DeepSeek V4.1 Flash 1017 vs Kimi K2.7 Code

DeepSeek V4.1 Flash 1017 leads llmrun Score 134.4 to 118.1; neither fits 24 GB.

Run DeepSeek V4.1 Flash 1017 in the cloud →

Model A · DeepSeek

DeepSeek V4.1 Flash 1017

134.4llmrun Score

763.2B · 16B active · 1M context · MIT · Oct 2026

Vision

Model B · Moonshot AI

Kimi K2.7 Code

118.1llmrun Score

1026.9B · 33.3B active · 256K context · Other · Jun 2026

VisionCodeFunctions

Which should you choose?

Choose DeepSeek V4.1 Flash 1017 if you want…

Higher llmrun Score
134.4 vs 118.1
Stronger at reasoning
137.1 vs 115.3
Stronger at coding
135.1 vs 114.8
Ahead on the benchmarks
10 of 10 shared boards
Lighter on memory
458.3 vs 620.0 GB at Q4_K_M
Longer context window
1M vs 256K tokens

Choose Kimi K2.7 Code if you want…

Also does code, function-calling
DeepSeek V4.1 Flash 1017 doesn't list it

On your hardware

Each model at its default quant (Q4_K_M), a smaller one when it must. Estimates, ±20%.

MemoryDeepSeek V4.1 Flash 1017Kimi K2.7 Code

8 GB

RTX 4060 · 8 GB tier

DeepSeek V4.1 Flash 1017

Doesn't fit

smallest quant needs 210.4 GB

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

12 GB

RTX 3060 12GB · 12 GB tier

DeepSeek V4.1 Flash 1017

Doesn't fit

smallest quant needs 210.4 GB

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

16 GB

RTX 5060 Ti 16GB · 16 GB tier

DeepSeek V4.1 Flash 1017

Doesn't fit

smallest quant needs 210.4 GB

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

24 GBreference

RTX 4090 · 24 GB tier

DeepSeek V4.1 Flash 1017

Doesn't fit

smallest quant needs 210.4 GB

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

32 GB

RTX 5090 · 32 GB tier

DeepSeek V4.1 Flash 1017

Doesn't fit

smallest quant needs 210.4 GB

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

48 GB

RTX A6000 · 48 GB tier

DeepSeek V4.1 Flash 1017

Doesn't fit

smallest quant needs 210.4 GB

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

Mac 32 GB

Mac Mini M4 · Macs

DeepSeek V4.1 Flash 1017

Doesn't fit

smallest quant needs 210.4 GB

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

Mac 64 GB

Mac Studio M4 Max · Macs

DeepSeek V4.1 Flash 1017

Doesn't fit

smallest quant needs 210.4 GB

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

Mac 128 GB

Mac Studio M4 Max · Macs

DeepSeek V4.1 Flash 1017

Doesn't fit

smallest quant needs 210.4 GB

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

Reference GPU: RTX 4090. Tinted cell = the better pick on that machine (fits, more headroom, or at least 10% faster).

llmrun Score

with its 90% range · bars share one scale

DeepSeek V4.1 Flash 1017 Kimi K2.7 Code

Overall

DeepSeek V4.1 Flash 1017

134.4132–137

Kimi K2.7 Code

118.1115–121

Coding

DeepSeek V4.1 Flash 1017

135.1127–143

Kimi K2.7 Code

114.8110–120

Agents

DeepSeek V4.1 Flash 1017

135.7131–141

Kimi K2.7 Code

118.7112–125

Math

DeepSeek V4.1 Flash 1017

132.0129–135

Kimi K2.7 Code

120.7116–125

Science

DeepSeek V4.1 Flash 1017

134.3123–146

Kimi K2.7 Code

117.6107–129

Reasoning

DeepSeek V4.1 Flash 1017

137.1133–142

Kimi K2.7 Code

115.3106–125

DeepSeek V4.1 Flash 1017 · #2 of 106 open models · #1 of 102 that fit ≤512 GB

Kimi K2.7 Code · #19 of 106 open models · #16 of 102 that fit ≤640 GB

Benchmarks

10 shared boards: DeepSeek V4.1 Flash 1017 leads 10, Kimi K2.7 Code leads 0 · Benchmarks imported Nov 2026

