DeepSeek V4 Pro 0813 vs Gemini 3.5 Flash Lite

DeepSeek V4 Pro 0813 leads Gemini 3.5 Flash Lite on coding, 56.1 to 49.0 on the Vibe Coding Index, and DeepSeek V4 Pro 0813 costs 1.3x less per output token ($1.98 vs $2.50 per million). Updated October 22, 2026; 67 benchmarks have a result for both.

Replace DeepSeek V4 Pro 0813 Replace Gemini 3.5 Flash Lite

DeepSeek V4 Pro 0813DeepSeek

Coding: 56.1
Overall: 60.8
Output $/M: $1.98

Gemini 3.5 Flash LiteGoogle

Coding: 49.0
Overall: 49.8
Output $/M: $2.50

vs boards won of 67 shared, 1 tied

DeepSeek V4 Pro 0813 or Gemini 3.5 Flash Lite: which to pick

Pick DeepSeek V4 Pro 0813 for coding: it scores 56.1 on the Vibe Coding Index against 49.0 for Gemini 3.5 Flash Lite.

Pick Gemini 3.5 Flash Lite for work measured by LegalBench (Vals AI) or MedCode (Vals AI), where it leads.

Model ADeepSeek V4 Pro 0813DeepSeek56.1/1005 independent benchmarks$0.10 per solved task Model BGemini 3.5 Flash LiteGoogle49.0/1003 independent benchmarks$0.41 per solved task

671118

Shared results: 67
DeepSeek V4 Pro 0813 only: 11
Gemini 3.5 Flash Lite only: 18
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.

Coding
Vibe Coding Index, six public coding benchmarks
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 scores 56.1 against 49.0.
5 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 36.0 against 22.2.
Same board, both measured
Agentic work
AA Agentic Index
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 41.3 against 14.3.
Same board, both measured
Reasoning
GPQA Diamond
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 92.4% against 83.8%.
Same board, both measured
Knowledge
MMLU Pro
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 leads, 87.0% against 85.8%.
Same board, both measured
General
Vals Index
No call
Only DeepSeek V4 Pro 0813 has a Vals Index result, 53.0%.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 3.5 Flash Lite
DeepSeek V4 Pro 0813 $0.0016, Gemini 3.5 Flash Lite $0.0015 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813 $0.10, Gemini 3.5 Flash Lite $0.41.
Published attempt cost and pass rate

At a glance

Coding index: DeepSeek V4 Pro 0813 56.1 from 5 benchmarks, Gemini 3.5 Flash Lite 49.0 from 3 benchmarks.
Widest category: Math, 22.1 points apart on average over 6 shared benchmarks.
Widest single gap: ARC-AGI-2: DeepSeek V4 Pro 0813 61.3% against Gemini 3.5 Flash Lite 10.3%, 51.0 points apart on a 0 to 100 scale.
Output price: DeepSeek V4 Pro 0813 $1.98 against Gemini 3.5 Flash Lite $2.50 per million output tokens, 1.3x 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
Category	DeepSeek V4 Pro 0813	Gemini 3.5 Flash Lite	Ties
Coding	14	0	1 tie
Intelligence	2	0
Agentic work	6	0
Reasoning	11	0
Math	6	0
Knowledge	7	2
General	16	2
All shared boards	62	4	1 tie

