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DeepSeek V4.1 Flash 1017 vs Granite 4.2 8B

DeepSeek V4.1 Flash 1017 leads Granite 4.2 8B on the Artificial Analysis Intelligence Index, 39.5 to 11.1, and Granite 4.2 8B costs 3.0x less per output token ($0.20 vs $0.60 per million). Updated October 22, 2026; 4 benchmarks have a result for both.

DeepSeek V4.1 Flash 1017DeepSeek
Coding
70.3
Overall
67.6
Output $/M
$0.60
4
Granite 4.2 8BIBM Granite
Coding
No data
Overall
No data
Output $/M
$0.20
0
vs boards won of 4 shared

DeepSeek V4.1 Flash 1017 or Granite 4.2 8B: which to pick

Only DeepSeek V4.1 Flash 1017 has a coding score, 70.3 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 3.0x cheaper ($0.20 vs $0.60 per million).

Shared results
4
DeepSeek V4.1 Flash 1017 only
35
Granite 4.2 8B only
23
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
DeepSeek V4.1 Flash 1017 70.3 from 4 benchmarks, Granite 4.2 8B not benchmarked.
Widest category
General, 37.7 points apart on average over 1 shared benchmark.
Widest single gap
Long context reasoning (AA-LCR): DeepSeek V4.1 Flash 1017 82.7% against Granite 4.2 8B 45.0%, 37.7 points apart on a 0 to 100 scale.
Output price
DeepSeek V4.1 Flash 1017 $0.60 against Granite 4.2 8B $0.20 per million output tokens, 3.0x apart.
Context window
DeepSeek V4.1 Flash 1017 takes 1.05M 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
CategoryDeepSeek V4.1 Flash 1017BarsGranite 4.2 8BTies
Coding10
Intelligence10
Reasoning10
General10
All shared boards40
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
Coding benchmarks for DeepSeek V4.1 Flash 1017 and Granite 4.2 8B
BenchmarkDeepSeek V4.1 Flash 1017Granite 4.2 8BLeader
LiveBench coding96.0%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LMArena WebDev1664Not measuredOnly DeepSeek V4.1 Flash 1017 measured
AA Coding IndexNot measured22.4Only Granite 4.2 8B measured
Terminal-Bench 4 (Vals AI)31.8%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Vibe Code Bench (Vals AI)87.7%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Code migration (Vals AI)44.2%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
SciCode55.9%31.5%DeepSeek V4.1 Flash 1017
ALE-Bench1622.0Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LMArena Text: codingNot measured1378Only Granite 4.2 8B measured
LMArena Text: software and ITNot measured1367Only Granite 4.2 8B measured
LMArena WebDev: React1667Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LMArena WebDev: HTML1687Not measuredOnly DeepSeek V4.1 Flash 1017 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 DeepSeek V4.1 Flash 1017 and Granite 4.2 8B
BenchmarkDeepSeek V4.1 Flash 1017Granite 4.2 8BLeader
AA Intelligence Index39.511.1DeepSeek V4.1 Flash 1017
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Agentic work benchmarks for DeepSeek V4.1 Flash 1017 and Granite 4.2 8B
BenchmarkDeepSeek V4.1 Flash 1017Granite 4.2 8BLeader
AA Agentic IndexNot measured1.3Only Granite 4.2 8B measured
Design Arena: spreadsheets1259Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench research79.5%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench browser76.0%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench long agentic50.9%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Finance Agent (Vals AI)57.0%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Tax Agent Bench (Vals AI)44.4%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Legal Research Bench (Vals AI)45.2%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Harvey's Legal Agent Benchmark (Vals AI)14.2%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Excel Modeling Benchmark (Vals AI)61.8%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
Reasoning benchmarks for DeepSeek V4.1 Flash 1017 and Granite 4.2 8B
BenchmarkDeepSeek V4.1 Flash 1017Granite 4.2 8BLeader
LiveBench reasoning89.1%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
GPQA Diamond (Artificial Analysis run)Not measured63.1%Only Granite 4.2 8B measured
Humanity's Last Exam (Artificial Analysis run)43.3%9.7%DeepSeek V4.1 Flash 1017
GPQA Diamond (Epoch AI run)93.2%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Chess puzzles46.0%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Mystery game puzzles49.0%Not measuredOnly DeepSeek V4.1 Flash 1017 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 14 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Math benchmarks for DeepSeek V4.1 Flash 1017 and Granite 4.2 8B
BenchmarkDeepSeek V4.1 Flash 1017Granite 4.2 8BLeader
OTIS Mock AIME99.4%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
FrontierMath, tiers 1 to 371.2%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
FrontierMath, tier 446.3%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Neither model has a result on the other 11 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Knowledge benchmarks for DeepSeek V4.1 Flash 1017 and Granite 4.2 8B
BenchmarkDeepSeek V4.1 Flash 1017Granite 4.2 8BLeader
SimpleQA Verified42.5%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
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 15 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for DeepSeek V4.1 Flash 1017 and Granite 4.2 8B
BenchmarkDeepSeek V4.1 Flash 1017Granite 4.2 8BLeader
Design Arena: websites1310Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Design Arena: UI components1306Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Design Arena: game dev1352Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Design Arena: data viz1306Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Design Arena: 3D1363Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Design Arena: all code categories1330Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Design Arena: ASCII art1233Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench design83.4%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
General benchmarks for DeepSeek V4.1 Flash 1017 and Granite 4.2 8B
BenchmarkDeepSeek V4.1 Flash 1017Granite 4.2 8BLeader
Vals Index61.3%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench data analysis79.5%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Long context reasoning (AA-LCR)82.7%45.0%DeepSeek V4.1 Flash 1017
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 34 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4.1 Flash 1017 and Granite 4.2 8B
BenchmarkDeepSeek V4.1 Flash 1017Granite 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

DeepSeek V4.1 Flash 1017$0.0004Fits 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

DeepSeek V4.1 Flash 1017$0.0093Fits 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

DeepSeek V4.1 Flash 1017$0.036Fits 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 DeepSeek V4.1 Flash 1017 and Granite 4.2 8B
SpecificationDeepSeek V4.1 Flash 1017IBM Granite 4.2 8B
MakerDeepSeekIBM Granite
WeightsOpen weightsOpen weights
ReleasedOctober 17, 2026August 31, 2026
Context window1.05M131K
Input $/Mtok$0.15$0.08
Output $/Mtok$0.60$0.20
Coding index70.3Not benchmarked
Independent measurements behind it40
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4.1 Flash 1017 better than Granite 4.2 8B for coding?

Only DeepSeek V4.1 Flash 1017 has a coding score, 70.3 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 3.0x cheaper ($0.20 vs $0.60 per million).

Which is cheaper, DeepSeek V4.1 Flash 1017 or Granite 4.2 8B?

DeepSeek V4.1 Flash 1017 costs $0.15 per million input tokens and $0.60 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, DeepSeek V4.1 Flash 1017 or Granite 4.2 8B?

DeepSeek V4.1 Flash 1017, with 1.05M tokens against 131K.

How many benchmarks is the DeepSeek V4.1 Flash 1017 vs Granite 4.2 8B comparison based on?

4 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4.1 Flash 1017's coding index rests on 4 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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