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DeepSeek V4 Flash 0423 vs Gemini 3.5 Flash

Gemini 3.5 Flash leads DeepSeek V4 Flash 0423 on the Artificial Analysis Intelligence Index, 33.6 to 24.4, and DeepSeek V4 Flash 0423 costs 32.1x less per output token ($0.28 vs $9.00 per million). Updated October 22, 2026; 46 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0423 Replace Gemini 3.5 Flash
DeepSeek V4 Flash 0423DeepSeek
Coding
No data
Overall
No data
Output $/M
$0.28
3
Gemini 3.5 FlashGoogle
Coding
39.8
Overall
63.8
Output $/M
$9.00
43
vs boards won of 46 shared

DeepSeek V4 Flash 0423 or Gemini 3.5 Flash: which to pick

Only Gemini 3.5 Flash has a coding score, 39.8 on the Vibe Coding Index; DeepSeek V4 Flash 0423 has none, so the two cannot be ranked on coding.

Pick DeepSeek V4 Flash 0423 for output tokens 32.1x cheaper ($0.28 vs $9.00 per million) and work measured by LMArena WebDev or LMArena WebDev: React, where it leads.

Model ADeepSeek V4 Flash 0423DeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BGemini 3.5 FlashGoogle39.8/1004 independent benchmarks$1.21 per solved task
Shared results
46
DeepSeek V4 Flash 0423 only
3
Gemini 3.5 Flash only
66
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, Gemini 3.5 Flash 39.8 from 4 benchmarks.
Widest category
Reasoning, 13.1 points apart on average over 4 shared benchmarks.
Widest single gap
SimpleBench: DeepSeek V4 Flash 0423 46.3% against Gemini 3.5 Flash 76.7%, 30.4 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.28 against Gemini 3.5 Flash $9.00 per million output tokens, 32.1x apart.
Context window
Both take 1.05M tokens.

