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Claude Opus 4.8 vs GLM 5.2

Claude Opus 4.8 leads GLM 5.2 on coding, 65.0 to 61.1 on the Vibe Coding Index, and GLM 5.2 costs 5.7x less per output token ($4.40 vs $25.00 per million). Updated October 22, 2026; 96 benchmarks have a result for both.

Replace Claude Opus 4.8 Replace GLM 5.2
Claude Opus 4.8Anthropic
Coding
65.0
Overall
69.8
Output $/M
$25.00
67
GLM 5.2Z.ai
Coding
61.1
Overall
62.5
Output $/M
$4.40
29
vs boards won of 96 shared

Claude Opus 4.8 or GLM 5.2: which to pick

Pick Claude Opus 4.8 for coding: it scores 65.0 on the Vibe Coding Index against 61.1 for GLM 5.2.

Pick GLM 5.2 for output tokens 5.7x cheaper ($4.40 vs $25.00 per million) and a lower cost per solved task ($0.86 against $2.17).

Model AClaude Opus 4.8Anthropic65.0/1006 independent benchmarks$2.17 per solved taskModel BGLM 5.2Z.ai61.1/1004 independent benchmarks$0.86 per solved task
Shared results
96
Claude Opus 4.8 only
34
GLM 5.2 only
2
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 5.2 61.1 from 4 benchmarks.
Widest category
Math, 15.9 points apart on average over 6 shared benchmarks.
Widest single gap
ARC-AGI-2: Claude Opus 4.8 72.1% against GLM 5.2 22.8%, 49.3 points apart on a 0 to 100 scale.
Output price
Claude Opus 4.8 $25.00 against GLM 5.2 $4.40 per million output tokens, 5.7x apart.
Context window
Claude Opus 4.8 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.

