Claude Opus 4.1 vs GLM 5
Updated October 21, 2026. 52 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GLM 5 for coding: it scores 59.7 on the Vibe Coding Index against 27.2 for Claude Opus 4.1.
Pick Claude Opus 4.1 when what matters is LMArena Text: coding or SimpleBench, where it leads.
- Shared results
- 52
- Claude Opus 4.1 only
- 19
- GLM 5 only
- 23
- Like-for-like categories
- 7 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
GLM 5
GLM 5 scores 59.7 against 27.2.
1 and 2 benchmarks behind the scores
Intelligence
AA Intelligence Index
GLM 5
GLM 5 leads, 27.9 against 22.8.
Same board, both measured
Reasoning
GPQA Diamond
GLM 5
GLM 5 leads, 83.3% against 76.3%.
Same board, both measured
Math
AIME
GLM 5
GLM 5 leads, 91.7% against 78.2%.
Same board, both measured
Knowledge
MMLU Pro
Claude Opus 4.1
Claude Opus 4.1 leads, 87.9% against 86.0%.
Same board, both measured
Web design
Design Arena: websites
GLM 5
GLM 5 leads, 1247 against 1177.
Same board, both measured
Long documents
Listed context window
GLM 5
GLM 5 takes 205K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5
Claude Opus 4.1 $0.052, GLM 5 $0.0026 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GLM 5 has the number, $0.63.
Directional only
At a glance
- Coding index
- Claude Opus 4.1 27.2 from 1 benchmark, GLM 5 59.7 from 2 benchmarks.
- Widest category
- Math, 7.3 points apart on average over 4 shared benchmarks.
- Widest single gap
- LiveCodeBench (Vals AI): Claude Opus 4.1 66.5% against GLM 5 81.9%, 15.4 points apart on a 0 to 100 scale.
- Output price
- Claude Opus 4.1 $75.00 against GLM 5 $3.20 per million output tokens, 23.4x apart.
- Context window
- Claude Opus 4.1 takes 200K tokens, GLM 5 205K.
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 4.1 | Bars | GLM 5 | Ties |
|---|---|---|---|---|
| Coding | 1 | 6 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 1 | 5 | ||
| Math | 0 | 4 | ||
| Knowledge | 2 | 6 | ||
| Web design | 1 | 7 | ||
| General | 2 | 15 | ||
| All shared boards | 7 | 45 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index16
| Benchmark | Claude Opus 4.1 | GLM 5 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 72.8% | Only GLM 5 measured |
| SWE-bench Multilingual | Not measured | 69.7% | Only GLM 5 measured |
| LMArena WebDev | 1390 | 1435 | GLM 5 |
| LiveCodeBench (Vals AI) | 66.5% | 81.9% | GLM 5 |
| SWE-bench Verified (Vals AI) | Not measured | 71.4% | Only GLM 5 measured |
| Vibe Code Bench (Vals AI) | Not measured | 23.4% | Only GLM 5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 43.2% | Only GLM 5 measured |
| Terminal-Bench | 38.0% | 52.4% | GLM 5 |
| WeirdML | 45.9% | 48.2% | GLM 5 |
| Cybench | 42.0% | Not measured | Only Claude Opus 4.1 measured |
| ALE-Bench | Not measured | 765.6 | Only GLM 5 measured |
| LMArena Text: coding | 1479 | 1461 | Claude Opus 4.1 |
| LMArena Text: software and IT | 1456 | 1460 | GLM 5 |
| LMArena WebDev: React | Not measured | 1424 | Only GLM 5 measured |
| LMArena WebDev: HTML | 1399 | 1450 | GLM 5 |
| Neither model has a result on the other 23 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Claude Opus 4.1 | GLM 5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 22.8 | 27.9 | GLM 5 |
| Epoch Capabilities Index | 144.1 | 145.8 | GLM 5 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
| Benchmark | Claude Opus 4.1 | GLM 5 | Leader |
|---|---|---|---|
| Design Arena: agents building full-stack apps | Not measured | 1123 | Only GLM 5 measured |
