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DeepSeek V4 Flash 0423 vs Gemma 3 12B

Updated October 21, 2026. 28 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace DeepSeek V4 Flash 0423 Replace Gemma 3 12B
DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
24.4
Output $/M
$0.28
28
Gemma 3 12BGoogle
Coding
No data
Overall
3.8
Output $/M
$0.1625
0
vs boards won of 28 shared

Decision reading

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

DeepSeek V4 Flash 0423 has the edge where the context window is larger, 1.05M against 131K tokens.

Model ADeepSeek V4 Flash 0423DeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BGemma 3 12BGoogleNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
28
DeepSeek V4 Flash 0423 only
20
Gemma 3 12B only
13
Like-for-like categories
7 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 12B not benchmarked.
Widest category
Coding, 33.0 points apart on average over 3 shared benchmarks.
Widest single gap
AA Coding Index: DeepSeek V4 Flash 0423 52.0 against Gemma 3 12B 5.8, 46.2 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against Gemma 3 12B $0.1625 per million output tokens, 1.7x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, Gemma 3 12B 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 12BTies
Coding30
Intelligence20
Agentic work10
Reasoning30
Math20
Knowledge40
General130
All shared boards280
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 12B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 12BLeader
LMArena WebDev1582Not measuredOnly DeepSeek V4 Flash 0423 measured
AA Coding Index52.05.8DeepSeek V4 Flash 0423
LiveCodeBench (Artificial Analysis run)Not measured13.7%Only Gemma 3 12B measured
SciCodeNot measured16.4%Only Gemma 3 12B measured
Terminal-Bench Hard (Artificial Analysis run)Not measured0.8%Only Gemma 3 12B measured
WeirdML45.6%Not measuredOnly DeepSeek V4 Flash 0423 measured
ALE-Bench678.2Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: coding14571281DeepSeek V4 Flash 0423
LMArena Text: software and IT14531313DeepSeek V4 Flash 0423
LMArena WebDev: React1585Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena WebDev: HTML1558Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 12B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 12BLeader
AA Intelligence Index24.43.8DeepSeek V4 Flash 0423
Epoch Capabilities Index146.1123.5DeepSeek 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 12B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 12BLeader
AA Agentic Index26.30.1DeepSeek V4 Flash 0423
τ²-Bench TelecomNot measured10.8%Only Gemma 3 12B measured
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 12B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 12BLeader
GPQA Diamond (Artificial Analysis run)Not measured34.9%Only Gemma 3 12B measured
Humanity's Last Exam (Artificial Analysis run)Not measured4.2%Only Gemma 3 12B measured
GPQA Diamond (Epoch AI run)Not measured39.5%Only Gemma 3 12B measured
SimpleBench46.3%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: hard prompts14441309DeepSeek V4 Flash 0423
LMArena Text: expert14411248DeepSeek V4 Flash 0423
LMArena Text: hard prompts in English14491318DeepSeek V4 Flash 0423
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 12B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 12BLeader
AA Math IndexNot measured18.3Only Gemma 3 12B measured
AIME 2025 (Artificial Analysis run)Not measured18.3%Only Gemma 3 12B measured
OTIS Mock AIMENot measured16.7%Only Gemma 3 12B measured
LMArena Text: math14261307DeepSeek V4 Flash 0423
LMArena Text: mathematical work14321336DeepSeek V4 Flash 0423
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 12B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 12BLeader
MMLU Pro (Artificial Analysis run)Not measured59.5%Only Gemma 3 12B measured
LMArena Text: science14461366DeepSeek V4 Flash 0423
LMArena Text: medicine and healthcare14481334DeepSeek V4 Flash 0423
LMArena Text: legal and government14391381DeepSeek V4 Flash 0423
LMArena Text: business and finance14251376DeepSeek V4 Flash 0423
Neither model has a result on the other 12 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 12B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 12BLeader
Design Arena: websites1208Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: UI components1165Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: game dev1197Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: data viz1127Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: 3D1189Not 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 index130
General benchmarks for DeepSeek V4 Flash 0423 and Gemma 3 12B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 12BLeader
IFBenchNot measured36.7%Only Gemma 3 12B measured
Long context reasoning (AA-LCR)Not measured8.3%Only Gemma 3 12B measured
DTBench86.4%48.8%DeepSeek V4 Flash 0423
LMCA35.9%4.5%DeepSeek V4 Flash 0423
LMArena Text14321334DeepSeek V4 Flash 0423
LMArena Text: instruction following14211299DeepSeek V4 Flash 0423
LMArena Text: creative writing14031331DeepSeek V4 Flash 0423
LMArena Text: English14411349DeepSeek V4 Flash 0423
LMArena Text: non-English14191318DeepSeek V4 Flash 0423
LMArena Text: Chinese1463Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: German14191370DeepSeek V4 Flash 0423
LMArena Text: Japanese1389Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Korean1383Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: French1439Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Spanish1436Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: Russian14271335DeepSeek V4 Flash 0423
LMArena Text: Polish1436Not measuredOnly DeepSeek V4 Flash 0423 measured
LMArena Text: multi-turn14491334DeepSeek V4 Flash 0423
LMArena Text: longer queries14341317DeepSeek V4 Flash 0423
LMArena Text: writing and language14101307DeepSeek V4 Flash 0423
LMArena Text: entertainment and media14001297DeepSeek V4 Flash 0423
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 0423 and Gemma 3 12B
BenchmarkDeepSeek V4 Flash 0423Gemma 3 12BLeader
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 12B$0.0002Fits in one request

Gemma 3 12B costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0423$0.0078Fits in one request
Gemma 3 12B$0.0042Fits in one request

Gemma 3 12B costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0423$0.031Fits in one request
Gemma 3 12B$0.017Exceeds the context window

Gemma 3 12B 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 12B
SpecificationDeepSeek V4 Flash 0423Google Gemma 3 12B
MakerDeepSeekGoogle
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026March 13, 2025
Context window1.05M131K
Input $/Mtok$0.14$0.075
Output $/Mtok$0.28$0.1625
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 12B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. DeepSeek V4 Flash 0423 has the edge where the context window is larger, 1.05M against 131K tokens.

Which is cheaper, DeepSeek V4 Flash 0423 or Gemma 3 12B?

DeepSeek V4 Flash 0423 costs $0.14 per million input tokens and $0.28 per million output tokens; Gemma 3 12B costs $0.075 and $0.1625. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V4 Flash 0423 or Gemma 3 12B?

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

How many benchmarks is the DeepSeek V4 Flash 0423 vs Gemma 3 12B comparison based on?

28 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Flash 0423's coding index rests on 1 independent benchmark and Gemma 3 12B's on 0. Where only one model has a result, the page says so instead of naming a winner.

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