Boards won, where both have a result
CategoryClaude Opus 4.8BarsGLM 5.2Ties
Coding143
Intelligence20
Agentic work142
Reasoning131
Math60
Knowledge64
Web design17
General1112
All shared boards6729
CodingLike-for-likeSix of these boards feed the Vibe Coding Index143
Coding benchmarks for Claude Opus 4.8 and GLM 5.2
BenchmarkClaude Opus 4.8GLM 5.2Leader
LiveBench coding77.3%Not measuredOnly Claude Opus 4.8 measured
LMArena WebDev15561604GLM 5.2
AA Coding Index74.368.8Claude Opus 4.8
LiveCodeBench (Vals AI)87.8%69.5%Claude Opus 4.8
SWE-bench Verified (Vals AI)88.6%82.8%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%64.0%Claude Opus 4.8
Code migration (Vals AI)47.3%37.9%Claude Opus 4.8
ProgramBench (Vals AI)1.0%0.5%Claude Opus 4.8
Terminal-Bench 2.1 (Vals AI)71.9%67.8%Claude Opus 4.8
SkillsBench (Vals AI)59.2%45.1%Claude Opus 4.8
SciCode54.4%51.2%Claude Opus 4.8
Terminal-Bench Hard (Artificial Analysis run)58.3%50.8%Claude Opus 4.8
FrontierCode46.5%24.5%Claude Opus 4.8
GSO-Bench47.1%Not measuredOnly Claude Opus 4.8 measured
WeirdML82.9%70.1%Claude Opus 4.8
ALE-BenchNot measured1047.0Only GLM 5.2 measured
LMArena Text: coding14901487Claude Opus 4.8
LMArena Text: software and IT14881486Claude Opus 4.8
LMArena WebDev: React15571617GLM 5.2
LMArena WebDev: HTML15431565GLM 5.2
SciCode12.3%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 17 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Claude Opus 4.8 and GLM 5.2
BenchmarkClaude Opus 4.8GLM 5.2Leader
AA Intelligence Index41.833.7Claude Opus 4.8
Epoch Capabilities Index159.0151.9Claude Opus 4.8
Agentic workLike-for-likePublic boards, shown as published, kept out of the index142
Agentic work benchmarks for Claude Opus 4.8 and GLM 5.2
BenchmarkClaude Opus 4.8GLM 5.2Leader
AA Agentic Index41.938.4Claude Opus 4.8
Design Arena: agents building web apps12331222Claude Opus 4.8
Design Arena: agents building full-stack apps12491241Claude Opus 4.8
Design Arena: agents building mobile apps12221159Claude Opus 4.8
Design Arena: agents building Android apps12331178Claude Opus 4.8
Design Arena: agents building Godot games12311142Claude Opus 4.8
Design Arena: agents building games12391206Claude Opus 4.8
Design Arena: HTML slides11711125Claude Opus 4.8
Design Arena: PowerPoint slides12021170Claude Opus 4.8
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
SREBench (Vals AI)Not measured0.0%Only GLM 5.2 measured
Finance Agent (Vals AI)53.9%49.7%Claude Opus 4.8
Tax Agent Bench (Vals AI)30.0%Not measuredOnly Claude Opus 4.8 measured
Legal Research Bench (Vals AI)43.8%31.3%Claude Opus 4.8
Excel Modeling Benchmark (Vals AI)69.4%61.5%Claude Opus 4.8
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%99.1%GLM 5.2
APEX-Agents48.9%45.2%Claude Opus 4.8
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%31.7%Claude Opus 4.8
Vending-Bench 2$5,787$8,314GLM 5.2
LMArena Search1204Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 13 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index131
Reasoning benchmarks for Claude Opus 4.8 and GLM 5.2
BenchmarkClaude Opus 4.8GLM 5.2Leader
GPQA Diamond92.4%85.6%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%89.5%Claude Opus 4.8
Humanity's Last Exam (Artificial Analysis run)48.7%41.1%Claude Opus 4.8
GPQA Diamond (Epoch AI run)91.0%91.9%GLM 5.2
ARC-AGI92.5%77.0%Claude Opus 4.8
ARC-AGI-272.1%22.8%Claude Opus 4.8
SimpleBench64.8%58.8%Claude Opus 4.8
Chess puzzles52.0%22.0%Claude Opus 4.8
Mystery game puzzles36.0%19.0%Claude Opus 4.8
EBR-bench28.6%9.5%Claude Opus 4.8
LMArena Text: hard prompts14821481Claude Opus 4.8
LMArena Text: expert15031487Claude Opus 4.8
LMArena Text: hard prompts in English14871481Claude 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%62.6%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 index60
Math benchmarks for Claude Opus 4.8 and GLM 5.2
BenchmarkClaude Opus 4.8GLM 5.2Leader
OTIS Mock AIME98.3%86.4%Claude Opus 4.8
FrontierMath, tiers 1 to 380.0%59.2%Claude Opus 4.8
FrontierMath, tier 456.1%29.3%Claude Opus 4.8
ProofBench69.0%35.0%Claude Opus 4.8
LMArena Text: math14861483Claude Opus 4.8
LMArena Text: mathematical work14971489Claude Opus 4.8
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index64
Knowledge benchmarks for Claude Opus 4.8 and GLM 5.2
BenchmarkClaude Opus 4.8GLM 5.2Leader
MMLU Pro89.6%86.7%Claude Opus 4.8
LegalBench (Vals AI)83.6%84.1%GLM 5.2
CorpFin (Vals AI)66.7%66.1%Claude Opus 4.8
TaxEval (Vals AI)75.6%73.3%Claude Opus 4.8
MortgageTax (Vals AI)69.9%Not measuredOnly Claude Opus 4.8 measured
MedCode (Vals AI)53.2%40.8%Claude Opus 4.8
SimpleQA Verified53.0%34.2%Claude Opus 4.8
LMArena Text: science14771489GLM 5.2
LMArena Text: medicine and healthcare14641475GLM 5.2
LMArena Text: legal and government14771486GLM 5.2
LMArena Text: business and finance14581451Claude Opus 4.8
FACTS Benchmark Suite53.5%Not measuredOnly Claude Opus 4.8 measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index17
Web design benchmarks for Claude Opus 4.8 and GLM 5.2
BenchmarkClaude Opus 4.8GLM 5.2Leader
Design Arena: websites12581285GLM 5.2
Design Arena: UI components12551294GLM 5.2
Design Arena: game dev12641268GLM 5.2
Design Arena: data viz12401285GLM 5.2
Design Arena: 3D12221287GLM 5.2
Design Arena: all code categories12551287GLM 5.2
Design Arena: SVG11951213GLM 5.2
Design Arena: ASCII art12771191Claude Opus 4.8
LiveBench design78.8%Not measuredOnly Claude Opus 4.8 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index1112
General benchmarks for Claude Opus 4.8 and GLM 5.2
BenchmarkClaude Opus 4.8GLM 5.2Leader
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%83.5%Claude Opus 4.8
Vals Multimodal Index70.9%Not measuredOnly Claude Opus 4.8 measured
IFBench62.2%73.3%GLM 5.2
Long context reasoning (AA-LCR)77.7%78.3%GLM 5.2
DTBench94.9%93.6%Claude Opus 4.8
LMCA57.5%45.8%Claude Opus 4.8
Surface Evolver Bench87.5%55.6%Claude Opus 4.8
Furniture assembly42.5%Not measuredOnly Claude Opus 4.8 measured
LMArena Text14611470GLM 5.2
LMArena Text: instruction following14761466Claude Opus 4.8
LMArena Text: creative writing14541463GLM 5.2
LMArena Vision1294Not measuredOnly Claude Opus 4.8 measured
LMArena Text: English14681475GLM 5.2
LMArena Text: non-English14501459GLM 5.2
LMArena Text: Chinese15061522GLM 5.2
LMArena Text: German14721470Claude Opus 4.8
LMArena Text: Japanese14421450GLM 5.2
LMArena Text: Korean14311440GLM 5.2
LMArena Text: French14811479Claude Opus 4.8
LMArena Text: Spanish14651478GLM 5.2
LMArena Text: Russian14741468Claude Opus 4.8
LMArena Text: Polish14591456Claude Opus 4.8
LMArena Text: multi-turn14761469Claude Opus 4.8
LMArena Text: longer queries14831480Claude Opus 4.8
LMArena Text: writing and language14611463GLM 5.2
LMArena Text: entertainment and media14401450GLM 5.2
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 11 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 5.2
BenchmarkClaude Opus 4.8GLM 5.2Leader
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 5.2$0.0036Fits in one request

