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Claude Haiku 4.5 vs GLM 4.6

Claude Haiku 4.5 leads GLM 4.6 on coding, 35.6 to 8.8 on the Vibe Coding Index, and GLM 4.6 costs 2.3x less per output token ($2.20 vs $5.00 per million). Updated October 22, 2026; 52 benchmarks have a result for both.

Replace Claude Haiku 4.5 Replace GLM 4.6
Claude Haiku 4.5Anthropic
Coding
35.6
Overall
41.0
Output $/M
$5.00
10
GLM 4.6Z.ai
Coding
8.8
Overall
33.4
Output $/M
$2.20
42
vs boards won of 52 shared

Claude Haiku 4.5 or GLM 4.6: which to pick

Pick Claude Haiku 4.5 for coding: it scores 35.6 on the Vibe Coding Index against 8.8 for GLM 4.6.

Pick GLM 4.6 for output tokens 2.3x cheaper ($2.20 vs $5.00 per million) and a larger context window (205K against 200K tokens).

Model AClaude Haiku 4.5Anthropic35.6/1004 independent benchmarks$0.56 per solved taskModel BGLM 4.6Z.ai8.8/1002 independent benchmarksNo cost per solved task
Shared results
52
Claude Haiku 4.5 only
46
GLM 4.6 only
18
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 Haiku 4.5 35.6 from 4 benchmarks, GLM 4.6 8.8 from 2 benchmarks.
Widest category
Coding, 8.1 points apart on average over 9 shared benchmarks.
Widest single gap
LiveCodeBench (Vals AI): Claude Haiku 4.5 41.2% against GLM 4.6 81.0%, 39.9 points apart on a 0 to 100 scale.
Output price
Claude Haiku 4.5 $5.00 against GLM 4.6 $2.20 per million output tokens, 2.3x apart.
Context window
Claude Haiku 4.5 takes 200K tokens, GLM 4.6 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 Haiku 4.5BarsGLM 4.6Ties
Coding36
Intelligence01
Agentic work01
Reasoning13
Math13
Knowledge36
Web design07
General215
All shared boards1042
CodingLike-for-likeSix of these boards feed the Vibe Coding Index36
Coding benchmarks for Claude Haiku 4.5 and GLM 4.6
BenchmarkClaude Haiku 4.5GLM 4.6Leader
SWE-bench Verified66.6%68.2%GLM 4.6
SWE-bench Multilingual64.7%Not measuredOnly Claude Haiku 4.5 measured
LiveBench coding48.1%Not measuredOnly Claude Haiku 4.5 measured
LMArena WebDev13301341GLM 4.6
AA Coding Index43.945.8GLM 4.6
LiveCodeBench (Vals AI)41.2%81.0%GLM 4.6
SWE-bench Verified (Vals AI)66.6%Not measuredOnly Claude Haiku 4.5 measured
Vibe Code Bench (Vals AI)11.4%3.1%Claude Haiku 4.5
Code migration (Vals AI)7.5%Not measuredOnly Claude Haiku 4.5 measured
ProgramBench (Vals AI)0.0%Not measuredOnly Claude Haiku 4.5 measured
Terminal-Bench 2.1 (Vals AI)43.8%Not measuredOnly Claude Haiku 4.5 measured
LiveCodeBench (Artificial Analysis run)Not measured69.5%Only GLM 4.6 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured28.8%Only GLM 4.6 measured
Terminal-Bench35.5%24.5%Claude Haiku 4.5
WeirdML45.4%Not measuredOnly Claude Haiku 4.5 measured
ALE-BenchNot measured340.8Only GLM 4.6 measured
LMArena Text: coding14541449Claude Haiku 4.5
LMArena Text: software and IT14391455GLM 4.6
LMArena WebDev: React1326Not measuredOnly Claude Haiku 4.5 measured
LMArena WebDev: HTML13181350GLM 4.6
Neither model has a result on the other 23 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Claude Haiku 4.5 and GLM 4.6
BenchmarkClaude Haiku 4.5GLM 4.6Leader
AA Intelligence Index16.918.5GLM 4.6
Epoch Capabilities Index142.2Not measuredOnly Claude Haiku 4.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Claude Haiku 4.5 and GLM 4.6
BenchmarkClaude Haiku 4.5GLM 4.6Leader
AA Agentic Index8.0Not measuredOnly Claude Haiku 4.5 measured
Design Arena: agents building full-stack appsNot measured1029Only GLM 4.6 measured
Design Arena: agents building mobile appsNot measured1096Only GLM 4.6 measured
Design Arena: agents building Android appsNot measured1084Only GLM 4.6 measured
Design Arena: agents building Godot gamesNot measured1180Only GLM 4.6 measured
LiveBench research42.2%Not measuredOnly Claude Haiku 4.5 measured
LiveBench browser40.0%Not measuredOnly Claude Haiku 4.5 measured
LiveBench long agentic11.1%Not measuredOnly Claude Haiku 4.5 measured
Finance Agent (Vals AI)31.0%Not measuredOnly Claude Haiku 4.5 measured
Tax Agent Bench (Vals AI)5.9%Not measuredOnly Claude Haiku 4.5 measured
Legal Research Bench (Vals AI)10.6%Not measuredOnly Claude Haiku 4.5 measured
Excel Modeling Benchmark (Vals AI)22.7%Not measuredOnly Claude Haiku 4.5 measured
τ²-Bench TelecomNot measured76.9%Only GLM 4.6 measured
BALROG31.2%Not measuredOnly Claude Haiku 4.5 measured
DeepResearch Bench45.5%Not measuredOnly Claude Haiku 4.5 measured
Vending-Bench 2$459Not measuredOnly Claude Haiku 4.5 measured
Berkeley Function Calling Leaderboard (BFCL)68.7%72.4%GLM 4.6
BrowseComp-PlusNot measured48.2%Only GLM 4.6 measured
MCP Atlas40.2%Not measuredOnly Claude Haiku 4.5 measured
Neither model has a result on the other 23 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index13
Reasoning benchmarks for Claude Haiku 4.5 and GLM 4.6
