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Grok Build 0.1 vs Granite 4.2 8B

Grok Build 0.1 leads Granite 4.2 8B on the Artificial Analysis Intelligence Index, 27.2 to 11.1, and Granite 4.2 8B costs 10.0x less per output token ($0.20 vs $2.00 per million). Updated October 22, 2026; 2 benchmarks have a result for both.

Grok Build 0.1xAI
Coding
No data
Overall
No data
Output $/M
$2.00
2
Granite 4.2 8BIBM Granite
Coding
No data
Overall
No data
Output $/M
$0.20
0
vs boards won of 2 shared

Grok Build 0.1 or Granite 4.2 8B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Grok Build 0.1 for a larger context window (256K against 131K tokens).

Shared results
2
Grok Build 0.1 only
1
Granite 4.2 8B only
25
Like-for-like categories
2 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
Grok Build 0.1 not benchmarked, Granite 4.2 8B not benchmarked.
Widest category
Coding, 29.1 points apart on average over 1 shared benchmark.
Widest single gap
AA Coding Index: Grok Build 0.1 51.5 against Granite 4.2 8B 22.4, 29.1 points apart on a 0 to 100 scale.
Output price
Grok Build 0.1 $2.00 against Granite 4.2 8B $0.20 per million output tokens, 10.0x apart.
Context window
Grok Build 0.1 takes 256K 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
CategoryGrok Build 0.1BarsGranite 4.2 8BTies
Coding10
Intelligence10
All shared boards20
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
Coding benchmarks for Grok Build 0.1 and Granite 4.2 8B
BenchmarkGrok Build 0.1Granite 4.2 8BLeader
AA Coding Index51.522.4Grok Build 0.1
Vibe Code Bench (Vals AI)13.4%Not measuredOnly Grok Build 0.1 measured
SciCodeNot measured31.5%Only Granite 4.2 8B measured
LMArena Text: codingNot measured1378Only Granite 4.2 8B measured
LMArena Text: software and ITNot measured1367Only Granite 4.2 8B measured
Neither model has a result on the other 38 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Grok Build 0.1 and Granite 4.2 8B
BenchmarkGrok Build 0.1Granite 4.2 8BLeader
AA Intelligence Index27.211.1Grok Build 0.1
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Agentic work benchmarks for Grok Build 0.1 and Granite 4.2 8B
BenchmarkGrok Build 0.1Granite 4.2 8BLeader
AA Agentic IndexNot measured1.3Only Granite 4.2 8B measured
Neither model has a result on the other 41 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Reasoning benchmarks for Grok Build 0.1 and Granite 4.2 8B
BenchmarkGrok Build 0.1Granite 4.2 8BLeader
GPQA Diamond (Artificial Analysis run)Not measured63.1%Only Granite 4.2 8B measured
Humanity's Last Exam (Artificial Analysis run)Not measured9.7%Only Granite 4.2 8B measured
LMArena Text: hard promptsNot measured1327Only Granite 4.2 8B measured
LMArena Text: expertNot measured1386Only Granite 4.2 8B measured
LMArena Text: hard prompts in EnglishNot measured1345Only Granite 4.2 8B measured
Neither model has a result on the other 18 boards here
MathNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Math benchmarks for Grok Build 0.1 and Granite 4.2 8B
BenchmarkGrok Build 0.1Granite 4.2 8BLeader
Neither model has a result on 14 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Knowledge benchmarks for Grok Build 0.1 and Granite 4.2 8B
BenchmarkGrok Build 0.1Granite 4.2 8BLeader
LMArena Text: scienceNot measured1336Only Granite 4.2 8B measured
LMArena Text: medicine and healthcareNot measured1336Only Granite 4.2 8B measured
LMArena Text: legal and governmentNot measured1327Only Granite 4.2 8B measured
LMArena Text: business and financeNot measured1322Only Granite 4.2 8B measured
Neither model has a result on the other 16 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Grok Build 0.1 and Granite 4.2 8B
BenchmarkGrok Build 0.1Granite 4.2 8BLeader
Neither model has a result on 9 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
General benchmarks for Grok Build 0.1 and Granite 4.2 8B
BenchmarkGrok Build 0.1Granite 4.2 8BLeader
Long context reasoning (AA-LCR)Not measured45.0%Only Granite 4.2 8B measured
LMArena TextNot measured1319Only Granite 4.2 8B measured
LMArena Text: instruction followingNot measured1300Only Granite 4.2 8B measured
LMArena Text: creative writingNot measured1236Only Granite 4.2 8B measured
LMArena Text: EnglishNot measured1337Only Granite 4.2 8B measured
LMArena Text: non-EnglishNot measured1301Only Granite 4.2 8B measured
LMArena Text: ChineseNot measured1367Only Granite 4.2 8B measured
LMArena Text: RussianNot measured1282Only Granite 4.2 8B measured
LMArena Text: multi-turnNot measured1301Only Granite 4.2 8B measured
LMArena Text: longer queriesNot measured1325Only Granite 4.2 8B measured
LMArena Text: writing and languageNot measured1269Only Granite 4.2 8B measured
LMArena Text: entertainment and mediaNot measured1271Only Granite 4.2 8B measured
Neither model has a result on the other 36 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Grok Build 0.1 and Granite 4.2 8B
BenchmarkGrok Build 0.1Granite 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

Grok Build 0.1$0.0020Fits 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

Grok Build 0.1$0.056Fits 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

Grok Build 0.1$0.220Fits in one request
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 Grok Build 0.1 and Granite 4.2 8B
SpecificationSpaceXAI Grok Build 0.1IBM Granite 4.2 8B
MakerxAIIBM Granite
WeightsNo public weights listedOpen weights
ReleasedMay 20, 2026August 31, 2026
Context window256K131K
Input $/Mtok$1.00$0.08
Output $/Mtok$2.00$0.20
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Grok Build 0.1 better than Granite 4.2 8B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Grok Build 0.1 for a larger context window (256K against 131K tokens).

Which is cheaper, Grok Build 0.1 or Granite 4.2 8B?

Grok Build 0.1 costs $1.00 per million input tokens and $2.00 per million output tokens; Granite 4.2 8B costs $0.08 and $0.20. Cost per solved task is known for neither of them.

Which has the bigger context window, Grok Build 0.1 or Granite 4.2 8B?

Grok Build 0.1, with 256K tokens against 131K.

How many benchmarks is the Grok Build 0.1 vs Granite 4.2 8B comparison based on?

2 benchmarks have a result for both models as of October 22, 2026. Grok Build 0.1's coding index rests on 1 independent benchmark 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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