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Granite 4.2 8B vs Qwen3.8 27B

Qwen3.8 27B leads Granite 4.2 8B on the Artificial Analysis Intelligence Index, 33.7 to 11.1, and Granite 4.2 8B costs 12.7x less per output token ($0.20 vs $2.55 per million). Updated October 23, 2026; 27 benchmarks have a result for both.

Replace Granite 4.2 8B Replace Qwen3.8 27B
Granite 4.2 8BIBM Granite
Coding
No data
Overall
No data
Output $/M
$0.20
0
Qwen3.8 27BQwen
Coding
74.1
Overall
59.5
Output $/M
$2.55
27
vs boards won of 27 shared

Granite 4.2 8B or Qwen3.8 27B: which to pick

Only Qwen3.8 27B has a coding score, 74.1 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 12.7x cheaper ($0.20 vs $2.55 per million).

Model AGranite 4.2 8BIBM GraniteNot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.8 27BQwen74.1/1004 independent benchmarks$1.26 per solved task
Shared results
27
Granite 4.2 8B only
0
Qwen3.8 27B only
58
Like-for-like categories
6 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
Granite 4.2 8B not benchmarked, Qwen3.8 27B 74.1 from 4 benchmarks.
Widest category
Agentic work, 44.5 points apart on average over 1 shared benchmark.
Widest single gap
AA Coding Index: Granite 4.2 8B 22.4 against Qwen3.8 27B 68.1, 45.7 points apart on a 0 to 100 scale.
Output price
Granite 4.2 8B $0.20 against Qwen3.8 27B $2.55 per million output tokens, 12.7x apart.
Context window
Granite 4.2 8B takes 131K tokens, Qwen3.8 27B 1M.

