LLMBenchmark.ai

Enter opens the highlighted result. Esc closes.

DeepSeek V4.1 Flash 1017 vs Kimi K2 0711

Updated October 21, 2026. 8 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

DeepSeek V4.1 Flash 1017DeepSeek
Coding
83.3
Overall
39.5
Output $/M
$0.60
8
Kimi K2 0711Moonshot AI
Coding
64.7
Overall
12.7
Output $/M
$2.30
0
vs boards won of 8 shared

Decision reading

DeepSeek V4.1 Flash 1017 scores 83.3 and Kimi K2 0711 64.7 on the Vibe Coding Index, but no coding benchmark measured both, so the gap is directional, not a ranking.

Pick DeepSeek V4.1 Flash 1017 when output tokens cost 3.8x less, or when the context window is larger, 1.05M against 131K tokens.

Shared results
8
DeepSeek V4.1 Flash 1017 only
24
Kimi K2 0711 only
28
Like-for-like categories
4 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 V4.1 Flash 1017 83.3 from 2 benchmarks, Kimi K2 0711 64.7 from 2 benchmarks.
Widest category
Web design, 38.5 points apart on average over 5 shared benchmarks.
Widest single gap
Design Arena: game dev: DeepSeek V4.1 Flash 1017 1365 against Kimi K2 0711 974, 48.9 points apart on a 0 to 100 scale.
Output price
DeepSeek V4.1 Flash 1017 $0.60 against Kimi K2 0711 $2.30 per million output tokens, 3.8x apart.
Context window
DeepSeek V4.1 Flash 1017 takes 1.05M tokens, Kimi K2 0711 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 V4.1 Flash 1017BarsKimi K2 0711Ties
Intelligence10
Reasoning10
Web design50
General10
All shared boards80
CodingDirectional onlyFour of these boards feed the Vibe Coding Index17 boards, none shared
Coding benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K2 0711
BenchmarkDeepSeek V4.1 Flash 1017Kimi K2 0711Leader
Aider polyglotNot measured59.1%Only Kimi K2 0711 measured
SWE-bench VerifiedNot measured71.2%Only Kimi K2 0711 measured
LiveBench coding96.0%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LMArena WebDev1664Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveCodeBench (Vals AI)Not measured70.5%Only Kimi K2 0711 measured
Terminal-Bench 4 (Vals AI)31.8%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Vibe Code Bench (Vals AI)87.7%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Code migration (Vals AI)44.2%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveCodeBench (Artificial Analysis run)Not measured55.6%Only Kimi K2 0711 measured
SciCode55.9%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured15.9%Only Kimi K2 0711 measured
Terminal-BenchNot measured27.8%Only Kimi K2 0711 measured
GSO-BenchNot measured4.9%Only Kimi K2 0711 measured
WeirdMLNot measured39.4%Only Kimi K2 0711 measured
ALE-Bench1622.0Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LMArena WebDev: React1667Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LMArena WebDev: HTML1687Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Neither model has a result on the other 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K2 0711
BenchmarkDeepSeek V4.1 Flash 1017Kimi K2 0711Leader
AA Intelligence Index39.512.7DeepSeek V4.1 Flash 1017
Epoch Capabilities IndexNot measured140.0Only Kimi K2 0711 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Agentic work benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K2 0711
BenchmarkDeepSeek V4.1 Flash 1017Kimi K2 0711Leader
Design Arena: spreadsheets1238Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench research79.5%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench browser76.0%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench long agentic50.9%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Finance Agent (Vals AI)57.0%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Tax Agent Bench (Vals AI)44.4%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Legal Research Bench (Vals AI)45.2%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Harvey's Legal Agent Benchmark (Vals AI)14.2%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Excel Modeling Benchmark (Vals AI)61.8%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
τ²-Bench TelecomNot measured61.1%Only Kimi K2 0711 measured
Neither model has a result on the other 29 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
Reasoning benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K2 0711
BenchmarkDeepSeek V4.1 Flash 1017Kimi K2 0711Leader
GPQA DiamondNot measured71.5%Only Kimi K2 0711 measured
LiveBench reasoning89.1%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
GPQA Diamond (Artificial Analysis run)Not measured76.6%Only Kimi K2 0711 measured
Humanity's Last Exam (Artificial Analysis run)43.3%7.4%DeepSeek V4.1 Flash 1017
SimpleBenchNot measured26.3%Only Kimi K2 0711 measured
Neither model has a result on the other 16 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K2 0711
BenchmarkDeepSeek V4.1 Flash 1017Kimi K2 0711Leader
AIMENot measured62.7%Only Kimi K2 0711 measured
MATH 500 (Vals AI)Not measured94.2%Only Kimi K2 0711 measured
MGSM (Vals AI)Not measured91.0%Only Kimi K2 0711 measured
AA Math IndexNot measured57.0Only Kimi K2 0711 measured
AIME 2025 (Artificial Analysis run)Not measured57.0%Only Kimi K2 0711 measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Knowledge benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K2 0711
BenchmarkDeepSeek V4.1 Flash 1017Kimi K2 0711Leader
MMLU ProNot measured79.4%Only Kimi K2 0711 measured
LegalBench (Vals AI)Not measured81.5%Only Kimi K2 0711 measured
CorpFin (Vals AI)Not measured50.4%Only Kimi K2 0711 measured
TaxEval (Vals AI)Not measured70.2%Only Kimi K2 0711 measured
MedQA (Vals AI)Not measured84.0%Only Kimi K2 0711 measured
MMLU Pro (Artificial Analysis run)Not measured82.4%Only Kimi K2 0711 measured
Neither model has a result on the other 11 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index50
Web design benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K2 0711
BenchmarkDeepSeek V4.1 Flash 1017Kimi K2 0711Leader
Design Arena: websites13121050DeepSeek V4.1 Flash 1017
Design Arena: UI components13051030DeepSeek V4.1 Flash 1017
Design Arena: game dev1365974DeepSeek V4.1 Flash 1017
Design Arena: data viz13301018DeepSeek V4.1 Flash 1017
Design Arena: 3D1368Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Design Arena: all code categories13351034DeepSeek V4.1 Flash 1017
Design Arena: ASCII art1244Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench design83.4%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
General benchmarks for DeepSeek V4.1 Flash 1017 and Kimi K2 0711
BenchmarkDeepSeek V4.1 Flash 1017Kimi K2 0711Leader
Vals Index61.3%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
LiveBench data analysis79.5%Not measuredOnly DeepSeek V4.1 Flash 1017 measured
IFBenchNot measured41.5%Only Kimi K2 0711 measured
Long context reasoning (AA-LCR)82.7%53.0%DeepSeek V4.1 Flash 1017
Fiction.LiveBenchNot measured61.1%Only Kimi K2 0711 measured
Creative writing (Lech Mazur)Not measured85.6%Only Kimi K2 0711 measured
CL-benchNot measured11.9%Only Kimi K2 0711 measured
Neither model has a result on the other 39 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 K2 0711
BenchmarkDeepSeek V4.1 Flash 1017Kimi K2 0711Leader
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 K2 0711$0.0017Fits 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 K2 0711$0.035Fits 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 K2 0711$0.137Exceeds the context window

