DeepSeek V4.1 Flash 1017 vs Kimi K3.1 Pro

Kimi K3.1 Pro leads DeepSeek V4.1 Flash 1017 on coding, 82.2 to 70.3 on the Vibe Coding Index, and DeepSeek V4.1 Flash 1017 costs 16.7x less per output token ($0.60 vs $10.00 per million). Updated October 29, 2026; 28 benchmarks have a result for both.

Replace DeepSeek V4.1 Flash 1017 Replace Kimi K3.1 Pro

DeepSeek V4.1 Flash 1017DeepSeek

Coding: 70.3
Overall: 68.6
Output $/M: $0.60

Kimi K3.1 ProMoonshot AI

Coding: 82.2
Overall: 74.4
Output $/M: $10.00

vs boards won of 28 shared

DeepSeek V4.1 Flash 1017 or Kimi K3.1 Pro: which to pick

Pick Kimi K3.1 Pro for coding: it scores 82.2 on the Vibe Coding Index against 70.3 for DeepSeek V4.1 Flash 1017.

Pick DeepSeek V4.1 Flash 1017 for output tokens 16.7x cheaper ($0.60 vs $10.00 per million) and work measured by LiveBench coding or Vibe Code Bench (Vals AI), where it leads.

Model ADeepSeek V4.1 Flash 1017DeepSeek70.3/1004 independent benchmarksNo cost per solved task Model BKimi K3.1 ProMoonshot AI82.2/1004 independent benchmarksNo cost per solved task

28197

Shared results: 28
DeepSeek V4.1 Flash 1017 only: 19
Kimi K3.1 Pro only: 7
Like-for-like categories: 6 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
Kimi K3.1 Pro
Kimi K3.1 Pro scores 82.2 against 70.3.
4 benchmarks behind each score
Intelligence
AA Intelligence Index
No call
Only Kimi K3.1 Pro has a AA Intelligence Index result, 46.0.
Directional only
Web design
Design Arena: websites
Kimi K3.1 Pro
Kimi K3.1 Pro leads, 1325 against 1302.
Same board, both measured
General
Vals Index
Kimi K3.1 Pro
Kimi K3.1 Pro leads, 62.5% against 61.3%.
Same board, both measured
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 $0.0004, Kimi K3.1 Pro $0.0070 per turn.
List prices

At a glance

Coding index: DeepSeek V4.1 Flash 1017 70.3 from 4 benchmarks, Kimi K3.1 Pro 82.2 from 4 benchmarks.
Widest category: Coding, 9.9 points apart on average over 8 shared benchmarks.
Widest single gap: Terminal-Bench 4 (Vals AI): DeepSeek V4.1 Flash 1017 31.8% against Kimi K3.1 Pro 63.6%, 42.4 points apart on a 0 to 100 scale.
Output price: DeepSeek V4.1 Flash 1017 $0.60 against Kimi K3.1 Pro $10.00 per million output tokens, 16.7x 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 V4.1 Flash 1017	Kimi K3.1 Pro
Coding	2	6
Agentic work	5	1
Reasoning	0	2
Math	0	1
Web design	1	7
General	1	2
All shared boards	9	19

CodingLike-for-likeSix of these boards feed the Vibe Coding Index26

Coding benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K3.1 Pro
Benchmark	DeepSeek V4.1 Flash 1017	Kimi K3.1 Pro	Leader
LiveBench coding	96.0%	81.8%	DeepSeek V4.1 Flash 1017
LMArena WebDev	1665	1695	Kimi K3.1 Pro
Terminal-Bench 4 (Vals AI)	31.8%	63.6%	Kimi K3.1 Pro
Vibe Code Bench (Vals AI)	87.7%	84.9%	DeepSeek V4.1 Flash 1017
Code migration (Vals AI)	44.2%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
IOI (Vals AI)	Not measured	81.9%	Only Kimi K3.1 Pro measured
SciCode	55.9%	60.8%	Kimi K3.1 Pro
ALE-Bench	1622.0	1932.8	Kimi K3.1 Pro
LMArena WebDev: React	1673	1701	Kimi K3.1 Pro
LMArena WebDev: HTML	1701	1706	Kimi K3.1 Pro
Neither model has a result on the other 33 boards here

IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared

Intelligence benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K3.1 Pro
Benchmark	DeepSeek V4.1 Flash 1017	Kimi K3.1 Pro	Leader
AA Intelligence Index	Not measured	46.0	Only Kimi K3.1 Pro measured
Neither model has a result on the other 1 board here

Agentic workLike-for-likePublic boards, shown as published, kept out of the index51

Agentic work benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K3.1 Pro
Benchmark	DeepSeek V4.1 Flash 1017	Kimi K3.1 Pro	Leader
Design Arena: spreadsheets	1280	Not measured	Only DeepSeek V4.1 Flash 1017 measured
LiveBench research	79.5%	77.9%	DeepSeek V4.1 Flash 1017
LiveBench browser	67.2%	75.9%	Kimi K3.1 Pro
LiveBench long agentic	40.9%	39.1%	DeepSeek V4.1 Flash 1017
Finance Agent (Vals AI)	57.0%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
Tax Agent Bench (Vals AI)	44.4%	24.9%	DeepSeek V4.1 Flash 1017
Legal Research Bench (Vals AI)	45.2%	37.5%	DeepSeek V4.1 Flash 1017
Harvey's Legal Agent Benchmark (Vals AI)	14.2%	11.7%	DeepSeek V4.1 Flash 1017
Excel Modeling Benchmark (Vals AI)	61.8%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
BioMysteryBench (Vals AI)	Not measured	75.6%	Only Kimi K3.1 Pro measured
Terminal-Bench-Science (Vals AI)	Not measured	31.4%	Only Kimi K3.1 Pro measured
Vals Science Index	Not measured	44.4%	Only Kimi K3.1 Pro measured
APEX-Agents	69.8%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
Neither model has a result on the other 29 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index02

