Arena: UI components | 1385 | 1294 | Claude Opus 5.5 |
| Design Arena: game dev | 1461 | 1268 | Claude Opus 5.5 |
| Design Arena: data viz | 1397 | 1285 | Claude Opus 5.5 |
| Design Arena: 3D | 1476 | 1287 | Claude Opus 5.5 |
| Design Arena: all code categories | 1390 | 1287 | Claude Opus 5.5 |
| Design Arena: SVG | 1329 | 1213 | Claude Opus 5.5 |
| Design Arena: ASCII art | Not measured | 1191 | Only GLM 5.2 measured |
| LiveBench design | 86.9% | Not measured | Only Claude Opus 5.5 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
| Benchmark | Claude Opus 5.5 | GLM 5.2 | Leader |
|---|---|---|---|
| Vals Index | 70.2% | Not measured | Only Claude Opus 5.5 measured |
| LiveBench data analysis | 80.3% | Not measured | Only Claude Opus 5.5 measured |
| Public Benefits Bench (Vals AI) | 70.6% | Not measured | Only Claude Opus 5.5 measured |
| SAGE (Vals AI) | 45.8% | Not measured | Only Claude Opus 5.5 measured |
| MedScribe (Vals AI) | 91.4% | 83.5% | Claude Opus 5.5 |
| IFBench | Not measured | 73.3% | Only GLM 5.2 measured |
| Long context reasoning (AA-LCR) | 84.7% | 78.3% | Claude Opus 5.5 |
| DTBench | 98.9% | 93.6% | Claude Opus 5.5 |
| LMCA | 68.2% | 45.8% | Claude Opus 5.5 |
| Surface Evolver Bench | Not measured | 55.6% | Only GLM 5.2 measured |
| Furniture assembly | 83.3% | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text | 1516 | 1470 | Claude Opus 5.5 |
| LMArena Text: instruction following | 1537 | 1466 | Claude Opus 5.5 |
| LMArena Text: creative writing | 1535 | 1463 | Claude Opus 5.5 |
| LMArena Vision | 1321 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: English | 1519 | 1475 | Claude Opus 5.5 |
| LMArena Text: non-English | 1507 | 1459 | Claude Opus 5.5 |
| LMArena Text: Chinese | 1582 | 1522 | Claude Opus 5.5 |
| LMArena Text: German | Not measured | 1470 | Only GLM 5.2 measured |
| LMArena Text: Japanese | 1534 | 1450 | Claude Opus 5.5 |
| LMArena Text: Korean | Not measured | 1440 | Only GLM 5.2 measured |
| LMArena Text: French | 1493 | 1479 | Claude Opus 5.5 |
| LMArena Text: Spanish | 1508 | 1478 | Claude Opus 5.5 |
| LMArena Text: Russian | 1517 | 1468 | Claude Opus 5.5 |
| LMArena Text: Polish | Not measured | 1456 | Only GLM 5.2 measured |
| LMArena Text: multi-turn | 1501 | 1469 | Claude Opus 5.5 |
| LMArena Text: longer queries | 1532 | 1480 | Claude Opus 5.5 |
| LMArena Text: writing and language | 1532 | 1463 | Claude Opus 5.5 |
| LMArena Text: entertainment and media | 1515 | 1450 | Claude Opus 5.5 |
| LMArena Vision: English | 1317 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: reading text | 1326 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: creative writing | 1320 | Not measured | Only Claude Opus 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 Opus 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 Opus 5.5 | Z.ai GLM 5.2 |
|---|---|---|
| Maker | Anthropic | Z.ai |
| Weights | No public weights listed | Open weights |
| Released | September 22, 2026 | June 16, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $4.00 | $1.40 |
| Output $/Mtok | $20.00 | $4.40 |
| Coding index | 88.8 | 61.1 |
| Independent measurements behind it | 5 | 4 |
| Cost per solved task | Not computable | $0.86 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Opus 5.5 better than GLM 5.2 for coding?
Pick Claude Opus 5.5 for coding: it scores 88.8 on the Vibe Coding Index against 61.1 for GLM 5.2. Pick GLM 5.2 for output tokens 4.5x cheaper ($4.40 vs $20.00 per million) and a larger context window (1.05M against 1M tokens).
Which is cheaper, Claude Opus 5.5 or GLM 5.2?
Claude Opus 5.5 costs $4.00 per million input tokens and $20.00 per million output tokens; GLM 5.2 costs $1.40 and $4.40. Cost per solved task is known for GLM 5.2 only.
Which has the bigger context window, Claude Opus 5.5 or GLM 5.2?
GLM 5.2, with 1.05M tokens against 1M.
How many benchmarks is the Claude Opus 5.5 vs GLM 5.2 comparison based on?
69 benchmarks have a result for both models as of October 22, 2026. Claude Opus 5.5's coding index rests on 5 independent benchmarks and GLM 5.2's on 4. Where only one model has a result, the page says so instead of naming a winner.