CodingLike-for-likeSix of these boards feed the Vibe Coding Index140

Coding benchmarks for DeepSeek V4 Pro 0813 and Gemini 3.5 Flash Lite
Benchmark	DeepSeek V4 Pro 0813	Gemini 3.5 Flash Lite	Leader
LMArena WebDev	1582	1435	DeepSeek V4 Pro 0813
AA Coding Index	68.8	49.3	DeepSeek V4 Pro 0813
LiveCodeBench (Vals AI)	87.5%	79.0%	DeepSeek V4 Pro 0813
SWE-bench Verified (Vals AI)	96.4%	75.0%	DeepSeek V4 Pro 0813
Terminal-Bench 4 (Vals AI)	14.1%	Not measured	Only DeepSeek V4 Pro 0813 measured
Vibe Code Bench (Vals AI)	82.3%	37.2%	DeepSeek V4 Pro 0813
Code migration (Vals AI)	41.5%	6.2%	DeepSeek V4 Pro 0813
ProgramBench (Vals AI)	0.0%	0.0%	Tie
IOI (Vals AI)	51.6%	Not measured	Only DeepSeek V4 Pro 0813 measured
Terminal-Bench 2.1 (Vals AI)	54.7%	50.2%	DeepSeek V4 Pro 0813
Vibe Code Bench 1-100 (Vals AI)	17.5%	Not measured	Only DeepSeek V4 Pro 0813 measured
SkillsBench (Vals AI)	53.8%	Not measured	Only DeepSeek V4 Pro 0813 measured
CyberBench (Vals AI)	72.9%	59.1%	DeepSeek V4 Pro 0813
SciCode	51.0%	41.3%	DeepSeek V4 Pro 0813
FrontierCode	28.5%	Not measured	Only DeepSeek V4 Pro 0813 measured
WeirdML	66.2%	39.0%	DeepSeek V4 Pro 0813
ALE-Bench	1403.2	765.3	DeepSeek V4 Pro 0813
LMArena Text: coding	1469	1453	DeepSeek V4 Pro 0813
LMArena Text: software and IT	1462	1451	DeepSeek V4 Pro 0813
LMArena WebDev: React	1588	1408	DeepSeek V4 Pro 0813
LMArena WebDev: HTML	1566	Not measured	Only DeepSeek V4 Pro 0813 measured
LMArena WebDev: from an image	Not measured	1448	Only Gemini 3.5 Flash Lite measured
SciCode	Not measured	6.2%	Only Gemini 3.5 Flash Lite measured
Neither model has a result on the other 16 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20

Intelligence benchmarks for DeepSeek V4 Pro 0813 and Gemini 3.5 Flash Lite
Benchmark	DeepSeek V4 Pro 0813	Gemini 3.5 Flash Lite	Leader
AA Intelligence Index	36.0	22.2	DeepSeek V4 Pro 0813
Epoch Capabilities Index	155.6	144.9	DeepSeek V4 Pro 0813

Agentic workLike-for-likePublic boards, shown as published, kept out of the index60

Agentic work benchmarks for DeepSeek V4 Pro 0813 and Gemini 3.5 Flash Lite
Benchmark	DeepSeek V4 Pro 0813	Gemini 3.5 Flash Lite	Leader
AA Agentic Index	41.3	14.3	DeepSeek V4 Pro 0813
SREBench (Vals AI)	1.9%	Not measured	Only DeepSeek V4 Pro 0813 measured
Finance Agent (Vals AI)	50.4%	47.4%	DeepSeek V4 Pro 0813
Tax Agent Bench (Vals AI)	26.8%	7.2%	DeepSeek V4 Pro 0813
Legal Research Bench (Vals AI)	40.9%	13.9%	DeepSeek V4 Pro 0813
Harvey's Legal Agent Benchmark (Vals AI)	10.8%	Not measured	Only DeepSeek V4 Pro 0813 measured
Excel Modeling Benchmark (Vals AI)	52.8%	43.2%	DeepSeek V4 Pro 0813
Terminal-Bench-Science (Vals AI)	4.3%	Not measured	Only DeepSeek V4 Pro 0813 measured
APEX-Agents	47.3%	29.3%	DeepSeek V4 Pro 0813
Neither model has a result on the other 32 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index110

Reasoning benchmarks for DeepSeek V4 Pro 0813 and Gemini 3.5 Flash Lite
Benchmark	DeepSeek V4 Pro 0813	Gemini 3.5 Flash Lite	Leader
GPQA Diamond	92.4%	83.8%	DeepSeek V4 Pro 0813
MMMU Pro (Vals AI)	Not measured	83.6%	Only Gemini 3.5 Flash Lite measured
GPQA Diamond (Artificial Analysis run)	92.8%	83.8%	DeepSeek V4 Pro 0813
Humanity's Last Exam (Artificial Analysis run)	41.0%	18.8%	DeepSeek V4 Pro 0813
GPQA Diamond (Epoch AI run)	91.7%	83.3%	DeepSeek V4 Pro 0813
ARC-AGI	90.5%	53.5%	DeepSeek V4 Pro 0813
ARC-AGI-2	61.3%	10.3%	DeepSeek V4 Pro 0813
Chess puzzles	46.0%	21.0%	DeepSeek V4 Pro 0813
Mystery game puzzles	43.0%	19.0%	DeepSeek V4 Pro 0813
LMArena Text: hard prompts	1458	1441	DeepSeek V4 Pro 0813
LMArena Text: expert	1459	1434	DeepSeek V4 Pro 0813
LMArena Text: hard prompts in English	1463	1440	DeepSeek V4 Pro 0813
LMArena Vision: diagrams	Not measured	1284	Only Gemini 3.5 Flash Lite measured
LMArena Vision: homework	Not measured	1291	Only Gemini 3.5 Flash Lite measured
Neither model has a result on the other 8 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index60

