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Gemma 4 31B vs Granite 4.2 8B

Gemma 4 31B leads Granite 4.2 8B on the Artificial Analysis Intelligence Index, 14.7 to 11.1, and Granite 4.2 8B costs 2.0x less per output token ($0.20 vs $0.40 per million). Updated October 22, 2026; 27 benchmarks have a result for both.

Gemma 4 31BGoogle
Coding
39.0
Overall
42.1
Output $/M
$0.40
27
Granite 4.2 8BIBM Granite
Coding
No data
Overall
No data
Output $/M
$0.20
0
vs boards won of 27 shared

Gemma 4 31B or Granite 4.2 8B: which to pick

Only Gemma 4 31B has a coding score, 39.0 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 2.0x cheaper ($0.20 vs $0.40 per million).

Shared results
27
Gemma 4 31B only
45
Granite 4.2 8B only
0
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
Gemma 4 31B 39.0 from 2 benchmarks, Granite 4.2 8B not benchmarked.
Widest category
General, 23.4 points apart on average over 12 shared benchmarks.
Widest single gap
LMArena Text: creative writing: Gemma 4 31B 1417 against Granite 4.2 8B 1236, 30.1 points apart on a 0 to 100 scale.
Output price
Gemma 4 31B $0.40 against Granite 4.2 8B $0.20 per million output tokens, 2.0x apart.
Context window
Gemma 4 31B takes 262K 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
CategoryGemma 4 31BBarsGranite 4.2 8BTies
Coding40
Intelligence10
Agentic work10
Reasoning50
Knowledge40
General120
All shared boards270
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for Gemma 4 31B and Granite 4.2 8B
BenchmarkGemma 4 31BGranite 4.2 8BLeader
LiveBench coding49.0%Not measuredOnly Gemma 4 31B measured
LMArena WebDev1367Not measuredOnly Gemma 4 31B measured
AA Coding Index43.422.4Gemma 4 31B
SciCode45.5%31.5%Gemma 4 31B
Terminal-Bench Hard (Artificial Analysis run)36.4%Not measuredOnly Gemma 4 31B measured
WeirdML52.3%Not measuredOnly Gemma 4 31B measured
ALE-Bench925.5Not measuredOnly Gemma 4 31B measured
LMArena Text: coding14591378Gemma 4 31B
LMArena Text: software and IT14631367Gemma 4 31B
LMArena WebDev: React1359Not measuredOnly Gemma 4 31B measured
LMArena WebDev: HTML1380Not measuredOnly Gemma 4 31B measured
SciCode8.9%Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 31 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Gemma 4 31B and Granite 4.2 8B
BenchmarkGemma 4 31BGranite 4.2 8BLeader
AA Intelligence Index14.711.1Gemma 4 31B
Epoch Capabilities Index143.0Not measuredOnly Gemma 4 31B measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Gemma 4 31B and Granite 4.2 8B
BenchmarkGemma 4 31BGranite 4.2 8BLeader
AA Agentic Index4.21.3Gemma 4 31B
LiveBench research44.4%Not measuredOnly Gemma 4 31B measured
LiveBench browser4.0%Not measuredOnly Gemma 4 31B measured
LiveBench long agentic13.3%Not measuredOnly Gemma 4 31B measured
τ²-Bench Telecom65.5%Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for Gemma 4 31B and Granite 4.2 8B
BenchmarkGemma 4 31BGranite 4.2 8BLeader
LiveBench reasoning68.3%Not measuredOnly Gemma 4 31B measured
GPQA Diamond (Artificial Analysis run)85.7%63.1%Gemma 4 31B
Humanity's Last Exam (Artificial Analysis run)23.6%9.7%Gemma 4 31B
GPQA Diamond (Epoch AI run)75.8%Not measuredOnly Gemma 4 31B measured
LMArena Text: hard prompts14481327Gemma 4 31B
LMArena Text: expert14641386Gemma 4 31B
LMArena Text: hard prompts in English14561345Gemma 4 31B
LMArena Vision: diagrams1283Not measuredOnly Gemma 4 31B measured
LMArena Vision: homework1310Not measuredOnly Gemma 4 31B measured
Kagi LLM Benchmark63.5%Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 13 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Math benchmarks for Gemma 4 31B and Granite 4.2 8B
BenchmarkGemma 4 31BGranite 4.2 8BLeader
OTIS Mock AIME73.3%Not measuredOnly Gemma 4 31B measured
LMArena Text: math1463Not measuredOnly Gemma 4 31B measured
LMArena Text: mathematical work1465Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 11 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Gemma 4 31B and Granite 4.2 8B
BenchmarkGemma 4 31BGranite 4.2 8BLeader
CaseLaw (Vals AI)52.6%Not measuredOnly Gemma 4 31B measured