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 0423BarsGemini 3.5 FlashTies
Coding34
Intelligence02
Reasoning04
Math02
Knowledge04
Web design08
General019
All shared boards343
CodingLike-for-likeSix of these boards feed the Vibe Coding Index34
Coding benchmarks for DeepSeek V4 Flash 0423 and Gemini 3.5 Flash
BenchmarkDeepSeek V4 Flash 0423Gemini 3.5 FlashLeader
LMArena WebDev15821499DeepSeek V4 Flash 0423
AA Coding Index52.0Not measuredOnly DeepSeek V4 Flash 0423 measured
LiveCodeBench (Vals AI)Not measured87.6%Only Gemini 3.5 Flash measured
SWE-bench Verified (Vals AI)Not measured78.8%Only Gemini 3.5 Flash measured
Terminal-Bench 4 (Vals AI)Not measured6.1%Only Gemini 3.5 Flash measured
Vibe Code Bench (Vals AI)Not measured48.7%Only Gemini 3.5 Flash measured
Code migration (Vals AI)Not measured26.8%Only Gemini 3.5 Flash measured
ProgramBench (Vals AI)Not measured0.0%Only Gemini 3.5 Flash measured
Terminal-Bench 2.1 (Vals AI)Not measured74.2%Only Gemini 3.5 Flash measured
SkillsBench (Vals AI)Not measured52.7%Only Gemini 3.5 Flash measured
SciCodeNot measured53.9%Only Gemini 3.5 Flash measured
Terminal-Bench Hard (Artificial Analysis run)Not measured46.2%Only Gemini 3.5 Flash measured
WeirdML45.6%62.6%Gemini 3.5 Flash
ALE-Bench678.2911.0Gemini 3.5 Flash
LMArena Text: coding14571493Gemini 3.5 Flash
LMArena Text: software and IT14531494Gemini 3.5 Flash
LMArena WebDev: React15851495DeepSeek V4 Flash 0423
LMArena WebDev: HTML15581522DeepSeek V4 Flash 0423
LMArena WebDev: from an imageNot measured1504Only Gemini 3.5 Flash measured
SciCodeNot measured12.3%Only Gemini 3.5 Flash measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for DeepSeek V4 Flash 0423 and Gemini 3.5 Flash
BenchmarkDeepSeek V4 Flash 0423Gemini 3.5 FlashLeader
AA Intelligence Index24.433.6Gemini 3.5 Flash
Epoch Capabilities Index146.1154.9Gemini 3.5 Flash
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0423 and Gemini 3.5 Flash
BenchmarkDeepSeek V4 Flash 0423Gemini 3.5 FlashLeader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: agents building web appsNot measured1202Only Gemini 3.5 Flash measured
Design Arena: agents building full-stack appsNot measured1197Only Gemini 3.5 Flash measured
Design Arena: agents building mobile appsNot measured1174Only Gemini 3.5 Flash measured
Design Arena: agents building Android appsNot measured1185Only Gemini 3.5 Flash measured
Design Arena: agents building Godot gamesNot measured1098Only Gemini 3.5 Flash measured
Design Arena: agents building gamesNot measured1180Only Gemini 3.5 Flash measured
Design Arena: HTML slidesNot measured1093Only Gemini 3.5 Flash measured
Design Arena: PowerPoint slidesNot measured1154Only Gemini 3.5 Flash measured
Finance Agent (Vals AI)Not measured57.9%Only Gemini 3.5 Flash measured
Tax Agent Bench (Vals AI)Not measured21.6%Only Gemini 3.5 Flash measured
Legal Research Bench (Vals AI)Not measured30.8%Only Gemini 3.5 Flash measured
Excel Modeling Benchmark (Vals AI)Not measured63.5%Only Gemini 3.5 Flash measured
Terminal-Bench-Science (Vals AI)Not measured5.7%Only Gemini 3.5 Flash measured
τ²-Bench TelecomNot measured95.6%Only Gemini 3.5 Flash measured
APEX-AgentsNot measured27.5%Only Gemini 3.5 Flash measured
Vending-Bench 2Not measured$5,396Only Gemini 3.5 Flash measured
Neither model has a result on the other 24 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for DeepSeek V4 Flash 0423 and Gemini 3.5 Flash
BenchmarkDeepSeek V4 Flash 0423Gemini 3.5 FlashLeader
GPQA DiamondNot measured92.7%Only Gemini 3.5 Flash measured
MMMU Pro (Vals AI)Not measured88.3%Only Gemini 3.5 Flash measured
GPQA Diamond (Artificial Analysis run)Not measured92.2%Only Gemini 3.5 Flash measured
Humanity's Last Exam (Artificial Analysis run)Not measured42.7%Only Gemini 3.5 Flash measured
GPQA Diamond (Epoch AI run)Not measured92.8%Only Gemini 3.5 Flash measured
ARC-AGINot measured92.5%Only Gemini 3.5 Flash measured
ARC-AGI-2Not measured72.1%Only Gemini 3.5 Flash measured
SimpleBench46.3%76.7%Gemini 3.5 Flash
Chess puzzlesNot measured45.0%Only Gemini 3.5 Flash measured
Mystery game puzzlesNot measured32.0%Only Gemini 3.5 Flash measured
EBR-benchNot measured4.8%Only Gemini 3.5 Flash measured
LMArena Text: hard prompts14441488Gemini 3.5 Flash
LMArena Text: expert14411495Gemini 3.5 Flash
LMArena Text: hard prompts in English14491483Gemini 3.5 Flash
LMArena Vision: diagramsNot measured1323Only Gemini 3.5 Flash measured
LMArena Vision: homeworkNot measured1330Only Gemini 3.5 Flash measured
Kagi LLM Benchmark52.2%Not measuredOnly DeepSeek V4 Flash 0423 measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for DeepSeek V4 Flash 0423 and Gemini 3.5 Flash
BenchmarkDeepSeek V4 Flash 0423Gemini 3.5 FlashLeader
OTIS Mock AIMENot measured95.6%Only Gemini 3.5 Flash measured
FrontierMath, tiers 1 to 3Not measured62.8%Only Gemini 3.5 Flash measured
FrontierMath, tier 4Not measured26.8%Only Gemini 3.5 Flash measured
ProofBenchNot measured31.0%Only Gemini 3.5 Flash measured
LMArena Text: math14261504Gemini 3.5 Flash
LMArena Text: mathematical work14321495Gemini 3.5 Flash
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for DeepSeek V4 Flash 0423 and Gemini 3.5 Flash
BenchmarkDeepSeek V4 Flash 0423Gemini 3.5 FlashLeader
MMLU ProNot measured89.5%Only Gemini 3.5 Flash measured
LegalBench (Vals AI)Not measured83.6%Only Gemini 3.5 Flash measured
CorpFin (Vals AI)Not measured64.7%Only Gemini 3.5 Flash measured
TaxEval (Vals AI)Not measured74.4%Only Gemini 3.5 Flash measured
MortgageTax (Vals AI)Not measured68.1%Only Gemini 3.5 Flash measured
MedCode (Vals AI)Not measured55.8%Only Gemini 3.5 Flash measured
SimpleQA VerifiedNot measured66.2%Only Gemini 3.5 Flash measured
LMArena Text: science14461495Gemini 3.5 Flash
LMArena Text: medicine and healthcare14481483Gemini 3.5 Flash
LMArena Text: legal and government14391488Gemini 3.5 Flash
LMArena Text: business and finance14251467Gemini 3.5 Flash
FACTS Benchmark SuiteNot measured63.1%Only Gemini 3.5 Flash measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for DeepSeek V4 Flash 0423 and Gemini 3.5 Flash
BenchmarkDeepSeek V4 Flash 0423Gemini 3.5 FlashLeader
Design Arena: websites12071267Gemini 3.5 Flash
Design Arena: UI components11621269Gemini 3.5 Flash
Design Arena: game dev11961263Gemini 3.5 Flash
Design Arena: data viz11271236Gemini 3.5 Flash
Design Arena: 3D11881243Gemini 3.5 Flash
Design Arena: all code categories12051266Gemini 3.5 Flash
Design Arena: SVG11551253Gemini 3.5 Flash
Design Arena: ASCII art11091254Gemini 3.5 Flash
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index019
General benchmarks for DeepSeek V4 Flash 0423 and Gemini 3.5 Flash
BenchmarkDeepSeek V4 Flash 0423Gemini 3.5 FlashLeader
Public Benefits Bench (Vals AI)Not measured59.5%Only Gemini 3.5 Flash measured
SAGE (Vals AI)Not measured49.9%Only Gemini 3.5 Flash measured
MedScribe (Vals AI)Not measured76.6%Only Gemini 3.5 Flash measured
Vals Multimodal IndexNot measured62.9%Only Gemini 3.5 Flash measured
IFBenchNot measured76.3%Only Gemini 3.5 Flash measured
Long context reasoning (AA-LCR)Not measured74.3%Only Gemini 3.5 Flash measured
DTBench86.4%94.7%Gemini 3.5 Flash
LMCA35.9%47.1%Gemini 3.5 Flash
Surface Evolver BenchNot measured58.1%Only Gemini 3.5 Flash measured
LMArena Text14321482Gemini 3.5 Flash
LMArena Text: instruction following14211467Gemini 3.5 Flash
LMArena Text: creative writing14031470Gemini 3.5 Flash
LMArena VisionNot measured1308Only Gemini 3.5 Flash measured
LMArena Text: English14411481Gemini 3.5 Flash
LMArena Text: non-English14191475Gemini 3.5 Flash
LMArena Text: Chinese14631527Gemini 3.5 Flash
LMArena Text: German14191494Gemini 3.5 Flash
LMArena Text: Japanese13891486Gemini 3.5 Flash
LMArena Text: Korean13831448Gemini 3.5 Flash
LMArena Text: French14391490Gemini 3.5 Flash
LMArena Text: Spanish14361480Gemini 3.5 Flash
LMArena Text: Russian14271493Gemini 3.5 Flash
LMArena Text: Polish14361516Gemini 3.5 Flash
LMArena Text: multi-turn14491481Gemini 3.5 Flash
LMArena Text: longer queries14341483Gemini 3.5 Flash
LMArena Text: writing and language14101478Gemini 3.5 Flash
LMArena Text: entertainment and media14001459Gemini 3.5 Flash
LMArena Vision: EnglishNot measured1305Only Gemini 3.5 Flash measured
LMArena Vision: ChineseNot measured1377Only Gemini 3.5 Flash measured
LMArena Vision: reading textNot measured1317Only Gemini 3.5 Flash measured
LMArena Vision: humorNot measured1321Only Gemini 3.5 Flash measured
LMArena Vision: creative writingNot measured1301Only Gemini 3.5 Flash measured
LMArena DocumentNot measured1463Only Gemini 3.5 Flash measured
Neither model has a result on the other 13 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 Gemini 3.5 Flash
BenchmarkDeepSeek V4 Flash 0423Gemini 3.5 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