BoardDeepSeek V4.1 Flash 1017Kimi K2.7 Code

GPQA Diamond

DeepSeek V4.1 Flash 1017

93.2%#1/100 open

IndependentEpoch AI · Oct 2026

Kimi K2.7 Code

87.9%#17/100 open

IndependentEpoch AI · Jun 2026

AIME 2024/2025

DeepSeek V4.1 Flash 1017

99.4%#1/88 open

IndependentEpoch AI · Oct 2026

Kimi K2.7 Code

95.6%#9/88 open

IndependentEpoch AI · Jun 2026

FrontierMath

DeepSeek V4.1 Flash 1017

71.2%#2/19 open

IndependentEpoch AI · Oct 2026

Kimi K2.7 Code

54.0%#12/19 open

IndependentEpoch AI · Jun 2026

SciCode

DeepSeek V4.1 Flash 1017

55.9%#7/72 open

Lab-reportedEpoch AI · Oct 2026

Kimi K2.7 Code

47.8%#21/72 open

Lab-reportedEpoch AI · Jun 2026

SimpleQA

DeepSeek V4.1 Flash 1017

42.5%#6/19 open

IndependentEpoch AI · Oct 2026

Kimi K2.7 Code

36.5%#10/19 open

IndependentEpoch AI · Jun 2026

FrontierMath Tier 4

DeepSeek V4.1 Flash 1017

46.3%#1/15 open

IndependentEpoch AI · Oct 2026

Kimi K2.7 Code

12.2%#13/15 open

IndependentEpoch AI · Jun 2026

ALE-Bench

DeepSeek V4.1 Flash 1017

1622.0#2/48 open

Lab-reportedEpoch AI · Oct 2026

Kimi K2.7 Code

886.2#20/48 open

Lab-reportedEpoch AI · Jun 2026

APEX-Agents

DeepSeek V4.1 Flash 1017

69.8%#1/20 open

Lab-reportedEpoch AI · Oct 2026

Kimi K2.7 Code

37.6%#14/20 open

Lab-reportedEpoch AI · Jun 2026

Chess Puzzles

DeepSeek V4.1 Flash 1017

46.0%#2/16 open

IndependentEpoch AI · Oct 2026

Kimi K2.7 Code

14.0%#16/16 open

IndependentEpoch AI · Jun 2026

CritPt

DeepSeek V4.1 Flash 1017

24.0%#3/84 open

Lab-reportedEpoch AI · Oct 2026

Kimi K2.7 Code

10.0%#16/84 open

Lab-reportedEpoch AI · Jun 2026

23 more boards (other shared and single-model boards)

LMArena WebDev

DeepSeek V4.1 Flash 1017

1665.0#1/55 open

ArenaLMArena · Oct 2026

Kimi K2.7 Code

1473.5#21/55 open

ArenaLMArena · Oct 2026

Only DeepSeek V4.1 Flash 1017 (12)

Only Kimi K2.7 Code (10)

VRAM by quantization

Memory to load the model and 2K context; below it, the total at 32K and 128K context. Lighter side in bold.

