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Claude Opus 4.8 vs GLM 5

Claude Opus 4.8 leads GLM 5 on coding, 65.0 to 41.7 on the Vibe Coding Index, and GLM 5 costs 7.8x less per output token ($3.20 vs $25.00 per million). Updated October 22, 2026; 68 benchmarks have a result for both.

Claude Opus 4.8Anthropic
Coding
65.0
Overall
69.8
Output $/M
$25.00
63
GLM 5Z.ai
Coding
41.7
Overall
54.3
Output $/M
$3.20
5
vs boards won of 68 shared

Claude Opus 4.8 or GLM 5: which to pick

Pick Claude Opus 4.8 for coding: it scores 65.0 on the Vibe Coding Index against 41.7 for GLM 5.

Pick GLM 5 for output tokens 7.8x cheaper ($3.20 vs $25.00 per million) and a lower cost per solved task ($0.63 against $2.17).

Shared results
68
Claude Opus 4.8 only
62
GLM 5 only
8
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.

At a glance

Coding index
Claude Opus 4.8 65.0 from 6 benchmarks, GLM 5 41.7 from 3 benchmarks.
Widest category
Coding, 19.7 points apart on average over 10 shared benchmarks.
Widest single gap
ARC-AGI-2: Claude Opus 4.8 72.1% against GLM 5 4.9%, 67.2 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.8 $25.00 against GLM 5 $3.20 per million output tokens, 7.8x apart.
Context window
Claude Opus 4.8 takes 1M 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.

