Enter opens the highlighted result. Esc closes.

Granite 4.2 8B vs Qwen3.5-Flash

Granite 4.2 8B costs 1.3x less per output token than Qwen3.5-Flash ($0.20 vs $0.26 per million). Updated October 22, 2026; 20 benchmarks have a result for both.

Replace Granite 4.2 8B Replace Qwen3.5-Flash
Granite 4.2 8BIBM Granite
Coding
No data
Overall
No data
Output $/M
$0.20
0
Qwen3.5-FlashQwen
Coding
41.1
Overall
50.1
Output $/M
$0.26
20
vs boards won of 20 shared

Granite 4.2 8B or Qwen3.5-Flash: which to pick

Only Qwen3.5-Flash has a coding score, 41.1 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 1.3x cheaper ($0.20 vs $0.26 per million).

Model AGranite 4.2 8BIBM GraniteNot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.5-FlashQwen41.1/1002 independent benchmarks$0.40 per solved task
Shared results
20
Granite 4.2 8B only
7
Qwen3.5-Flash only
35
Like-for-like categories
4 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, Qwen3.5-Flash 41.1 from 2 benchmarks.
Widest category
General, 13.9 points apart on average over 11 shared benchmarks.
Widest single gap
LMArena Text: creative writing: Granite 4.2 8B 1236 against Qwen3.5-Flash 1343, 17.9 points apart on a 0 to 100 scale.
Output price
Granite 4.2 8B $0.20 against Qwen3.5-Flash $0.26 per million output tokens, 1.3x apart.
Context window
Granite 4.2 8B takes 131K tokens, Qwen3.5-Flash 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 8BBarsQwen3.5-FlashTies
Coding02
Reasoning03
Knowledge04
General011
All shared boards020
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Granite 4.2 8B and Qwen3.5-Flash
BenchmarkGranite 4.2 8BQwen3.5-FlashLeader
LMArena WebDevNot measured1244Only Qwen3.5-Flash measured
AA Coding Index22.4Not measuredOnly Granite 4.2 8B measured
LiveCodeBench (Vals AI)Not measured83.3%Only Qwen3.5-Flash measured
SWE-bench Verified (Vals AI)Not measured64.4%Only Qwen3.5-Flash measured
SciCode31.5%Not measuredOnly Granite 4.2 8B measured
ALE-BenchNot measured265.9Only Qwen3.5-Flash measured
LMArena Text: coding13781412Qwen3.5-Flash
LMArena Text: software and IT13671416Qwen3.5-Flash
LMArena WebDev: ReactNot measured1229Only Qwen3.5-Flash measured
LMArena WebDev: HTMLNot measured1291Only Qwen3.5-Flash measured
Neither model has a result on the other 33 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Granite 4.2 8B and Qwen3.5-Flash
BenchmarkGranite 4.2 8BQwen3.5-FlashLeader
AA Intelligence Index11.1Not measuredOnly Granite 4.2 8B measured
Epoch Capabilities IndexNot measured143.5Only Qwen3.5-Flash measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Agentic work benchmarks for Granite 4.2 8B and Qwen3.5-Flash
BenchmarkGranite 4.2 8BQwen3.5-FlashLeader
AA Agentic Index1.3Not measuredOnly Granite 4.2 8B measured
Neither model has a result on the other 41 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for Granite 4.2 8B and Qwen3.5-Flash
BenchmarkGranite 4.2 8BQwen3.5-FlashLeader
GPQA DiamondNot measured82.8%Only Qwen3.5-Flash measured
MMMU Pro (Vals AI)Not measured81.9%Only Qwen3.5-Flash measured
GPQA Diamond (Artificial Analysis run)63.1%Not measuredOnly Granite 4.2 8B measured
Humanity's Last Exam (Artificial Analysis run)9.7%Not measuredOnly Granite 4.2 8B measured
GPQA Diamond (Epoch AI run)Not measured82.3%Only Qwen3.5-Flash measured
Chess puzzlesNot measured14.0%Only Qwen3.5-Flash measured
Mystery game puzzlesNot measured20.0%Only Qwen3.5-Flash measured
LMArena Text: hard prompts13271403Qwen3.5-Flash
LMArena Text: expert13861407Qwen3.5-Flash
LMArena Text: hard prompts in English13451409Qwen3.5-Flash
Neither model has a result on the other 13 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for Granite 4.2 8B and Qwen3.5-Flash
BenchmarkGranite 4.2 8BQwen3.5-FlashLeader
AIMENot measured92.5%Only Qwen3.5-Flash measured
OTIS Mock AIMENot measured84.4%Only Qwen3.5-Flash measured
FrontierMath, tiers 1 to 3Not measured18.2%Only Qwen3.5-Flash measured
LMArena Text: mathNot measured1407Only Qwen3.5-Flash measured
LMArena Text: mathematical workNot measured1413Only Qwen3.5-Flash measured
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Granite 4.2 8B and Qwen3.5-Flash
BenchmarkGranite 4.2 8BQwen3.5-FlashLeader
MMLU ProNot measured84.1%Only Qwen3.5-Flash measured
LegalBench (Vals AI)Not measured84.3%Only Qwen3.5-Flash measured
CaseLaw (Vals AI)Not measured56.0%Only Qwen3.5-Flash measured
CorpFin (Vals AI)Not measured63.6%Only Qwen3.5-Flash measured
TaxEval (Vals AI)Not measured72.2%Only Qwen3.5-Flash measured
MortgageTax (Vals AI)Not measured67.4%Only Qwen3.5-Flash measured
MedCode (Vals AI)Not measured33.0%Only Qwen3.5-Flash measured
SimpleQA VerifiedNot measured20.3%Only Qwen3.5-Flash measured
LMArena Text: science13361415Qwen3.5-Flash
LMArena Text: medicine and healthcare13361407Qwen3.5-Flash
LMArena Text: legal and government13271398Qwen3.5-Flash
LMArena Text: business and finance13221394Qwen3.5-Flash
Neither model has a result on the other 8 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Granite 4.2 8B and Qwen3.5-Flash
BenchmarkGranite 4.2 8BQwen3.5-FlashLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index011
General benchmarks for Granite 4.2 8B and Qwen3.5-Flash
BenchmarkGranite 4.2 8BQwen3.5-FlashLeader
SAGE (Vals AI)Not measured42.5%Only Qwen3.5-Flash measured
MedScribe (Vals AI)Not measured70.6%Only Qwen3.5-Flash measured
Long context reasoning (AA-LCR)45.0%Not measuredOnly Granite 4.2 8B measured
DTBenchNot measured82.9%Only Qwen3.5-Flash measured
LMCANot measured29.1%Only Qwen3.5-Flash measured
LMArena Text13191397Qwen3.5-Flash
LMArena Text: instruction following13001374Qwen3.5-Flash
LMArena Text: creative writing12361343Qwen3.5-Flash
LMArena Text: English13371404Qwen3.5-Flash
LMArena Text: non-English13011385Qwen3.5-Flash
LMArena Text: Chinese13671445Qwen3.5-Flash
LMArena Text: GermanNot measured1390Only Qwen3.5-Flash measured
LMArena Text: JapaneseNot measured1369Only Qwen3.5-Flash measured
LMArena Text: KoreanNot measured1344Only Qwen3.5-Flash measured
LMArena Text: FrenchNot measured1413Only Qwen3.5-Flash measured
LMArena Text: SpanishNot measured1400Only Qwen3.5-Flash measured
LMArena Text: Russian12821380Qwen3.5-Flash
LMArena Text: PolishNot measured1376Only Qwen3.5-Flash measured
LMArena Text: multi-turn13011393Qwen3.5-Flash
LMArena Text: longer queries13251392Qwen3.5-Flash
LMArena Text: writing and language12691369Qwen3.5-Flash
LMArena Text: entertainment and media12711347Qwen3.5-Flash
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 Granite 4.2 8B and Qwen3.5-Flash
BenchmarkGranite 4.2 8BQwen3.5-FlashLeader
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
Qwen3.5-Flash$0.0002Fits 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
Qwen3.5-Flash$0.0040Fits in one request