QuantDeepSeek V4.1 Flash 1017Kimi K2.7 Code

Q2_K

DeepSeek V4.1 Flash 1017

325 GB264.5 GB file

32K 325 GB · 128K 326 GB

Kimi K2.7 Code

440 GB~436.4 GB file

32K 439 GB · 128K 446 GB

Q3_K_M

DeepSeek V4.1 Flash 1017

372 GB347.3 GB file

32K 373 GB · 128K 374 GB

Kimi K2.7 Code

504 GB463.6 GB file

32K 503 GB · 128K 510 GB

Q4_K_M

DeepSeek V4.1 Flash 1017

458 GB444.7 GB file

32K 459 GB · 128K 460 GB

Kimi K2.7 Code

620 GB~616.1 GB file

32K 619 GB · 128K 626 GB

Q5_K_M

DeepSeek V4.1 Flash 1017

544 GB~543.8 GB file

32K 545 GB · 128K 546 GB

Kimi K2.7 Code

736 GB~731.6 GB file

32K 734 GB · 128K 741 GB

Q6_K

DeepSeek V4.1 Flash 1017

630 GB~629.6 GB file

32K 630 GB · 128K 632 GB

Kimi K2.7 Code

851 GB~847.2 GB file

32K 850 GB · 128K 857 GB

Q8_0

DeepSeek V4.1 Flash 1017

764 GB~763.2 GB file

32K 764 GB · 128K 765 GB

Kimi K2.7 Code

1031 GB~1026.9 GB file

32K 1029 GB · 128K 1036 GB

9 more quants

IQ2_XXS

DeepSeek V4.1 Flash 1017

210 GB300.5 GB file

32K 211 GB · 128K 212 GB

Kimi K2.7 Code

286 GB317.8 GB file

32K 285 GB · 128K 292 GB

IQ2_XS

DeepSeek V4.1 Flash 1017

229 GB~229.0 GB file

32K 230 GB · 128K 231 GB

Kimi K2.7 Code

not listed

IQ2_S

DeepSeek V4.1 Flash 1017

not listed

Kimi K2.7 Code

325 GB334.8 GB file

32K 324 GB · 128K 330 GB

IQ2_M

DeepSeek V4.1 Flash 1017

not listed

Kimi K2.7 Code

350 GB318.0 GB file

32K 349 GB · 128K 356 GB

IQ3_XXS

DeepSeek V4.1 Flash 1017

296 GB394.7 GB file

32K 296 GB · 128K 298 GB

Kimi K2.7 Code

402 GB376.9 GB file

32K 401 GB · 128K 407 GB

IQ3_S

DeepSeek V4.1 Flash 1017

325 GB423.6 GB file

32K 325 GB · 128K 326 GB

Kimi K2.7 Code

440 GB418.8 GB file

32K 439 GB · 128K 446 GB

Q3_K_L

DeepSeek V4.1 Flash 1017

not listed

Kimi K2.7 Code

530 GB493.9 GB file

32K 529 GB · 128K 536 GB

IQ4_XS

DeepSeek V4.1 Flash 1017

not listed

Kimi K2.7 Code

556 GB495.1 GB file

32K 555 GB · 128K 561 GB

BF16

DeepSeek V4.1 Flash 1017

1527 GB~1526.4 GB file

32K 1527 GB · 128K 1528 GB

Kimi K2.7 Code

2058 GB~2053.8 GB file

32K 2056 GB · 128K 2063 GB

How to run each

DeepSeek V4.1 Flash 1017

Ollama · Q4_K_M

$ollama run hf.co/mrfakename/DeepSeek-V4.1-Flash-1017-GGUF:Q4_K_M

All ways to run DeepSeek V4.1 Flash 1017 →

Kimi K2.7 Code

Ollama · Q4_K_M

$ollama run hf.co/unsloth/Kimi-K2.7-Code-GGUF

All ways to run Kimi K2.7 Code →

Specifications

Specifications of DeepSeek V4.1 Flash 1017 and Kimi K2.7 Code
Spec	DeepSeek V4.1 Flash 1017	Kimi K2.7 Code
Publisher	DeepSeek	Moonshot AI
Parameters	763.2B	1026.9B
Active parameters	16B per token	33B per token
Architecture	DeepseekV41ForCausalLM	KimiK25ForConditionalGeneration
Context	1M tokens	256K tokens
Modalities	Vision	Vision, Code, Function-calling
License	MIT	Other
Released	Oct 2026	Jun 2026

Frequently Asked Questions

Which is better, DeepSeek V4.1 Flash 1017 or Kimi K2.7 Code?

DeepSeek V4.1 Flash 1017 leads llmrun Score 134.4 to 118.1; neither fits 24 GB. Choose DeepSeek V4.1 Flash 1017 for higher llmrun Score and stronger at reasoning; choose Kimi K2.7 Code for also does code, function-calling.

Which needs less VRAM, DeepSeek V4.1 Flash 1017 or Kimi K2.7 Code?

At Q4_K_M, DeepSeek V4.1 Flash 1017 requires 458.3 GB while Kimi K2.7 Code needs 620.0 GB, making DeepSeek V4.1 Flash 1017 the easier model to run on your local setup.

Can I run DeepSeek V4.1 Flash 1017 or Kimi K2.7 Code on a 16 GB GPU?

DeepSeek V4.1 Flash 1017 does not fit (smallest quant needs 210.4 GB); Kimi K2.7 Code does not fit (smallest quant needs 283.8 GB).

Which has a longer context window, DeepSeek V4.1 Flash 1017 or Kimi K2.7 Code?

DeepSeek V4.1 Flash 1017 supports 1,048,576 tokens and Kimi K2.7 Code supports 262,144 tokens.