Math benchmarks for DeepSeek V4 Pro 0813 and Gemini 3.5 Flash Lite
Benchmark	DeepSeek V4 Pro 0813	Gemini 3.5 Flash Lite	Leader
OTIS Mock AIME	98.6%	71.1%	DeepSeek V4 Pro 0813
FrontierMath, tiers 1 to 3	64.6%	26.0%	DeepSeek V4 Pro 0813
FrontierMath, tier 4	26.8%	0.0%	DeepSeek V4 Pro 0813
ProofBench	50.0%	13.0%	DeepSeek V4 Pro 0813
LMArena Text: math	1441	1434	DeepSeek V4 Pro 0813
LMArena Text: mathematical work	1443	1433	DeepSeek V4 Pro 0813
Neither model has a result on the other 7 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index72

Knowledge benchmarks for DeepSeek V4 Pro 0813 and Gemini 3.5 Flash Lite
Benchmark	DeepSeek V4 Pro 0813	Gemini 3.5 Flash Lite	Leader
MMLU Pro	87.0%	85.8%	DeepSeek V4 Pro 0813
LegalBench (Vals AI)	82.4%	84.1%	Gemini 3.5 Flash Lite
CorpFin (Vals AI)	65.4%	60.7%	DeepSeek V4 Pro 0813
TaxEval (Vals AI)	73.1%	72.6%	DeepSeek V4 Pro 0813
MortgageTax (Vals AI)	Not measured	68.7%	Only Gemini 3.5 Flash Lite measured
MedCode (Vals AI)	42.5%	43.5%	Gemini 3.5 Flash Lite
SimpleQA Verified	52.9%	Not measured	Only DeepSeek V4 Pro 0813 measured
LMArena Text: science	1457	1451	DeepSeek V4 Pro 0813
LMArena Text: medicine and healthcare	1446	1438	DeepSeek V4 Pro 0813
LMArena Text: legal and government	1459	1431	DeepSeek V4 Pro 0813
LMArena Text: business and finance	1442	1423	DeepSeek V4 Pro 0813
FACTS Benchmark Suite	Not measured	53.5%	Only Gemini 3.5 Flash Lite measured
Neither model has a result on the other 6 boards here

Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared

Web design benchmarks for DeepSeek V4 Pro 0813 and Gemini 3.5 Flash Lite
Benchmark	DeepSeek V4 Pro 0813	Gemini 3.5 Flash Lite	Leader
Neither model has a result on 9 boards here