BenchmarkClaude Haiku 4.5GLM 4.6Leader
GPQA Diamond72.2%74.5%GLM 4.6
LiveBench reasoning61.7%Not measuredOnly Claude Haiku 4.5 measured
MMMU Pro (Vals AI)46.1%Not measuredOnly Claude Haiku 4.5 measured
GPQA Diamond (Artificial Analysis run)Not measured78.0%Only GLM 4.6 measured
Humanity's Last Exam (Artificial Analysis run)Not measured14.5%Only GLM 4.6 measured
GPQA Diamond (Epoch AI run)71.2%Not measuredOnly Claude Haiku 4.5 measured
ARC-AGI47.7%Not measuredOnly Claude Haiku 4.5 measured
ARC-AGI-24.0%Not measuredOnly Claude Haiku 4.5 measured
Chess puzzles8.0%Not measuredOnly Claude Haiku 4.5 measured
LMArena Text: hard prompts14211440GLM 4.6
LMArena Text: expert14431432Claude Haiku 4.5
LMArena Text: hard prompts in English14351445GLM 4.6
Kagi LLM BenchmarkNot measured45.7%Only GLM 4.6 measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index13
Math benchmarks for Claude Haiku 4.5 and GLM 4.6
BenchmarkClaude Haiku 4.5GLM 4.6Leader
AIME82.7%92.7%GLM 4.6
MGSM (Vals AI)92.2%89.8%Claude Haiku 4.5
AA Math IndexNot measured86.0Only GLM 4.6 measured
AIME 2025 (Artificial Analysis run)Not measured86.0%Only GLM 4.6 measured
OTIS Mock AIME66.7%Not measuredOnly Claude Haiku 4.5 measured
MATH level 596.4%Not measuredOnly Claude Haiku 4.5 measured
LMArena Text: math13981432GLM 4.6
LMArena Text: mathematical work14301447GLM 4.6
MathArenaNot measured16.3%Only GLM 4.6 measured
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index36
Knowledge benchmarks for Claude Haiku 4.5 and GLM 4.6
BenchmarkClaude Haiku 4.5GLM 4.6Leader
MMLU Pro78.7%82.2%GLM 4.6
LegalBench (Vals AI)81.2%79.6%Claude Haiku 4.5
CaseLaw (Vals AI)56.5%Not measuredOnly Claude Haiku 4.5 measured
CorpFin (Vals AI)60.6%56.8%Claude Haiku 4.5
TaxEval (Vals AI)67.5%66.2%Claude Haiku 4.5
MortgageTax (Vals AI)62.2%Not measuredOnly Claude Haiku 4.5 measured
MedQA (Vals AI)79.6%92.2%GLM 4.6
MedCode (Vals AI)32.7%Not measuredOnly Claude Haiku 4.5 measured
MMLU Pro (Artificial Analysis run)Not measured82.9%Only GLM 4.6 measured
SimpleQA Verified13.2%Not measuredOnly Claude Haiku 4.5 measured
LMArena Text: science14061456GLM 4.6
LMArena Text: medicine and healthcare13941455GLM 4.6
LMArena Text: legal and government14001448GLM 4.6
LMArena Text: business and finance14001416GLM 4.6
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for Claude Haiku 4.5 and GLM 4.6
BenchmarkClaude Haiku 4.5GLM 4.6Leader
Design Arena: websites11221174GLM 4.6
Design Arena: UI components10971145GLM 4.6
Design Arena: game dev10961150GLM 4.6
Design Arena: data viz11241161GLM 4.6
Design Arena: 3D10711128GLM 4.6
Design Arena: all code categories11141165GLM 4.6
Design Arena: SVG10251108GLM 4.6
Design Arena: ASCII art1140Not measuredOnly Claude Haiku 4.5 measured
LiveBench design59.9%Not measuredOnly Claude Haiku 4.5 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index215
General benchmarks for Claude Haiku 4.5 and GLM 4.6
BenchmarkClaude Haiku 4.5GLM 4.6Leader
LiveBench data analysis59.3%Not measuredOnly Claude Haiku 4.5 measured
Public Benefits Bench (Vals AI)54.3%Not measuredOnly Claude Haiku 4.5 measured
SAGE (Vals AI)31.8%Not measuredOnly Claude Haiku 4.5 measured
MedScribe (Vals AI)85.2%Not measuredOnly Claude Haiku 4.5 measured
Vals Multimodal Index42.9%Not measuredOnly Claude Haiku 4.5 measured
IFBenchNot measured43.4%Only GLM 4.6 measured
Long context reasoning (AA-LCR)Not measured54.0%Only GLM 4.6 measured
DTBench73.6%Not measuredOnly Claude Haiku 4.5 measured
LMCA30.9%Not measuredOnly Claude Haiku 4.5 measured
ExploitBench13.7%Not measuredOnly Claude Haiku 4.5 measured
LMArena Text13971440GLM 4.6
LMArena Text: instruction following14141410Claude Haiku 4.5
LMArena Text: creative writing13711412GLM 4.6
LMArena Text: English14141449GLM 4.6
LMArena Text: non-English13771426GLM 4.6
LMArena Text: Chinese14181499GLM 4.6
LMArena Text: German13741447GLM 4.6
LMArena Text: Japanese13381393GLM 4.6
LMArena Text: Korean13461400GLM 4.6
LMArena Text: French14111459GLM 4.6
LMArena Text: Spanish14211436GLM 4.6
LMArena Text: Russian13811418GLM 4.6
LMArena Text: Polish13431447GLM 4.6
LMArena Text: multi-turn14091427GLM 4.6
LMArena Text: longer queries14271422Claude Haiku 4.5
LMArena Text: writing and language13861415GLM 4.6
LMArena Text: entertainment and media13691409GLM 4.6
LMArena Document1420Not measuredOnly Claude Haiku 4.5 measured
MultiChallenge50.5%Not measuredOnly Claude Haiku 4.5 measured
EQ-Bench 41064Not measuredOnly Claude Haiku 4.5 measured
Neither model has a result on the other 18 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Haiku 4.5 and GLM 4.6
BenchmarkClaude Haiku 4.5GLM 4.6Leader
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 Haiku 4.5$0.0035Fits in one request
GLM 4.6$0.0017Fits in one request