MortgageTax (Vals AI)61.4%Not measuredOnly Gemma 4 31B measured
SimpleQA Verified10.4%Not measuredOnly Gemma 4 31B measured
LMArena Text: science14571336Gemma 4 31B
LMArena Text: medicine and healthcare14511336Gemma 4 31B
LMArena Text: legal and government14381327Gemma 4 31B
LMArena Text: business and finance14301322Gemma 4 31B
FACTS Benchmark Suite45.3%Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 12 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Web design benchmarks for Gemma 4 31B and Granite 4.2 8B
BenchmarkGemma 4 31BGranite 4.2 8BLeader
LiveBench design58.4%Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 8 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index120
General benchmarks for Gemma 4 31B and Granite 4.2 8B
BenchmarkGemma 4 31BGranite 4.2 8BLeader
LiveBench data analysis53.3%Not measuredOnly Gemma 4 31B measured
SAGE (Vals AI)55.0%Not measuredOnly Gemma 4 31B measured
IFBench75.6%Not measuredOnly Gemma 4 31B measured
Long context reasoning (AA-LCR)69.7%45.0%Gemma 4 31B
DTBench82.7%Not measuredOnly Gemma 4 31B measured
LMCA39.3%Not measuredOnly Gemma 4 31B measured
Surface Evolver Bench30.6%Not measuredOnly Gemma 4 31B measured
LMArena Text14431319Gemma 4 31B
LMArena Text: instruction following14331300Gemma 4 31B
LMArena Text: creative writing14171236Gemma 4 31B
LMArena Vision1276Not measuredOnly Gemma 4 31B measured
LMArena Text: English14511337Gemma 4 31B
LMArena Text: non-English14301301Gemma 4 31B
LMArena Text: Chinese14751367Gemma 4 31B
LMArena Text: French1436Not measuredOnly Gemma 4 31B measured
LMArena Text: Spanish1442Not measuredOnly Gemma 4 31B measured
LMArena Text: Russian14601282Gemma 4 31B
LMArena Text: Polish1433Not measuredOnly Gemma 4 31B measured
LMArena Text: multi-turn14521301Gemma 4 31B
LMArena Text: longer queries14461325Gemma 4 31B
LMArena Text: writing and language14321269Gemma 4 31B
LMArena Text: entertainment and media14051271Gemma 4 31B
LMArena Vision: English1271Not measuredOnly Gemma 4 31B measured
LMArena Vision: Chinese1326Not measuredOnly Gemma 4 31B measured
LMArena Vision: reading text1282Not measuredOnly Gemma 4 31B measured
LMArena Vision: humor1280Not measuredOnly Gemma 4 31B measured
LMArena Vision: captioning1218Not measuredOnly Gemma 4 31B measured
LMArena Vision: recognizing things1226Not measuredOnly Gemma 4 31B measured
LMArena Vision: creative writing1285Not measuredOnly Gemma 4 31B measured
LMArena Document1425Not measuredOnly Gemma 4 31B measured
EQ-Bench 41120Not measuredOnly Gemma 4 31B measured
Neither model has a result on the other 17 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemma 4 31B and Granite 4.2 8B
BenchmarkGemma 4 31BGranite 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

Gemma 4 31B$0.0003Fits 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

Gemma 4 31B$0.0082Fits 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

Gemma 4 31B$0.032Fits 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 Gemma 4 31B and Granite 4.2 8B
SpecificationGoogle Gemma 4 31BIBM Granite 4.2 8B
MakerGoogleIBM Granite
WeightsOpen weightsOpen weights
ReleasedApril 2, 2026August 31, 2026
Context window262K131K
Input $/Mtok$0.14$0.08
Output $/Mtok$0.40$0.20
Coding index39.0Not benchmarked
Independent measurements behind it20
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 4 31B better than Granite 4.2 8B for coding?

Only Gemma 4 31B has a coding score, 39.0 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 2.0x cheaper ($0.20 vs $0.40 per million).

Which is cheaper, Gemma 4 31B or Granite 4.2 8B?

Gemma 4 31B costs $0.14 per million input tokens and $0.40 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, Gemma 4 31B or Granite 4.2 8B?

Gemma 4 31B, with 262K tokens against 131K.

How many benchmarks is the Gemma 4 31B vs Granite 4.2 8B comparison based on?

27 benchmarks have a result for both models as of October 22, 2026. Gemma 4 31B's coding index rests on 2 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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