Boards won, where both have a result
CategoryClaude Opus 4.8BarsGLM 5Ties
Coding100
Intelligence20
Agentic work61
Reasoning110
Math30
Knowledge71
Web design71
General172
All shared boards635
CodingLike-for-likeSix of these boards feed the Vibe Coding Index100
Coding benchmarks for Claude Opus 4.8 and GLM 5
BenchmarkClaude Opus 4.8GLM 5Leader
SWE-bench VerifiedNot measured72.8%Only GLM 5 measured
SWE-bench MultilingualNot measured69.7%Only GLM 5 measured
LiveBench coding77.3%Not measuredOnly Claude Opus 4.8 measured
LMArena WebDev15561435Claude Opus 4.8
AA Coding Index74.3Not measuredOnly Claude Opus 4.8 measured
LiveCodeBench (Vals AI)87.8%81.9%Claude Opus 4.8
SWE-bench Verified (Vals AI)88.6%71.4%Claude Opus 4.8
Terminal-Bench 4 (Vals AI)23.2%Not measuredOnly Claude Opus 4.8 measured
Vibe Code Bench (Vals AI)82.7%23.4%Claude Opus 4.8
Code migration (Vals AI)47.3%Not measuredOnly Claude Opus 4.8 measured
ProgramBench (Vals AI)1.0%Not measuredOnly Claude Opus 4.8 measured
Terminal-Bench 2.1 (Vals AI)71.9%Not measuredOnly Claude Opus 4.8 measured
SkillsBench (Vals AI)59.2%Not measuredOnly Claude Opus 4.8 measured
SciCode54.4%Not measuredOnly Claude Opus 4.8 measured
Terminal-Bench Hard (Artificial Analysis run)58.3%43.2%Claude Opus 4.8
Terminal-BenchNot measured52.4%Only GLM 5 measured
FrontierCode46.5%Not measuredOnly Claude Opus 4.8 measured
GSO-Bench47.1%Not measuredOnly Claude Opus 4.8 measured
WeirdML82.9%48.2%Claude Opus 4.8
ALE-BenchNot measured765.6Only GLM 5 measured
LMArena Text: coding14901461Claude Opus 4.8
LMArena Text: software and IT14881460Claude Opus 4.8
LMArena WebDev: React15571424Claude Opus 4.8
LMArena WebDev: HTML15431450Claude Opus 4.8
SciCode12.3%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 14 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Claude Opus 4.8 and GLM 5
BenchmarkClaude Opus 4.8GLM 5Leader
AA Intelligence Index41.827.9Claude Opus 4.8
Epoch Capabilities Index159.0145.8Claude Opus 4.8
Agentic workLike-for-likePublic boards, shown as published, kept out of the index61
Agentic work benchmarks for Claude Opus 4.8 and GLM 5
BenchmarkClaude Opus 4.8GLM 5Leader
AA Agentic Index41.9Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building web apps1233Not measuredOnly Claude Opus 4.8 measured
Design Arena: agents building full-stack apps12491123Claude Opus 4.8
Design Arena: agents building mobile apps12221136Claude Opus 4.8
Design Arena: agents building Android apps12331147Claude Opus 4.8
Design Arena: agents building Godot games12311144Claude Opus 4.8
Design Arena: agents building games1239Not measuredOnly Claude Opus 4.8 measured
Design Arena: HTML slides11711098Claude Opus 4.8
Design Arena: PowerPoint slides1202Not measuredOnly Claude Opus 4.8 measured
Design Arena: spreadsheets1303Not measuredOnly Claude Opus 4.8 measured
LiveBench research81.8%Not measuredOnly Claude Opus 4.8 measured
LiveBench browser96.0%Not measuredOnly Claude Opus 4.8 measured
LiveBench long agentic48.3%Not measuredOnly Claude Opus 4.8 measured
Finance Agent (Vals AI)53.9%Not measuredOnly Claude Opus 4.8 measured
Tax Agent Bench (Vals AI)30.0%Not measuredOnly Claude Opus 4.8 measured
Legal Research Bench (Vals AI)43.8%Not measuredOnly Claude Opus 4.8 measured
Excel Modeling Benchmark (Vals AI)69.4%Not measuredOnly Claude Opus 4.8 measured
Terminal-Bench-Science (Vals AI)4.3%Not measuredOnly Claude Opus 4.8 measured
Time Horizon Index (Vals AI)11.8%Not measuredOnly Claude Opus 4.8 measured
τ²-Bench Telecom94.4%98.2%GLM 5
APEX-Agents48.9%Not measuredOnly Claude Opus 4.8 measured
Remote Labor Index8.3%Not measuredOnly Claude Opus 4.8 measured
OSWorld 2.020.6%Not measuredOnly Claude Opus 4.8 measured
DeepResearch Bench50.2%Not measuredOnly Claude Opus 4.8 measured
PostTrainBench33.8%Not measuredOnly Claude Opus 4.8 measured
Vending-Bench 2$5,787$4,432Claude Opus 4.8
LMArena Search1204Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 14 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index110
Reasoning benchmarks for Claude Opus 4.8 and GLM 5
BenchmarkClaude Opus 4.8GLM 5Leader
GPQA Diamond92.4%83.3%Claude Opus 4.8
LiveBench reasoning89.2%Not measuredOnly Claude Opus 4.8 measured
MMMU Pro (Vals AI)86.6%Not measuredOnly Claude Opus 4.8 measured
GPQA Diamond (Artificial Analysis run)92.0%82.0%Claude Opus 4.8
Humanity's Last Exam (Artificial Analysis run)48.7%29.3%Claude Opus 4.8
GPQA Diamond (Epoch AI run)91.0%87.8%Claude Opus 4.8
ARC-AGI92.5%44.7%Claude Opus 4.8
ARC-AGI-272.1%4.9%Claude Opus 4.8
SimpleBench64.8%53.2%Claude Opus 4.8
Chess puzzles52.0%Not measuredOnly Claude Opus 4.8 measured
Mystery game puzzles36.0%Not measuredOnly Claude Opus 4.8 measured
EBR-bench28.6%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: hard prompts14821452Claude Opus 4.8
LMArena Text: expert15031454Claude Opus 4.8
LMArena Text: hard prompts in English14871460Claude Opus 4.8
LMArena Vision: diagrams1315Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: homework1337Not measuredOnly Claude Opus 4.8 measured
Kagi LLM Benchmark88.8%75.0%Claude Opus 4.8
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for Claude Opus 4.8 and GLM 5
BenchmarkClaude Opus 4.8GLM 5Leader
AIMENot measured91.7%Only GLM 5 measured
OTIS Mock AIME98.3%80.0%Claude Opus 4.8
FrontierMath, tiers 1 to 380.0%Not measuredOnly Claude Opus 4.8 measured
FrontierMath, tier 456.1%Not measuredOnly Claude Opus 4.8 measured
ProofBench69.0%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: math14861440Claude Opus 4.8
LMArena Text: mathematical work14971451Claude Opus 4.8
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index71
Knowledge benchmarks for Claude Opus 4.8 and GLM 5
BenchmarkClaude Opus 4.8GLM 5Leader
MMLU Pro89.6%86.0%Claude Opus 4.8
LegalBench (Vals AI)83.6%84.1%GLM 5
CaseLaw (Vals AI)Not measured52.5%Only GLM 5 measured
CorpFin (Vals AI)66.7%62.9%Claude Opus 4.8
TaxEval (Vals AI)75.6%70.0%Claude Opus 4.8
MortgageTax (Vals AI)69.9%Not measuredOnly Claude Opus 4.8 measured
MedQA (Vals AI)Not measured94.3%Only GLM 5 measured
MedCode (Vals AI)53.2%Not measuredOnly Claude Opus 4.8 measured
SimpleQA Verified53.0%Not measuredOnly Claude Opus 4.8 measured
LMArena Text: science14771460Claude Opus 4.8
LMArena Text: medicine and healthcare14641455Claude Opus 4.8
LMArena Text: legal and government14771453Claude Opus 4.8
LMArena Text: business and finance14581430Claude Opus 4.8
FACTS Benchmark Suite53.5%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index71
Web design benchmarks for Claude Opus 4.8 and GLM 5
BenchmarkClaude Opus 4.8GLM 5Leader
Design Arena: websites12581247Claude Opus 4.8
Design Arena: UI components12551227Claude Opus 4.8
Design Arena: game dev12641234Claude Opus 4.8
Design Arena: data viz12401228Claude Opus 4.8
Design Arena: 3D12221228GLM 5
Design Arena: all code categories12551246Claude Opus 4.8
Design Arena: SVG11951168Claude Opus 4.8
Design Arena: ASCII art12771147Claude Opus 4.8
LiveBench design78.8%Not measuredOnly Claude Opus 4.8 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index172
General benchmarks for Claude Opus 4.8 and GLM 5
BenchmarkClaude Opus 4.8GLM 5Leader
LiveBench data analysis66.0%Not measuredOnly Claude Opus 4.8 measured
Public Benefits Bench (Vals AI)68.1%Not measuredOnly Claude Opus 4.8 measured
SAGE (Vals AI)54.8%Not measuredOnly Claude Opus 4.8 measured
MedScribe (Vals AI)85.8%Not measuredOnly Claude Opus 4.8 measured
Vals Multimodal Index70.9%Not measuredOnly Claude Opus 4.8 measured
IFBench62.2%72.3%GLM 5
Long context reasoning (AA-LCR)77.7%75.7%Claude Opus 4.8
DTBench94.9%Not measuredOnly Claude Opus 4.8 measured
LMCA57.5%Not measuredOnly Claude Opus 4.8 measured
CL-benchNot measured18.7%Only GLM 5 measured
Surface Evolver Bench87.5%Not measuredOnly Claude Opus 4.8 measured
Furniture assembly42.5%Not measuredOnly Claude Opus 4.8 measured
LMArena Text14611446Claude Opus 4.8
LMArena Text: instruction following14761428Claude Opus 4.8
LMArena Text: creative writing14541438Claude Opus 4.8
LMArena Vision1294Not measuredOnly Claude Opus 4.8 measured
LMArena Text: English14681458Claude Opus 4.8
LMArena Text: non-English14501430Claude Opus 4.8
LMArena Text: Chinese15061511GLM 5
LMArena Text: German14721447Claude Opus 4.8
LMArena Text: Japanese14421416Claude Opus 4.8
LMArena Text: Korean14311423Claude Opus 4.8
LMArena Text: French14811456Claude Opus 4.8
LMArena Text: Spanish14651454Claude Opus 4.8
LMArena Text: Russian14741436Claude Opus 4.8
LMArena Text: Polish14591434Claude Opus 4.8
LMArena Text: multi-turn14761456Claude Opus 4.8
LMArena Text: longer queries14831446Claude Opus 4.8
LMArena Text: writing and language14611437Claude Opus 4.8
LMArena Text: entertainment and media14401426Claude Opus 4.8
LMArena Vision: English1293Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: Chinese1346Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: reading text1303Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: humor1282Not measuredOnly Claude Opus 4.8 measured
LMArena Vision: creative writing1301Not measuredOnly Claude Opus 4.8 measured
LMArena Document1475Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 10 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 4.8 and GLM 5
BenchmarkClaude Opus 4.8GLM 5Leader
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