Reasoning benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K3.1 Pro
Benchmark	DeepSeek V4.1 Flash 1017	Kimi K3.1 Pro	Leader
LiveBench reasoning	89.1%	91.1%	Kimi K3.1 Pro
MysteryMechanism (Vals AI)	Not measured	26.1%	Only Kimi K3.1 Pro measured
Humanity's Last Exam (Artificial Analysis run)	43.3%	52.5%	Kimi K3.1 Pro
GPQA Diamond (Epoch AI run)	93.2%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
ARC-AGI	94.5%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
ARC-AGI-2	78.1%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
Chess puzzles	46.0%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
Mystery game puzzles	49.0%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
Humanity's Last Exam (Scale run)	20.5%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
Neither model has a result on the other 14 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index01

Math benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K3.1 Pro
Benchmark	DeepSeek V4.1 Flash 1017	Kimi K3.1 Pro	Leader
OTIS Mock AIME	99.4%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
FrontierMath, tiers 1 to 3	71.2%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
FrontierMath, tier 4	46.3%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
ProofBench	Not measured	91.0%	Only Kimi K3.1 Pro measured
MathArena	51.6%	59.6%	Kimi K3.1 Pro
Neither model has a result on the other 9 boards here

KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared

Knowledge benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K3.1 Pro
Benchmark	DeepSeek V4.1 Flash 1017	Kimi K3.1 Pro	Leader
SimpleQA Verified	42.5%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
PRBench Finance	47.1%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
PRBench Legal	47.3%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
Neither model has a result on the other 17 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index17

Web design benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K3.1 Pro
Benchmark	DeepSeek V4.1 Flash 1017	Kimi K3.1 Pro	Leader
Design Arena: websites	1302	1325	Kimi K3.1 Pro
Design Arena: UI components	1302	1400	Kimi K3.1 Pro
Design Arena: game dev	1259	1410	Kimi K3.1 Pro
Design Arena: data viz	1263	1300	Kimi K3.1 Pro
Design Arena: 3D	1360	1451	Kimi K3.1 Pro
Design Arena: all code categories	1289	1354	Kimi K3.1 Pro
Design Arena: SVG	1245	1328	Kimi K3.1 Pro
Design Arena: ASCII art	1229	Not measured	Only DeepSeek V4.1 Flash 1017 measured
LiveBench design	83.4%	77.8%	DeepSeek V4.1 Flash 1017

GeneralLike-for-likePublic boards, shown as published, kept out of the index12

General benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K3.1 Pro
Benchmark	DeepSeek V4.1 Flash 1017	Kimi K3.1 Pro	Leader
Vals Index	61.3%	62.5%	Kimi K3.1 Pro
LiveBench data analysis	79.5%	79.1%	DeepSeek V4.1 Flash 1017
Long context reasoning (AA-LCR)	82.7%	86.3%	Kimi K3.1 Pro
MultiChallenge	74.9%	Not measured	Only DeepSeek V4.1 Flash 1017 measured
Neither model has a result on the other 44 boards here

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

Image generation benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K3.1 Pro
Benchmark	DeepSeek V4.1 Flash 1017	Kimi K3.1 Pro	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 V4.1 Flash 1017$0.0004Fits in one request

Kimi K3.1 Pro$0.0070Fits in one request

DeepSeek V4.1 Flash 1017 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4.1 Flash 1017$0.0093Fits in one request

Kimi K3.1 Pro$0.130Fits in one request

DeepSeek V4.1 Flash 1017 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4.1 Flash 1017$0.036Fits in one request

Kimi K3.1 Pro$0.500Fits in one request

DeepSeek V4.1 Flash 1017 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 V4.1 Flash 1017 and Kimi K3.1 Pro
Specification	DeepSeek V4.1 Flash 1017	MoonshotAI Kimi K3.1 Pro
Maker	DeepSeek	Moonshot AI
Weights	Open weights	No public weights listed
Released	October 17, 2026	October 23, 2026
Context window	1.05M	1.05M
Input $/Mtok	$0.15	$2.00
Output $/Mtok	$0.60	$10.00
Coding index	70.3	82.2
Independent measurements behind it	4	4
Cost per solved task	Not computable	Not computable
Source	OpenRouter listing	OpenRouter listing

Questions

Is DeepSeek V4.1 Flash 1017 better than Kimi K3.1 Pro for coding?

Pick Kimi K3.1 Pro for coding: it scores 82.2 on the Vibe Coding Index against 70.3 for DeepSeek V4.1 Flash 1017. Pick DeepSeek V4.1 Flash 1017 for output tokens 16.7x cheaper ($0.60 vs $10.00 per million) and work measured by LiveBench coding or Vibe Code Bench (Vals AI), where it leads.

Which is cheaper, DeepSeek V4.1 Flash 1017 or Kimi K3.1 Pro?

DeepSeek V4.1 Flash 1017 costs $0.15 per million input tokens and $0.60 per million output tokens; Kimi K3.1 Pro costs $2.00 and $10.00. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V4.1 Flash 1017 or Kimi K3.1 Pro?

Neither: both take 1.05M tokens.

How many benchmarks is the DeepSeek V4.1 Flash 1017 vs Kimi K3.1 Pro comparison based on?

28 benchmarks have a result for both models as of October 29, 2026. DeepSeek V4.1 Flash 1017's coding index rests on 4 independent benchmarks and Kimi K3.1 Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.

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DeepSeek V4.1 Flash 1017 or Kimi K3.1 Pro: which to pick

Which one for your work

Coding

Intelligence

Web design

General

Long documents

Everyday cost

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next