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DeepSeek V4 Flash 0731 vs Gemma 2 27B

DeepSeek V4 Flash 0731 costs 2.3x less per output token than Gemma 2 27B ($0.28 vs $0.65 per million). Updated October 21, 2026; 6 benchmarks have a result for both.

DeepSeek V4 Flash 0731DeepSeek
Coding
51.8
Overall
55.2
Output $/M
$0.28
6
Gemma 2 27BGoogle
Coding
No data
Overall
No data
Output $/M
$0.65
0
vs boards won of 6 shared

DeepSeek V4 Flash 0731 or Gemma 2 27B: which to pick

Only DeepSeek V4 Flash 0731 has a coding score, 51.8 on the Vibe Coding Index; Gemma 2 27B has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Shared results
6
DeepSeek V4 Flash 0731 only
49
Gemma 2 27B only
30
Like-for-like categories
5 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 Flash 0731 51.8 from 4 benchmarks, Gemma 2 27B not benchmarked.
Widest category
Math, 93.1 points apart on average over 1 shared benchmark.
Widest single gap
OTIS Mock AIME: DeepSeek V4 Flash 0731 94.4% against Gemma 2 27B 1.4%, 93.1 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0731 $0.28 against Gemma 2 27B $0.65 per million output tokens, 2.3x apart.
Context window
DeepSeek V4 Flash 0731 takes 1.05M tokens, Gemma 2 27B 8K.

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 Flash 0731BarsGemma 2 27BTies
Intelligence10
Reasoning10
Math10
Knowledge10
General20
All shared boards60
CodingDirectional onlySix of these boards feed the Vibe Coding Index17 boards, none shared
Coding benchmarks for DeepSeek V4 Flash 0731 and Gemma 2 27B
BenchmarkDeepSeek V4 Flash 0731Gemma 2 27BLeader
AA Coding Index69.1Not measuredOnly DeepSeek V4 Flash 0731 measured
LiveCodeBench (Vals AI)87.3%Not measuredOnly DeepSeek V4 Flash 0731 measured
SWE-bench Verified (Vals AI)88.8%Not measuredOnly DeepSeek V4 Flash 0731 measured
Terminal-Bench 4 (Vals AI)18.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
Vibe Code Bench (Vals AI)74.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
Code migration (Vals AI)38.6%Not measuredOnly DeepSeek V4 Flash 0731 measured
ProgramBench (Vals AI)0.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
IOI (Vals AI)32.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
Terminal-Bench 2.1 (Vals AI)67.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
SkillsBench (Vals AI)50.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
CyberBench (Vals AI)72.1%Not measuredOnly DeepSeek V4 Flash 0731 measured
SciCode50.3%Not measuredOnly DeepSeek V4 Flash 0731 measured
FrontierCode18.8%Not measuredOnly DeepSeek V4 Flash 0731 measured
WeirdML63.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
ALE-Bench1306.1Not measuredOnly DeepSeek V4 Flash 0731 measured
LMArena Text: codingNot measured1211Only Gemma 2 27B measured
LMArena Text: software and ITNot measured1228Only Gemma 2 27B measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V4 Flash 0731 and Gemma 2 27B
BenchmarkDeepSeek V4 Flash 0731Gemma 2 27BLeader
AA Intelligence Index34.3Not measuredOnly DeepSeek V4 Flash 0731 measured
Epoch Capabilities Index154.8122.1DeepSeek V4 Flash 0731
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0731 and Gemma 2 27B
BenchmarkDeepSeek V4 Flash 0731Gemma 2 27BLeader
AA Agentic Index41.0Not measuredOnly DeepSeek V4 Flash 0731 measured
Finance Agent (Vals AI)49.5%Not measuredOnly DeepSeek V4 Flash 0731 measured
Tax Agent Bench (Vals AI)28.1%Not measuredOnly DeepSeek V4 Flash 0731 measured
Legal Research Bench (Vals AI)30.3%Not measuredOnly DeepSeek V4 Flash 0731 measured
Excel Modeling Benchmark (Vals AI)57.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
BioMysteryBench (Vals AI)64.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
Terminal-Bench-Science (Vals AI)4.3%Not measuredOnly DeepSeek V4 Flash 0731 measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
Reasoning benchmarks for DeepSeek V4 Flash 0731 and Gemma 2 27B
BenchmarkDeepSeek V4 Flash 0731Gemma 2 27BLeader
GPQA Diamond89.9%Not measuredOnly DeepSeek V4 Flash 0731 measured
GPQA Diamond (Artificial Analysis run)90.8%Not measuredOnly DeepSeek V4 Flash 0731 measured
Humanity's Last Exam (Artificial Analysis run)38.6%Not measuredOnly DeepSeek V4 Flash 0731 measured
GPQA Diamond (Epoch AI run)91.0%36.5%DeepSeek V4 Flash 0731
ARC-AGI89.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
ARC-AGI-261.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
SimpleBench61.1%Not measuredOnly DeepSeek V4 Flash 0731 measured
Chess puzzles32.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
Mystery game puzzles34.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
LMArena Text: hard promptsNot measured1198Only Gemma 2 27B measured
LMArena Text: expertNot measured1171Only Gemma 2 27B measured
LMArena Text: hard prompts in EnglishNot measured1206Only Gemma 2 27B measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index10
Math benchmarks for DeepSeek V4 Flash 0731 and Gemma 2 27B
BenchmarkDeepSeek V4 Flash 0731Gemma 2 27BLeader
OTIS Mock AIME94.4%1.4%DeepSeek V4 Flash 0731
FrontierMath, tiers 1 to 357.5%Not measuredOnly DeepSeek V4 Flash 0731 measured
FrontierMath, tier 424.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
ProofBench56.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
MATH level 5Not measured27.9%Only Gemma 2 27B measured
LMArena Text: mathNot measured1212Only Gemma 2 27B measured
LMArena Text: mathematical workNot measured1221Only Gemma 2 27B measured
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for DeepSeek V4 Flash 0731 and Gemma 2 27B
BenchmarkDeepSeek V4 Flash 0731Gemma 2 27BLeader
MMLU Pro86.2%Not measuredOnly DeepSeek V4 Flash 0731 measured
LegalBench (Vals AI)77.7%68.0%DeepSeek V4 Flash 0731
CorpFin (Vals AI)61.9%Not measuredOnly DeepSeek V4 Flash 0731 measured
TaxEval (Vals AI)70.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
MedCode (Vals AI)41.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
SimpleQA Verified33.6%Not measuredOnly DeepSeek V4 Flash 0731 measured
MMLUNot measured75.7%Only Gemma 2 27B measured
LMArena Text: scienceNot measured1228Only Gemma 2 27B measured
LMArena Text: medicine and healthcareNot measured1198Only Gemma 2 27B measured
LMArena Text: legal and governmentNot measured1241Only Gemma 2 27B measured
LMArena Text: business and financeNot measured1208Only Gemma 2 27B measured
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for DeepSeek V4 Flash 0731 and Gemma 2 27B
BenchmarkDeepSeek V4 Flash 0731Gemma 2 27BLeader
Design Arena: websites1238Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: UI components1235Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: game dev1208Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: data viz1180Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: 3D1209Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: all code categories1230Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: SVG1185Not measuredOnly DeepSeek V4 Flash 0731 measured
Design Arena: ASCII art1090Not measuredOnly DeepSeek V4 Flash 0731 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
General benchmarks for DeepSeek V4 Flash 0731 and Gemma 2 27B
BenchmarkDeepSeek V4 Flash 0731Gemma 2 27BLeader
MedScribe (Vals AI)80.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
Long context reasoning (AA-LCR)79.7%Not measuredOnly DeepSeek V4 Flash 0731 measured
DTBench90.9%48.0%DeepSeek V4 Flash 0731
LMCA41.7%7.1%DeepSeek V4 Flash 0731
LMArena TextNot measured1231Only Gemma 2 27B measured
LMArena Text: instruction followingNot measured1206Only Gemma 2 27B measured
LMArena Text: creative writingNot measured1240Only Gemma 2 27B measured
LMArena Text: EnglishNot measured1242Only Gemma 2 27B measured
LMArena Text: non-EnglishNot measured1217Only Gemma 2 27B measured
LMArena Text: ChineseNot measured1221Only Gemma 2 27B measured
LMArena Text: GermanNot measured1209Only Gemma 2 27B measured
LMArena Text: JapaneseNot measured1175Only Gemma 2 27B measured
LMArena Text: KoreanNot measured1174Only Gemma 2 27B measured
LMArena Text: FrenchNot measured1248Only Gemma 2 27B measured
LMArena Text: SpanishNot measured1228Only Gemma 2 27B measured
LMArena Text: RussianNot measured1234Only Gemma 2 27B measured
LMArena Text: PolishNot measured1277Only Gemma 2 27B measured
LMArena Text: multi-turnNot measured1224Only Gemma 2 27B measured
LMArena Text: longer queriesNot measured1230Only Gemma 2 27B measured
LMArena Text: writing and languageNot measured1249Only Gemma 2 27B measured
LMArena Text: entertainment and mediaNot measured1212Only Gemma 2 27B measured
Neither model has a result on the other 25 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4 Flash 0731 and Gemma 2 27B
BenchmarkDeepSeek V4 Flash 0731Gemma 2 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

