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GLM 5 vs Granite 4.2 8B

GLM 5 leads Granite 4.2 8B on the Artificial Analysis Intelligence Index, 27.9 to 11.1, and Granite 4.2 8B costs 16.0x less per output token ($0.20 vs $3.20 per million). Updated October 22, 2026; 24 benchmarks have a result for both.

Replace GLM 5 Replace Granite 4.2 8B
GLM 5Z.ai
Coding
41.7
Overall
54.3
Output $/M
$3.20
24
Granite 4.2 8BIBM Granite
Coding
No data
Overall
No data
Output $/M
$0.20
0
vs boards won of 24 shared

GLM 5 or Granite 4.2 8B: which to pick

Only GLM 5 has a coding score, 41.7 on the Vibe Coding Index; Granite 4.2 8B has none, so the two cannot be ranked on coding.

Pick Granite 4.2 8B for output tokens 16.0x cheaper ($0.20 vs $3.20 per million).

Model AGLM 5Z.ai41.7/1003 independent benchmarks$0.63 per solved taskModel BGranite 4.2 8BIBM GraniteNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
24
GLM 5 only
52
Granite 4.2 8B only
3
Like-for-like categories
5 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
GLM 5 41.7 from 3 benchmarks, Granite 4.2 8B not benchmarked.
Widest category
General, 24.8 points apart on average over 12 shared benchmarks.
Widest single gap
LMArena Text: creative writing: GLM 5 1438 against Granite 4.2 8B 1236, 33.7 points apart on a 0 to 100 scale.
Output price
GLM 5 $3.20 against Granite 4.2 8B $0.20 per million output tokens, 16.0x apart.
Context window
GLM 5 takes 205K tokens, Granite 4.2 8B 131K.

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
CategoryGLM 5BarsGranite 4.2 8BTies
Coding20
Intelligence10
Reasoning50
Knowledge40
General120
All shared boards240
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for GLM 5 and Granite 4.2 8B
BenchmarkGLM 5Granite 4.2 8BLeader
SWE-bench Verified72.8%Not measuredOnly GLM 5 measured
SWE-bench Multilingual69.7%Not measuredOnly GLM 5 measured
LMArena WebDev1435Not measuredOnly GLM 5 measured
AA Coding IndexNot measured22.4Only Granite 4.2 8B measured
LiveCodeBench (Vals AI)81.9%Not measuredOnly GLM 5 measured
SWE-bench Verified (Vals AI)71.4%Not measuredOnly GLM 5 measured
Vibe Code Bench (Vals AI)23.4%Not measuredOnly GLM 5 measured
SciCodeNot measured31.5%Only Granite 4.2 8B measured
Terminal-Bench Hard (Artificial Analysis run)43.2%Not measuredOnly GLM 5 measured
Terminal-Bench52.4%Not measuredOnly GLM 5 measured
WeirdML48.2%Not measuredOnly GLM 5 measured
ALE-Bench765.6Not measuredOnly GLM 5 measured
LMArena Text: coding14611378GLM 5
LMArena Text: software and IT14601367GLM 5
LMArena WebDev: React1424Not measuredOnly GLM 5 measured
LMArena WebDev: HTML1450Not measuredOnly GLM 5 measured
Neither model has a result on the other 23 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 5 and Granite 4.2 8B
BenchmarkGLM 5Granite 4.2 8BLeader
AA Intelligence Index27.911.1GLM 5
Epoch Capabilities Index145.8Not measuredOnly GLM 5 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Agentic work benchmarks for GLM 5 and Granite 4.2 8B
BenchmarkGLM 5Granite 4.2 8BLeader
AA Agentic IndexNot measured1.3Only Granite 4.2 8B measured
Design Arena: agents building full-stack apps1123Not measuredOnly GLM 5 measured
Design Arena: agents building mobile apps1136Not measuredOnly GLM 5 measured
Design Arena: agents building Android apps1147Not measuredOnly GLM 5 measured
Design Arena: agents building Godot games1144Not measuredOnly GLM 5 measured
Design Arena: HTML slides1098Not measuredOnly GLM 5 measured
τ²-Bench Telecom98.2%Not measuredOnly GLM 5 measured
Vending-Bench 2$4,432Not measuredOnly GLM 5 measured
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for GLM 5 and Granite 4.2 8B
BenchmarkGLM 5Granite 4.2 8BLeader
GPQA Diamond83.3%Not measuredOnly GLM 5 measured
GPQA Diamond (Artificial Analysis run)82.0%63.1%GLM 5
Humanity's Last Exam (Artificial Analysis run)29.3%9.7%GLM 5
GPQA Diamond (Epoch AI run)87.8%Not measuredOnly GLM 5 measured
ARC-AGI44.7%Not measuredOnly GLM 5 measured
ARC-AGI-24.9%Not measuredOnly GLM 5 measured
SimpleBench53.2%Not measuredOnly GLM 5 measured
LMArena Text: hard prompts14521327GLM 5
LMArena Text: expert14541386GLM 5
LMArena Text: hard prompts in English14601345GLM 5
Kagi LLM Benchmark75.0%Not measuredOnly GLM 5 measured
Neither model has a result on the other 11 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for GLM 5 and Granite 4.2 8B
BenchmarkGLM 5Granite 4.2 8BLeader
AIME91.7%Not measuredOnly GLM 5 measured
OTIS Mock AIME80.0%Not measuredOnly GLM 5 measured
LMArena Text: math1440Not measuredOnly GLM 5 measured
LMArena Text: mathematical work1451Not measuredOnly GLM 5 measured
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for GLM 5 and Granite 4.2 8B
BenchmarkGLM 5Granite 4.2 8BLeader
MMLU Pro86.0%Not measuredOnly GLM 5 measured
LegalBench (Vals AI)84.1%Not measuredOnly GLM 5 measured
CaseLaw (Vals AI)52.5%Not measuredOnly GLM 5 measured
CorpFin (Vals AI)62.9%Not measuredOnly GLM 5 measured
TaxEval (Vals AI)70.0%Not measuredOnly GLM 5 measured
MedQA (Vals AI)94.3%Not measuredOnly GLM 5 measured
LMArena Text: science14601336GLM 5
LMArena Text: medicine and healthcare14551336GLM 5
LMArena Text: legal and government14531327GLM 5
LMArena Text: business and finance14301322GLM 5
Neither model has a result on the other 8 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GLM 5 and Granite 4.2 8B
BenchmarkGLM 5Granite 4.2 8BLeader
Design Arena: websites1247Not measuredOnly GLM 5 measured
Design Arena: UI components1227Not measuredOnly GLM 5 measured
Design Arena: game dev1234Not measuredOnly GLM 5 measured
Design Arena: data viz1228Not measuredOnly GLM 5 measured
Design Arena: 3D1228Not measuredOnly GLM 5 measured
Design Arena: all code categories1246Not measuredOnly GLM 5 measured
Design Arena: SVG1168Not measuredOnly GLM 5 measured
Design Arena: ASCII art1147Not measuredOnly GLM 5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index120
General benchmarks for GLM 5 and Granite 4.2 8B
BenchmarkGLM 5Granite 4.2 8BLeader
IFBench72.3%Not measuredOnly GLM 5 measured
Long context reasoning (AA-LCR)75.7%45.0%GLM 5
CL-bench18.7%Not measuredOnly GLM 5 measured
LMArena Text14461319GLM 5
LMArena Text: instruction following14281300GLM 5
LMArena Text: creative writing14381236GLM 5
LMArena Text: English14581337GLM 5
LMArena Text: non-English14301301GLM 5
LMArena Text: Chinese15111367GLM 5
LMArena Text: German1447Not measuredOnly GLM 5 measured
LMArena Text: Japanese1416Not measuredOnly GLM 5 measured
LMArena Text: Korean1423Not measuredOnly GLM 5 measured
LMArena Text: French1456Not measuredOnly GLM 5 measured
LMArena Text: Spanish1454Not measuredOnly GLM 5 measured
LMArena Text: Russian14361282GLM 5
LMArena Text: Polish1434Not measuredOnly GLM 5 measured
LMArena Text: multi-turn14561301GLM 5
LMArena Text: longer queries14461325GLM 5
LMArena Text: writing and language14371269GLM 5
LMArena Text: entertainment and media14261271GLM 5
Neither model has a result on the other 26 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 5 and Granite 4.2 8B
BenchmarkGLM 5Granite 4.2 8BLeader
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$0.0026Fits in one request
Granite 4.2 8B$0.0002Fits in one request