DeepSeek V4 Flash 0423$0.0003Fits in one request
Gemini 3.5 Flash$0.0060Fits in one request

DeepSeek V4 Flash 0423 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0423$0.0078Fits in one request
Gemini 3.5 Flash$0.102Fits in one request

DeepSeek V4 Flash 0423 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0423$0.031Fits in one request
Gemini 3.5 Flash$0.390Fits in one request

DeepSeek V4 Flash 0423 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 Gemini 3.5 Flash
SpecificationDeepSeek V4 Flash 0423Google Gemini 3.5 Flash
MakerDeepSeekGoogle
WeightsOpen weightsNo public weights listed
ReleasedApril 24, 2026May 19, 2026
Context window1.05M1.05M
Input $/Mtok$0.14$1.50
Output $/Mtok$0.28$9.00
Coding indexNot benchmarked39.8
Independent measurements behind it14
Cost per solved taskNot computable$1.21
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than Gemini 3.5 Flash for coding?

Only Gemini 3.5 Flash has a coding score, 39.8 on the Vibe Coding Index; DeepSeek V4 Flash 0423 has none, so the two cannot be ranked on coding. Pick DeepSeek V4 Flash 0423 for output tokens 32.1x cheaper ($0.28 vs $9.00 per million) and work measured by LMArena WebDev or LMArena WebDev: React, where it leads.

Which is cheaper, DeepSeek V4 Flash 0423 or Gemini 3.5 Flash?

DeepSeek V4 Flash 0423 costs $0.14 per million input tokens and $0.28 per million output tokens; Gemini 3.5 Flash costs $1.50 and $9.00. Cost per solved task is known for Gemini 3.5 Flash only.

Which has the bigger context window, DeepSeek V4 Flash 0423 or Gemini 3.5 Flash?

Neither: both take 1.05M tokens.

How many benchmarks is the DeepSeek V4 Flash 0423 vs Gemini 3.5 Flash comparison based on?

46 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 Gemini 3.5 Flash's on 4. Where only one model has a result, the page says so instead of naming a winner.

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