DeepSeek V4 Flash 0731$0.0003Fits in one request
Gemma 2 27B$0.0010Fits in one request

DeepSeek V4 Flash 0731 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0731$0.0078Fits in one request
Gemma 2 27B$0.034Exceeds the context window

DeepSeek V4 Flash 0731 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0731$0.031Fits in one request
Gemma 2 27B$0.137Exceeds the context window

DeepSeek V4 Flash 0731 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 Flash 0731 and Gemma 2 27B
SpecificationDeepSeek V4 Flash 0731Google Gemma 2 27B
MakerDeepSeekGoogle
WeightsOpen weightsOpen weights
ReleasedJuly 31, 2026July 13, 2024
Context window1.05M8K
Input $/Mtok$0.14$0.65
Output $/Mtok$0.28$0.65
Coding index51.8Not benchmarked
Independent measurements behind it40
Cost per solved task$0.01Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0731 better than Gemma 2 27B for coding?

Only DeepSeek V4 Flash 0731 has a coding score, 51.8 on the Vibe Coding Index; Gemma 2 27B has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, DeepSeek V4 Flash 0731 or Gemma 2 27B?

DeepSeek V4 Flash 0731 costs $0.14 per million input tokens and $0.28 per million output tokens; Gemma 2 27B costs $0.65 and $0.65. Cost per solved task is known for DeepSeek V4 Flash 0731 only.

Which has the bigger context window, DeepSeek V4 Flash 0731 or Gemma 2 27B?

DeepSeek V4 Flash 0731, with 1.05M tokens against 8K.

How many benchmarks is the DeepSeek V4 Flash 0731 vs Gemma 2 27B comparison based on?

6 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Flash 0731's coding index rests on 4 independent benchmarks and Gemma 2 27B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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