GeneralLike-for-likePublic boards, shown as published, kept out of the index162

General benchmarks for DeepSeek V4 Pro 0813 and Gemini 3.5 Flash Lite
Benchmark	DeepSeek V4 Pro 0813	Gemini 3.5 Flash Lite	Leader
Vals Index	53.0%	Not measured	Only DeepSeek V4 Pro 0813 measured
Public Benefits Bench (Vals AI)	Not measured	51.8%	Only Gemini 3.5 Flash Lite measured
SAGE (Vals AI)	Not measured	47.3%	Only Gemini 3.5 Flash Lite measured
MedScribe (Vals AI)	80.2%	70.9%	DeepSeek V4 Pro 0813
Long context reasoning (AA-LCR)	80.3%	76.0%	DeepSeek V4 Pro 0813
DTBench	93.9%	83.5%	DeepSeek V4 Pro 0813
LMCA	45.5%	37.6%	DeepSeek V4 Pro 0813
LMArena Text	1446	1435	DeepSeek V4 Pro 0813
LMArena Text: instruction following	1448	1419	DeepSeek V4 Pro 0813
LMArena Text: creative writing	1439	1421	DeepSeek V4 Pro 0813
LMArena Vision	Not measured	1269	Only Gemini 3.5 Flash Lite measured
LMArena Text: English	1457	1438	DeepSeek V4 Pro 0813
LMArena Text: non-English	1431	1427	DeepSeek V4 Pro 0813
LMArena Text: Chinese	1481	1468	DeepSeek V4 Pro 0813
LMArena Text: German	Not measured	1454	Only Gemini 3.5 Flash Lite measured
LMArena Text: Japanese	Not measured	1426	Only Gemini 3.5 Flash Lite measured
LMArena Text: Korean	1449	1407	DeepSeek V4 Pro 0813
LMArena Text: French	1446	1451	Gemini 3.5 Flash Lite
LMArena Text: Spanish	1435	1441	Gemini 3.5 Flash Lite
LMArena Text: Russian	1448	1443	DeepSeek V4 Pro 0813
LMArena Text: Polish	Not measured	1437	Only Gemini 3.5 Flash Lite measured
LMArena Text: multi-turn	1454	1445	DeepSeek V4 Pro 0813
LMArena Text: longer queries	1458	1435	DeepSeek V4 Pro 0813
LMArena Text: writing and language	1443	1428	DeepSeek V4 Pro 0813
LMArena Text: entertainment and media	1424	1414	DeepSeek V4 Pro 0813
LMArena Vision: English	Not measured	1269	Only Gemini 3.5 Flash Lite measured
LMArena Vision: Chinese	Not measured	1311	Only Gemini 3.5 Flash Lite measured
LMArena Vision: reading text	Not measured	1280	Only Gemini 3.5 Flash Lite measured
LMArena Vision: humor	Not measured	1287	Only Gemini 3.5 Flash Lite measured
LMArena Vision: creative writing	Not measured	1260	Only Gemini 3.5 Flash Lite measured
Neither model has a result on the other 16 boards here

Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared

Image generation benchmarks for DeepSeek V4 Pro 0813 and Gemini 3.5 Flash Lite
Benchmark	DeepSeek V4 Pro 0813	Gemini 3.5 Flash Lite	Leader
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 Pro 0813$0.0016Fits in one request

Gemini 3.5 Flash Lite$0.0015Fits in one request

Gemini 3.5 Flash Lite costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Pro 0813$0.039Fits in one request

Gemini 3.5 Flash Lite$0.022Fits in one request

Gemini 3.5 Flash Lite costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Pro 0813$0.152Fits in one request

Gemini 3.5 Flash Lite$0.085Fits in one request

Gemini 3.5 Flash Lite 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 Pro 0813 and Gemini 3.5 Flash Lite
Specification	DeepSeek V4 Pro 0813	Google Gemini 3.5 Flash Lite
Maker	DeepSeek	Google
Weights	Open weights	No public weights listed
Released	August 12, 2026	July 21, 2026
Context window	1.05M	1.05M
Input $/Mtok	$0.66	$0.30
Output $/Mtok	$1.98	$2.50
Coding index	56.1	49.0
Independent measurements behind it	5	3
Cost per solved task	$0.10	$0.41
Source	OpenRouter listing	OpenRouter listing

Questions

Is DeepSeek V4 Pro 0813 better than Gemini 3.5 Flash Lite for coding?

Pick DeepSeek V4 Pro 0813 for coding: it scores 56.1 on the Vibe Coding Index against 49.0 for Gemini 3.5 Flash Lite. Pick Gemini 3.5 Flash Lite for work measured by LegalBench (Vals AI) or MedCode (Vals AI), where it leads.

Which is cheaper, DeepSeek V4 Pro 0813 or Gemini 3.5 Flash Lite?

DeepSeek V4 Pro 0813 costs $0.66 per million input tokens and $1.98 per million output tokens; Gemini 3.5 Flash Lite costs $0.30 and $2.50. Per solved SWE-bench Verified task, DeepSeek V4 Pro 0813 costs $0.10 and Gemini 3.5 Flash Lite $0.41.

Which has the bigger context window, DeepSeek V4 Pro 0813 or Gemini 3.5 Flash Lite?

Neither: both take 1.05M tokens.

How many benchmarks is the DeepSeek V4 Pro 0813 vs Gemini 3.5 Flash Lite comparison based on?

67 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Pro 0813's coding index rests on 5 independent benchmarks and Gemini 3.5 Flash Lite's on 3. Where only one model has a result, the page says so instead of naming a winner.

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DeepSeek V4 Pro 0813 or Gemini 3.5 Flash Lite: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Knowledge

General

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

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