Qwen3.5-Flash costs less

Agent loop

200K input + 10K output tokens

Granite 4.2 8B$0.018Exceeds the context window
Qwen3.5-Flash$0.016Fits in one request

Qwen3.5-Flash 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 Qwen3.5-Flash
SpecificationIBM Granite 4.2 8BQwen3.5-Flash
MakerIBM GraniteQwen
WeightsOpen weightsNo public weights listed
ReleasedAugust 31, 2026February 25, 2026
Context window131K1M
Input $/Mtok$0.08$0.065
Output $/Mtok$0.20$0.26
Coding indexNot benchmarked41.1
Independent measurements behind it02
Cost per solved taskNot computable$0.40
SourceOpenRouter listingOpenRouter listing

Questions

Is Granite 4.2 8B better than Qwen3.5-Flash for coding?

Only Qwen3.5-Flash has a coding score, 41.1 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 1.3x cheaper ($0.20 vs $0.26 per million).

Which is cheaper, Granite 4.2 8B or Qwen3.5-Flash?

Granite 4.2 8B costs $0.08 per million input tokens and $0.20 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Cost per solved task is known for Qwen3.5-Flash only.

Which has the bigger context window, Granite 4.2 8B or Qwen3.5-Flash?

Qwen3.5-Flash, with 1M tokens against 131K.

How many benchmarks is the Granite 4.2 8B vs Qwen3.5-Flash comparison based on?

20 benchmarks have a result for both models as of October 22, 2026. Granite 4.2 8B's coding index rests on 0 independent benchmarks and Qwen3.5-Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.

Compare next