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DeepSeek V4 Flash 0423 vs Gemma 3 27B

DeepSeek V4 Flash 0423 leads Gemma 3 27B on the Artificial Analysis Intelligence Index, 24.4 to 4.9, at about the same output price ($0.28 vs $0.30 per million). Updated October 22, 2026; 35 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0423 Replace Gemma 3 27B
DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
No data
Output $/M
$0.28
35
Gemma 3 27BGoogle
Coding
No data
Overall
31.4
Output $/M
$0.30
0
vs boards won of 35 shared

DeepSeek V4 Flash 0423 or Gemma 3 27B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick DeepSeek V4 Flash 0423 for output tokens 1.1x cheaper ($0.28 vs $0.30 per million) and a larger context window (1.05M against 131K tokens).

Model ADeepSeek V4 Flash 0423DeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BGemma 3 27BGoogleNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
35
DeepSeek V4 Flash 0423 only
14
Gemma 3 27B only
31
Like-for-like categories
7 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 0423 not benchmarked, Gemma 3 27B not benchmarked.
Widest category
Coding, 27.0 points apart on average over 3 shared benchmarks.
Widest single gap
AA Coding Index: DeepSeek V4 Flash 0423 52.0 against Gemma 3 27B 10.1, 41.9 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against Gemma 3 27B $0.30 per million output tokens, 1.1x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, Gemma 3 27B 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 Flash 0423BarsGemma 3 27BTies
Coding30
Intelligence20
Agentic work10
Reasoning40
Math20
Knowledge40
General190
All shared boards350
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 27B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 27BLeader
Aider polyglotNot measured4.9%Only Gemma 3 27B measured
LMArena WebDev1582Not measuredOnly DeepSeek V4 Flash 0423 measured
AA Coding Index52.010.1DeepSeek V4 Flash 0423
LiveCodeBench (Artificial Analysis run)Not measured13.7%Only Gemma 3 27B measured
SciCodeNot measured23.3%Only Gemma 3 27B measured
Terminal-Bench Hard (Artificial Analysis run)Not measured3.8%Only Gemma 3 27B measured
WeirdML45.6%Not measuredOnly DeepSeek V4 Flash 0423 measured
ALE-Bench678.2Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: coding14571322DeepSeek V4 Flash 0423
LMArena Text: software and IT14531354DeepSeek V4 Flash 0423
LMArena WebDev: React1585Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena WebDev: HTML1558Not measuredOnly DeepSeek V4 Flash 0423 measured
SciCodeNot measured0.0%Only Gemma 3 27B measured
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 27B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 27BLeader
AA Intelligence Index24.44.9DeepSeek V4 Flash 0423
Epoch Capabilities Index146.1130.0DeepSeek V4 Flash 0423
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 27B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 27BLeader
AA Agentic Index26.30.1DeepSeek V4 Flash 0423
τ²-Bench TelecomNot measured10.5%Only Gemma 3 27B measured
Berkeley Function Calling Leaderboard (BFCL)Not measured29.5%Only Gemma 3 27B measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index40
Reasoning benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 27B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 27BLeader
GPQA Diamond (Artificial Analysis run)Not measured42.8%Only Gemma 3 27B measured
Humanity's Last Exam (Artificial Analysis run)Not measured4.4%Only Gemma 3 27B measured
GPQA Diamond (Epoch AI run)Not measured47.7%Only Gemma 3 27B measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: hard prompts14441340DeepSeek V4 Flash 0423
LMArena Text: expert14411304DeepSeek V4 Flash 0423
LMArena Text: hard prompts in English14491353DeepSeek V4 Flash 0423
LMArena Vision: diagramsNot measured1156Only Gemma 3 27B measured
LMArena Vision: homeworkNot measured1160Only Gemma 3 27B measured
Kagi LLM Benchmark52.2%35.1%DeepSeek V4 Flash 0423
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 27B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 27BLeader
AA Math IndexNot measured20.7Only Gemma 3 27B measured
AIME 2025 (Artificial Analysis run)Not measured20.7%Only Gemma 3 27B measured
OTIS Mock AIMENot measured22.5%Only Gemma 3 27B measured
MATH level 5Not measured74.0%Only Gemma 3 27B measured
LMArena Text: math14261312DeepSeek V4 Flash 0423
LMArena Text: mathematical work14321327DeepSeek V4 Flash 0423
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 27B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 27BLeader
MMLU Pro (Artificial Analysis run)Not measured66.9%Only Gemma 3 27B measured
GeoBenchNot measured52.0%Only Gemma 3 27B measured
LMArena Text: science14461383DeepSeek V4 Flash 0423
LMArena Text: medicine and healthcare14481391DeepSeek V4 Flash 0423
LMArena Text: legal and government14391375DeepSeek V4 Flash 0423
LMArena Text: business and finance14251360DeepSeek V4 Flash 0423
FACTS Benchmark SuiteNot measured29.1%Only Gemma 3 27B measured
Neither model has a result on the other 11 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 27B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 27BLeader
Design Arena: websites1207Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: UI components1162Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: game dev1196Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: data viz1127Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: 3D1188Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: all code categories1205Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: SVG1155Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: ASCII art1109Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index190
General benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 27B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 27BLeader
IFBenchNot measured31.8%Only Gemma 3 27B measured
Long context reasoning (AA-LCR)Not measured7.3%Only Gemma 3 27B measured
DTBench86.4%52.5%DeepSeek V4 Flash 0423
LMCA35.9%12.3%DeepSeek V4 Flash 0423
Fiction.LiveBenchNot measured33.3%Only Gemma 3 27B measured
Creative writing (Lech Mazur)Not measured79.9%Only Gemma 3 27B measured
LMArena Text14321358DeepSeek V4 Flash 0423
LMArena Text: instruction following14211321DeepSeek V4 Flash 0423
LMArena Text: creative writing14031345DeepSeek V4 Flash 0423
LMArena VisionNot measured1165Only Gemma 3 27B measured
LMArena Text: English14411377DeepSeek V4 Flash 0423
LMArena Text: non-English14191334DeepSeek V4 Flash 0423
LMArena Text: Chinese14631346DeepSeek V4 Flash 0423
LMArena Text: German14191362DeepSeek V4 Flash 0423
LMArena Text: Japanese13891287DeepSeek V4 Flash 0423
LMArena Text: Korean13831308DeepSeek V4 Flash 0423
LMArena Text: French14391368DeepSeek V4 Flash 0423
LMArena Text: Spanish14361349DeepSeek V4 Flash 0423
LMArena Text: Russian14271349DeepSeek V4 Flash 0423
LMArena Text: Polish14361345DeepSeek V4 Flash 0423
LMArena Text: multi-turn14491345DeepSeek V4 Flash 0423
LMArena Text: longer queries14341333DeepSeek V4 Flash 0423
LMArena Text: writing and language14101347DeepSeek V4 Flash 0423
LMArena Text: entertainment and media14001320DeepSeek V4 Flash 0423
LMArena Vision: EnglishNot measured1188Only Gemma 3 27B measured
LMArena Vision: ChineseNot measured1164Only Gemma 3 27B measured
LMArena Vision: reading textNot measured1156Only Gemma 3 27B measured
LMArena Vision: humorNot measured1166Only Gemma 3 27B measured
LMArena Vision: captioningNot measured1151Only Gemma 3 27B measured
LMArena Vision: recognizing thingsNot measured1196Only Gemma 3 27B measured
LMArena Vision: creative writingNot measured1177Only Gemma 3 27B measured
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 27B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 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 0423$0.0003Fits in one request
Gemma 3 27B$0.0002Fits in one request