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
CategoryGranite 4.2 8BBarsQwen3.8 27BTies
Coding04
Intelligence01
Agentic work01
Reasoning05
Knowledge04
General012
All shared boards027
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for Granite 4.2 8B and Qwen3.8 27B
BenchmarkGranite 4.2 8BQwen3.8 27BLeader
LiveBench codingNot measured86.8%Only Qwen3.8 27B measured
LMArena WebDevNot measured1591Only Qwen3.8 27B measured
AA Coding Index22.468.1Qwen3.8 27B
LiveCodeBench (Vals AI)Not measured84.0%Only Qwen3.8 27B measured
SWE-bench Verified (Vals AI)Not measured86.0%Only Qwen3.8 27B measured
Vibe Code Bench (Vals AI)Not measured64.8%Only Qwen3.8 27B measured
Code migration (Vals AI)Not measured14.2%Only Qwen3.8 27B measured
ProgramBench (Vals AI)Not measured0.0%Only Qwen3.8 27B measured
IOI (Vals AI)Not measured39.1%Only Qwen3.8 27B measured
Terminal-Bench 2.1 (Vals AI)Not measured58.4%Only Qwen3.8 27B measured
SkillsBench (Vals AI)Not measured38.1%Only Qwen3.8 27B measured
CyberBench (Vals AI)Not measured67.8%Only Qwen3.8 27B measured
SciCode31.5%46.6%Qwen3.8 27B
LMArena Text: coding13781483Qwen3.8 27B
LMArena Text: software and IT13661477Qwen3.8 27B
LMArena WebDev: ReactNot measured1600Only Qwen3.8 27B measured
LMArena WebDev: HTMLNot measured1569Only Qwen3.8 27B measured
LMArena WebDev: from an imageNot measured1577Only Qwen3.8 27B measured
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Granite 4.2 8B and Qwen3.8 27B
BenchmarkGranite 4.2 8BQwen3.8 27BLeader
AA Intelligence Index11.133.7Qwen3.8 27B
Epoch Capabilities IndexNot measured151.7Only Qwen3.8 27B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Granite 4.2 8B and Qwen3.8 27B
BenchmarkGranite 4.2 8BQwen3.8 27BLeader
AA Agentic Index1.345.8Qwen3.8 27B
LiveBench researchNot measured59.4%Only Qwen3.8 27B measured
LiveBench browserNot measured32.0%Only Qwen3.8 27B measured
LiveBench long agenticNot measured27.9%Only Qwen3.8 27B measured
Finance Agent (Vals AI)Not measured48.5%Only Qwen3.8 27B measured
Tax Agent Bench (Vals AI)Not measured30.9%Only Qwen3.8 27B measured
Legal Research Bench (Vals AI)Not measured36.1%Only Qwen3.8 27B measured
Excel Modeling Benchmark (Vals AI)Not measured59.7%Only Qwen3.8 27B measured
Terminal-Bench-Science (Vals AI)Not measured0.0%Only Qwen3.8 27B measured
APEX-AgentsNot measured47.5%Only Qwen3.8 27B measured
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Granite 4.2 8B and Qwen3.8 27B
BenchmarkGranite 4.2 8BQwen3.8 27BLeader
GPQA DiamondNot measured88.9%Only Qwen3.8 27B measured
LiveBench reasoningNot measured80.0%Only Qwen3.8 27B measured
MMMU Pro (Vals AI)Not measured83.9%Only Qwen3.8 27B measured
GPQA Diamond (Artificial Analysis run)63.1%90.5%Qwen3.8 27B
Humanity's Last Exam (Artificial Analysis run)9.7%33.9%Qwen3.8 27B
ARC-AGINot measured87.5%Only Qwen3.8 27B measured
ARC-AGI-2Not measured42.4%Only Qwen3.8 27B measured
LMArena Text: hard prompts13271459Qwen3.8 27B
LMArena Text: expert13861480Qwen3.8 27B
LMArena Text: hard prompts in English13441462Qwen3.8 27B
LMArena Vision: diagramsNot measured1285Only Qwen3.8 27B measured
LMArena Vision: homeworkNot measured1295Only Qwen3.8 27B measured
Neither model has a result on the other 11 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Math benchmarks for Granite 4.2 8B and Qwen3.8 27B
BenchmarkGranite 4.2 8BQwen3.8 27BLeader
ProofBenchNot measured16.0%Only Qwen3.8 27B measured
LMArena Text: mathNot measured1455Only Qwen3.8 27B measured
LMArena Text: mathematical workNot measured1458Only Qwen3.8 27B measured
Neither model has a result on the other 11 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Granite 4.2 8B and Qwen3.8 27B
BenchmarkGranite 4.2 8BQwen3.8 27BLeader
MMLU ProNot measured84.3%Only Qwen3.8 27B measured
LegalBench (Vals AI)Not measured82.4%Only Qwen3.8 27B measured
TaxEval (Vals AI)Not measured70.8%Only Qwen3.8 27B measured
MortgageTax (Vals AI)Not measured64.9%Only Qwen3.8 27B measured
MedCode (Vals AI)Not measured28.7%Only Qwen3.8 27B measured
LMArena Text: science13351468Qwen3.8 27B
LMArena Text: medicine and healthcare13321438Qwen3.8 27B
LMArena Text: legal and government13271447Qwen3.8 27B
LMArena Text: business and finance13221438Qwen3.8 27B
Neither model has a result on the other 11 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Web design benchmarks for Granite 4.2 8B and Qwen3.8 27B
BenchmarkGranite 4.2 8BQwen3.8 27BLeader
LiveBench designNot measured75.9%Only Qwen3.8 27B measured
Neither model has a result on the other 8 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index012
General benchmarks for Granite 4.2 8B and Qwen3.8 27B
BenchmarkGranite 4.2 8BQwen3.8 27BLeader
LiveBench data analysisNot measured76.6%Only Qwen3.8 27B measured
SAGE (Vals AI)Not measured52.4%Only Qwen3.8 27B measured
MedScribe (Vals AI)Not measured83.8%Only Qwen3.8 27B measured
Long context reasoning (AA-LCR)45.0%82.0%Qwen3.8 27B
DTBenchNot measured88.0%Only Qwen3.8 27B measured
LMCANot measured41.4%Only Qwen3.8 27B measured
Surface Evolver BenchNot measured45.0%Only Qwen3.8 27B measured
LMArena Text13191440Qwen3.8 27B
LMArena Text: instruction following13011436Qwen3.8 27B
LMArena Text: creative writing12351383Qwen3.8 27B
LMArena VisionNot measured1269Only Qwen3.8 27B measured
LMArena Text: English13371448Qwen3.8 27B
LMArena Text: non-English13001428Qwen3.8 27B
LMArena Text: Chinese13651501Qwen3.8 27B
LMArena Text: GermanNot measured1442Only Qwen3.8 27B measured
LMArena Text: JapaneseNot measured1388Only Qwen3.8 27B measured
LMArena Text: KoreanNot measured1380Only Qwen3.8 27B measured
LMArena Text: FrenchNot measured1464Only Qwen3.8 27B measured
LMArena Text: SpanishNot measured1448Only Qwen3.8 27B measured
LMArena Text: Russian12801414Qwen3.8 27B
LMArena Text: PolishNot measured1447Only Qwen3.8 27B measured
LMArena Text: multi-turn13001440Qwen3.8 27B
LMArena Text: longer queries13241449Qwen3.8 27B
LMArena Text: writing and language12691405Qwen3.8 27B
LMArena Text: entertainment and media12711393Qwen3.8 27B
LMArena Vision: EnglishNot measured1267Only Qwen3.8 27B measured
LMArena Vision: ChineseNot measured1326Only Qwen3.8 27B measured
LMArena Vision: reading textNot measured1281Only Qwen3.8 27B measured
LMArena Vision: humorNot measured1235Only Qwen3.8 27B measured
LMArena Vision: creative writingNot measured1237Only Qwen3.8 27B 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 Granite 4.2 8B and Qwen3.8 27B
BenchmarkGranite 4.2 8BQwen3.8 27BLeader
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