Granite 4.2 8B costs less

Repository review

50K input + 3K output tokens

GLM 5$0.060Fits in one request
Granite 4.2 8B$0.0046Fits in one request

Granite 4.2 8B costs less

Agent loop

200K input + 10K output tokens

GLM 5$0.232Exceeds the context window
Granite 4.2 8B$0.018Exceeds the context window

Granite 4.2 8B 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 GLM 5 and Granite 4.2 8B
SpecificationZ.ai GLM 5IBM Granite 4.2 8B
MakerZ.aiIBM Granite
WeightsOpen weightsOpen weights
ReleasedFebruary 11, 2026August 31, 2026
Context window205K131K
Input $/Mtok$1.00$0.08
Output $/Mtok$3.20$0.20
Coding index41.7Not benchmarked
Independent measurements behind it30
Cost per solved task$0.63Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5 better than Granite 4.2 8B for coding?

Only GLM 5 has a coding score, 41.7 on the Vibe Coding Index; Granite 4.2 8B has none, so the two cannot be ranked on coding. Pick Granite 4.2 8B for output tokens 16.0x cheaper ($0.20 vs $3.20 per million).

Which is cheaper, GLM 5 or Granite 4.2 8B?

GLM 5 costs $1.00 per million input tokens and $3.20 per million output tokens; Granite 4.2 8B costs $0.08 and $0.20. Cost per solved task is known for GLM 5 only.

Which has the bigger context window, GLM 5 or Granite 4.2 8B?

GLM 5, with 205K tokens against 131K.

How many benchmarks is the GLM 5 vs Granite 4.2 8B comparison based on?

24 benchmarks have a result for both models as of October 22, 2026. GLM 5's coding index rests on 3 independent benchmarks and Granite 4.2 8B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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