Gemma 3 27B costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0423$0.0078Fits in one request
Gemma 3 27B$0.0049Fits in one request

Gemma 3 27B costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0423$0.031Fits in one request
Gemma 3 27B$0.019Exceeds the context window

Gemma 3 27B 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 0423 and Gemma 3 27B
SpecificationDeepSeek V4 Flash 0423Google Gemma 3 27B
MakerDeepSeekGoogle
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026March 12, 2025
Context window1.05M131K
Input $/Mtok$0.14$0.08
Output $/Mtok$0.28$0.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than Gemma 3 27B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V4 Flash 0423 for output tokens 1.1x cheaper ($0.28 vs $0.30 per million) and a larger context window (1.05M against 131K tokens).

Which is cheaper, DeepSeek V4 Flash 0423 or Gemma 3 27B?

DeepSeek V4 Flash 0423 costs $0.14 per million input tokens and $0.28 per million output tokens; Gemma 3 27B costs $0.08 and $0.30. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V4 Flash 0423 or Gemma 3 27B?

DeepSeek V4 Flash 0423, with 1.05M tokens against 131K.

How many benchmarks is the DeepSeek V4 Flash 0423 vs Gemma 3 27B comparison based on?

35 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash 0423's coding index rests on 1 independent benchmark and Gemma 3 27B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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