Granite 4.2 8B$0.0002Fits in one request
Qwen3.8 27B$0.0017Fits in one request

Granite 4.2 8B costs less

Repository review

50K input + 3K output tokens

Granite 4.2 8B$0.0046Fits in one request
Qwen3.8 27B$0.029Fits in one request

Granite 4.2 8B costs less

Agent loop

200K input + 10K output tokens

Granite 4.2 8B$0.018Exceeds the context window
Qwen3.8 27B$0.111Fits in one request

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 Granite 4.2 8B and Qwen3.8 27B
SpecificationIBM Granite 4.2 8BQwen3.8 27B
MakerIBM GraniteQwen
WeightsOpen weightsOpen weights
ReleasedAugust 31, 2026August 14, 2026
Context window131K1M
Input $/Mtok$0.08$0.425
Output $/Mtok$0.20$2.55
Coding indexNot benchmarked74.1
Independent measurements behind it04
Cost per solved taskNot computable$1.26
SourceOpenRouter listingOpenRouter listing

Questions

Is Granite 4.2 8B better than Qwen3.8 27B for coding?

Only Qwen3.8 27B has a coding score, 74.1 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 12.7x cheaper ($0.20 vs $2.55 per million).

Which is cheaper, Granite 4.2 8B or Qwen3.8 27B?

Granite 4.2 8B costs $0.08 per million input tokens and $0.20 per million output tokens; Qwen3.8 27B costs $0.425 and $2.55. Cost per solved task is known for Qwen3.8 27B only.

Which has the bigger context window, Granite 4.2 8B or Qwen3.8 27B?

Qwen3.8 27B, with 1M tokens against 131K.

How many benchmarks is the Granite 4.2 8B vs Qwen3.8 27B comparison based on?

27 benchmarks have a result for both models as of October 23, 2026. Granite 4.2 8B's coding index rests on 0 independent benchmarks and Qwen3.8 27B's on 4. Where only one model has a result, the page says so instead of naming a winner.

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