GLM 5.2 costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.8$0.325Fits in one request
GLM 5.2$0.083Fits in one request

GLM 5.2 costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.8$1.25Fits in one request
GLM 5.2$0.324Fits in one request

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.

Specifications of Claude Opus 4.8 and GLM 5.2
SpecificationAnthropic Claude Opus 4.8Z.ai GLM 5.2
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedMay 27, 2026June 16, 2026
Context window1M1.05M
Input $/Mtok$5.00$1.40
Output $/Mtok$25.00$4.40
Coding index65.061.1
Independent measurements behind it64
Cost per solved task$2.17$0.86
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 4.8 better than GLM 5.2 for coding?

Pick Claude Opus 4.8 for coding: it scores 65.0 on the Vibe Coding Index against 61.1 for GLM 5.2. Pick GLM 5.2 for output tokens 5.7x cheaper ($4.40 vs $25.00 per million) and a lower cost per solved task ($0.86 against $2.17).

Which is cheaper, Claude Opus 4.8 or GLM 5.2?

Claude Opus 4.8 costs $5.00 per million input tokens and $25.00 per million output tokens; GLM 5.2 costs $1.40 and $4.40. Per solved SWE-bench Verified task, Claude Opus 4.8 costs $2.17 and GLM 5.2 $0.86.

Which has the bigger context window, Claude Opus 4.8 or GLM 5.2?

GLM 5.2, with 1.05M tokens against 1M.

How many benchmarks is the Claude Opus 4.8 vs GLM 5.2 comparison based on?

96 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 5.2's on 4. Where only one model has a result, the page says so instead of naming a winner.

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