Claude Opus 4.8$0.018Fits in one request
GLM 5$0.0026Fits in one request

GLM 5 costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.8$0.325Fits in one request
GLM 5$0.060Fits in one request

GLM 5 costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.8$1.25Fits in one request
GLM 5$0.232Exceeds the context window

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.

Specifications of Claude Opus 4.8 and GLM 5
SpecificationAnthropic Claude Opus 4.8Z.ai GLM 5
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedMay 27, 2026February 11, 2026
Context window1M205K
Input $/Mtok$5.00$1.00
Output $/Mtok$25.00$3.20
Coding index65.041.7
Independent measurements behind it63
Cost per solved task$2.17$0.63
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.8 better than GLM 5 for coding?

Pick Claude Opus 4.8 for coding: it scores 65.0 on the Vibe Coding Index against 41.7 for GLM 5. Pick GLM 5 for output tokens 7.8x cheaper ($3.20 vs $25.00 per million) and a lower cost per solved task ($0.63 against $2.17).

Which is cheaper, Claude Opus 4.8 or GLM 5?

Claude Opus 4.8 costs $5.00 per million input tokens and $25.00 per million output tokens; GLM 5 costs $1.00 and $3.20. Per solved SWE-bench Verified task, Claude Opus 4.8 costs $2.17 and GLM 5 $0.63.

Which has the bigger context window, Claude Opus 4.8 or GLM 5?

Claude Opus 4.8, with 1M tokens against 205K.

How many benchmarks is the Claude Opus 4.8 vs GLM 5 comparison based on?

68 benchmarks have a result for both models as of October 22, 2026. Claude Opus 4.8's coding index rests on 6 independent benchmarks and GLM 5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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