| Design Arena: agents building mobile apps | Not measured | 1136 | Only GLM 5 measured |
| Design Arena: agents building Android apps | Not measured | 1152 | Only GLM 5 measured |
| Design Arena: agents building Godot games | Not measured | 1144 | Only GLM 5 measured |
| Design Arena: HTML slides | Not measured | 1148 | Only GLM 5 measured |
| τ²-Bench Telecom | Not measured | 98.2% | Only GLM 5 measured |
| METR time horizons | 66.8% | Not measured | Only Claude Opus 4.1 measured |
| GDPval | 43.6% | Not measured | Only Claude Opus 4.1 measured |
| DeepResearch Bench | 48.3% | Not measured | Only Claude Opus 4.1 measured |
| Vending-Bench 2 | Not measured | $4,432 | Only GLM 5 measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | Claude Opus 4.1 | GLM 5 | Leader |
|---|---|---|---|
| GPQA Diamond | 76.3% | 83.3% | GLM 5 |
| MMMU Pro (Vals AI) | 77.5% | Not measured | Only Claude Opus 4.1 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 82.0% | Only GLM 5 measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 29.3% | Only GLM 5 measured |
| GPQA Diamond (Epoch AI run) | 77.3% | 87.8% | GLM 5 |
| ARC-AGI | Not measured | 44.7% | Only GLM 5 measured |
| ARC-AGI-2 | Not measured | 4.9% | Only GLM 5 measured |
| SimpleBench | 60.0% | 53.2% | Claude Opus 4.1 |
| Mystery game puzzles | 21.0% | Not measured | Only Claude Opus 4.1 measured |
| EBR-bench | 7.9% | Not measured | Only Claude Opus 4.1 measured |
| VPCT | 35.0% | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: hard prompts | 1442 | 1452 | GLM 5 |
| LMArena Text: expert | 1438 | 1454 | GLM 5 |
| LMArena Text: hard prompts in English | 1451 | 1460 | GLM 5 |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | Claude Opus 4.1 | GLM 5 | Leader |
|---|---|---|---|
| AIME | 78.2% | 91.7% | GLM 5 |
| MATH 500 (Vals AI) | 95.4% | Not measured | Only Claude Opus 4.1 measured |
| MGSM (Vals AI) | 94.4% | Not measured | Only Claude Opus 4.1 measured |
| OTIS Mock AIME | 68.9% | 80.0% | GLM 5 |
| FrontierMath, tiers 1 to 3 | 12.6% | Not measured | Only Claude Opus 4.1 measured |
| FrontierMath, tier 4 | 2.4% | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: math | 1431 | 1440 | GLM 5 |
| LMArena Text: mathematical work | 1434 | 1451 | GLM 5 |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index26
| Benchmark | Claude Opus 4.1 | GLM 5 | Leader |
|---|---|---|---|
| MMLU Pro | 87.9% | 86.0% | Claude Opus 4.1 |
| LegalBench (Vals AI) | 83.5% | 84.1% | GLM 5 |
| CaseLaw (Vals AI) | Not measured | 52.5% | Only GLM 5 measured |
| CorpFin (Vals AI) | Not measured | 62.9% | Only GLM 5 measured |
| TaxEval (Vals AI) | 73.7% | 70.0% | Claude Opus 4.1 |
| MortgageTax (Vals AI) | 61.1% | Not measured | Only Claude Opus 4.1 measured |
| MedQA (Vals AI) | 93.6% | 94.3% | GLM 5 |
| MedCode (Vals AI) | 47.2% | Not measured | Only Claude Opus 4.1 measured |
| LMArena Text: science | 1422 | 1460 | GLM 5 |
| LMArena Text: medicine and healthcare | 1416 | 1455 | GLM 5 |
| LMArena Text: legal and government | 1421 | 1453 | GLM 5 |
| LMArena Text: business and finance | 1406 | 1430 | GLM 5 |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index17
| Benchmark | Claude Opus 4.1 | GLM 5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1177 | 1247 | GLM 5 |
| Design Arena: UI components | 1164 | 1230 | GLM 5 |
| Design Arena: game dev | 1172 | 1234 | GLM 5 |
| Design Arena: data viz | 1166 | 1228 | GLM 5 |