GLM 4.6 costs less

Repository review

50K input + 3K output tokens

Claude Haiku 4.5$0.065Fits in one request
GLM 4.6$0.037Fits in one request

GLM 4.6 costs less

Agent loop

200K input + 10K output tokens

Claude Haiku 4.5$0.250Exceeds the context window
GLM 4.6$0.142Exceeds the context window

GLM 4.6 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 Haiku 4.5 and GLM 4.6
SpecificationAnthropic Claude Haiku 4.5Z.ai GLM 4.6
MakerAnthropicZ.ai
WeightsNo public weights listedOpen weights
ReleasedOctober 15, 2025September 30, 2025
Context window200K205K
Input $/Mtok$1.00$0.60
Output $/Mtok$5.00$2.20
Coding index35.68.8
Independent measurements behind it42
Cost per solved task$0.56Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Haiku 4.5 better than GLM 4.6 for coding?

Pick Claude Haiku 4.5 for coding: it scores 35.6 on the Vibe Coding Index against 8.8 for GLM 4.6. Pick GLM 4.6 for output tokens 2.3x cheaper ($2.20 vs $5.00 per million) and a larger context window (205K against 200K tokens).

Which is cheaper, Claude Haiku 4.5 or GLM 4.6?

Claude Haiku 4.5 costs $1.00 per million input tokens and $5.00 per million output tokens; GLM 4.6 costs $0.60 and $2.20. Cost per solved task is known for Claude Haiku 4.5 only.

Which has the bigger context window, Claude Haiku 4.5 or GLM 4.6?

GLM 4.6, with 205K tokens against 200K.

How many benchmarks is the Claude Haiku 4.5 vs GLM 4.6 comparison based on?

52 benchmarks have a result for both models as of October 22, 2026. Claude Haiku 4.5's coding index rests on 4 independent benchmarks and GLM 4.6's on 2. Where only one model has a result, the page says so instead of naming a winner.

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