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 K2 0711
SpecificationDeepSeek V4.1 Flash 1017MoonshotAI Kimi K2 0711
MakerDeepSeekMoonshot AI
WeightsOpen weightsOpen weights
ReleasedOctober 17, 2026July 11, 2025
Context window1.05M131K
Input $/Mtok$0.15$0.57
Output $/Mtok$0.60$2.30
Coding index83.364.7
Independent measurements behind it22
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4.1 Flash 1017 better than Kimi K2 0711 for coding?

DeepSeek V4.1 Flash 1017 scores 83.3 and Kimi K2 0711 64.7 on the Vibe Coding Index, but no coding benchmark measured both, so the gap is directional, not a ranking. Pick DeepSeek V4.1 Flash 1017 when output tokens cost 3.8x less, or when the context window is larger, 1.05M against 131K tokens.

Which is cheaper, DeepSeek V4.1 Flash 1017 or Kimi K2 0711?

DeepSeek V4.1 Flash 1017 costs $0.15 per million input tokens and $0.60 per million output tokens; Kimi K2 0711 costs $0.57 and $2.30. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V4.1 Flash 1017 or Kimi K2 0711?

DeepSeek V4.1 Flash 1017, with 1.05M tokens against 131K.

How many benchmarks is the DeepSeek V4.1 Flash 1017 vs Kimi K2 0711 comparison based on?

8 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4.1 Flash 1017's coding index rests on 2 independent benchmarks and Kimi K2 0711's on 2. Where only one model has a result, the page says so instead of naming a winner.

Compare next

Embed this comparison on your site

Free under CC BY 4.0, while the source link stays visible. Preview the frame · Terms and other embeds

<iframe src="https://llmbenchmark.ai/embed/compare/deepseek-v4-1-flash-1017-vs-kimi-k2" title="DeepSeek V4.1 Flash 1017 vs Kimi K2 0711, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/deepseek-v4-1-flash-1017-vs-kimi-k2">LLMBenchmark.ai, DeepSeek V4.1 Flash 1017 vs Kimi K2 0711</a></p>