| Design Arena: 3D | 1153 | 1229 | GLM 5 |
| Design Arena: all code categories | 1171 | 1246 | GLM 5 |
| Design Arena: SVG | 1152 | 1168 | GLM 5 |
| Design Arena: ASCII art | 1167 | 1146 | Claude Opus 4.1 |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index215
| Benchmark | Claude Opus 4.1 | GLM 5 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 31.4% | Not measured | Only Claude Opus 4.1 measured |
| MedScribe (Vals AI) | 73.9% | Not measured | Only Claude Opus 4.1 measured |
| IFBench | Not measured | 72.3% | Only GLM 5 measured |
| Long context reasoning (AA-LCR) | Not measured | 75.7% | Only GLM 5 measured |
| DTBench | 80.0% | Not measured | Only Claude Opus 4.1 measured |
| LMCA | 37.1% | Not measured | Only Claude Opus 4.1 measured |
| Creative writing (Lech Mazur) | 84.7% | Not measured | Only Claude Opus 4.1 measured |
| CL-bench | Not measured | 18.7% | Only GLM 5 measured |
| LMArena Text | 1419 | 1446 | GLM 5 |
| LMArena Text: instruction following | 1435 | 1428 | Claude Opus 4.1 |
| LMArena Text: creative writing | 1412 | 1438 | GLM 5 |
| LMArena Text: English | 1433 | 1458 | GLM 5 |
| LMArena Text: non-English | 1405 | 1430 | GLM 5 |
| LMArena Text: Chinese | 1427 | 1511 | GLM 5 |
| LMArena Text: German | 1413 | 1447 | GLM 5 |
| LMArena Text: Japanese | 1377 | 1416 | GLM 5 |
| LMArena Text: Korean | 1381 | 1423 | GLM 5 |
| LMArena Text: French | 1433 | 1456 | GLM 5 |
| LMArena Text: Spanish | 1448 | 1454 | GLM 5 |
| LMArena Text: Russian | 1422 | 1436 | GLM 5 |
| LMArena Text: Polish | 1413 | 1434 | GLM 5 |
| LMArena Text: multi-turn | 1444 | 1456 | GLM 5 |
| LMArena Text: longer queries | 1455 | 1446 | Claude Opus 4.1 |
| LMArena Text: writing and language | 1418 | 1437 | GLM 5 |
| LMArena Text: entertainment and media | 1398 | 1426 | GLM 5 |
| Neither model has a result on the other 21 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Opus 4.1 | GLM 5 | 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 costs less
Repository review
50K input + 3K output tokens
GLM 5 costs less
Agent loop
200K input + 10K output tokens
GLM 5 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 4.1 | Z.ai GLM 5 |
|---|---|---|
| Maker | Anthropic | Z.ai |
| Weights | No public weights listed | Open weights |
| Released | August 5, 2025 | February 11, 2026 |
| Context window | 200K | 205K |
| Input $/Mtok | $15.00 | $1.00 |
| Output $/Mtok | $75.00 | $3.20 |
| Coding index | 27.2 | 59.7 |
| Independent measurements behind it | 1 | 2 |
| Cost per solved task | Not computable | $0.63 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Opus 4.1 better than GLM 5 for coding?
Pick GLM 5 for coding: it scores 59.7 on the Vibe Coding Index against 27.2 for Claude Opus 4.1. Pick Claude Opus 4.1 when what matters is LMArena Text: coding or SimpleBench, where it leads.
Which is cheaper, Claude Opus 4.1 or GLM 5?
Claude Opus 4.1 costs $15.00 per million input tokens and $75.00 per million output tokens; GLM 5 costs $1.00 and $3.20. Cost per solved task is known for GLM 5 only.
Which has the bigger context window, Claude Opus 4.1 or GLM 5?
GLM 5, with 205K tokens against 200K.
How many benchmarks is the Claude Opus 4.1 vs GLM 5 comparison based on?
52 benchmarks have a result for both models as of October 21, 2026. Claude Opus 4.1's coding index rests on 1 independent benchmark and GLM 5's on 2. Where only one model has a result, the page says so instead of naming a winner.