llmrun

Kimi K2.7 Code vs Qwen3.8 27B

Qwen3.8 27B leads llmrun Score 122.1 to 118.1 (ranges overlap); only Qwen3.8 27B fits 24 GB (Q4_K_M); Kimi K2.7 Code needs 283.8 GB even at its smallest quant.

Model A · Moonshot AI

Kimi K2.7 Code
118.1llmrun Score

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

VisionCodeFunctions

Model B · Alibaba

Qwen3.8 27B
122.1llmrun Score

27.8B · 256K context · Apache 2.0 · Aug 2026

VisionFunctions

Which should you choose?

Choose Kimi K2.7 Code if you want…

  • Also does code

    Qwen3.8 27B doesn't list it

Choose Qwen3.8 27B if you want…

  • Higher llmrun Score

    122.1 vs 118.1, ranges overlap

  • Stronger at reasoning

    124.0 vs 115.4

  • Fits a 12 GB GPU

    IQ3_XXS · 12 GB; Kimi K2.7 Code needs 283.8 GB at its smallest quant

  • Fits a Mac 32 GB

    Q4_K_M · 17.9 GB; Kimi K2.7 Code needs 283.8 GB at its smallest quant

  • Lighter on memory

    17.4 vs 620.0 GB at Q4_K_M

  • More permissive license

    Apache 2.0 vs Other

On your hardware

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

8 GB

RTX 4060 · 8 GB tier

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

Qwen3.8 27B

Doesn't fit

smallest quant needs 8.8 GB

12 GB

RTX 3060 12GB · 12 GB tier

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

Qwen3.8 27B

IQ3_XXS · ~20 tok/s

12 GB · up to 16Kfits

16 GB

RTX 5060 Ti 16GB · 16 GB tier

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

Qwen3.8 27B

Q3_K_L · ~19 tok/s

15.4 GB · up to 16Kfits

24 GBreference

RTX 4090 · 24 GB tier

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

Qwen3.8 27B

Q4_K_M · ~38 tok/s

17.9 GB · up to 64Kfits

32 GB

RTX 5090 · 32 GB tier

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

Qwen3.8 27B

Q4_K_M · ~67 tok/s

17.9 GB · up to 256Kfits

48 GB

RTX A6000 · 48 GB tier

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

Qwen3.8 27B

Q4_K_M · ~29 tok/s

17.9 GB · up to 256Kfits

Mac 32 GB

Mac Mini M4 · Macs

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

Qwen3.8 27B

Q4_K_M · ~5 tok/s

17.9 GB · up to 128Kfits

Mac 64 GB

Mac Studio M4 Max · Macs

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256Kfits

Mac 128 GB

Mac Studio M4 Max · Macs

Kimi K2.7 Code

Doesn't fit

smallest quant needs 283.8 GB

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256Kfits

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

Overall

Kimi K2.7 Code

118.1115–121

Qwen3.8 27B

122.1120–124

Coding

Kimi K2.7 Code

114.8110–120

Qwen3.8 27B

119.7114–125

Agents

Kimi K2.7 Code

118.7112–125

Qwen3.8 27B

122.8117–129

Math

Kimi K2.7 Code

120.7116–125

Qwen3.8 27B

117.5111–124

Science

Kimi K2.7 Code

117.7107–128

Qwen3.8 27B

112.093–131

Reasoning

Kimi K2.7 Code

115.4106–125

Qwen3.8 27B

124.0121–127

Kimi K2.7 Code · #14 of 100 open models · #12 of 96 that fit ≤640 GB

Qwen3.8 27B · #11 of 100 open models · #1 of 35 that fit 24 GB

Benchmarks

7 shared boards: Kimi K2.7 Code leads 4, Qwen3.8 27B leads 3 · Benchmarks imported Oct 2026

LiveBench Coding

Kimi K2.7 Code

74.0#11/19 open

IndependentLiveBench · Jun 2026

Qwen3.8 27B

75.7#9/19 open

IndependentLiveBench · Jun 2026

LiveBench Reasoning

Kimi K2.7 Code

82.8#9/19 open

IndependentLiveBench · Jun 2026

Qwen3.8 27B

80.0#11/19 open

IndependentLiveBench · Jun 2026

LiveBench Math

Kimi K2.7 Code

79.6#18/19 open

IndependentLiveBench · Jun 2026

Qwen3.8 27B

86.2#11/19 open

IndependentLiveBench · Jun 2026

SciCode

Kimi K2.7 Code

47.8%#16/66 open

Lab-reportedEpoch AI · Jun 2026

Qwen3.8 27B

46.6%#19/66 open

Lab-reportedEpoch AI · Aug 2026

APEX-Agents

Kimi K2.7 Code

37.6%#11/16 open

Lab-reportedEpoch AI · Jun 2026

Qwen3.8 27B

47.5%#5/16 open

Lab-reportedEpoch AI · Aug 2026

CritPt

Kimi K2.7 Code

10.0%#11/66 open

Lab-reportedEpoch AI · Jun 2026

Qwen3.8 27B

5.4%#15/66 open

Lab-reportedEpoch AI · Aug 2026

Surface Evolver Bench

Kimi K2.7 Code

48.8%#5/13 open

Lab-reportedEpoch AI · Jun 2026

Qwen3.8 27B

45.0%#7/13 open

Lab-reportedEpoch AI · Aug 2026

26 more boards (other shared and single-model boards)
LMArena WebDev

Kimi K2.7 Code

1473.8#19/52 open

ArenaLMArena · Oct 2026

Qwen3.8 27B

1593.2#10/52 open

ArenaLMArena · Oct 2026

VRAM by quantization

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

Q2_K

Kimi K2.7 Code

440 GB~436.4 GB file

32K 439 GB · 128K 446 GB

Qwen3.8 27B

12.6 GB10.8 GB file

32K 13.9 GB · 128K 19.3 GB

Q3_K_S

Kimi K2.7 Code

not listed

Qwen3.8 27B

12.9 GB12.7 GB file

32K 14.2 GB · 128K 19.6 GB

Q3_K_M

Kimi K2.7 Code

504 GB463.6 GB file

32K 503 GB · 128K 510 GB

Qwen3.8 27B

14.3 GB13.4 GB file

32K 15.6 GB · 128K 21.0 GB

Q4_0

Kimi K2.7 Code

not listed

Qwen3.8 27B

14.6 GB~13.9 GB file

32K 16.0 GB · 128K 21.4 GB

Q4_K_M

Kimi K2.7 Code

620 GB~616.1 GB file

32K 619 GB · 128K 626 GB

Qwen3.8 27B

17.4 GB16.5 GB file

32K 18.8 GB · 128K 24.1 GB

Q5_K_M

Kimi K2.7 Code

736 GB~731.6 GB file

32K 734 GB · 128K 741 GB

Qwen3.8 27B

20.5 GB19.8 GB file

32K 21.9 GB · 128K 27.3 GB

Q6_K

Kimi K2.7 Code

851 GB~847.2 GB file

32K 850 GB · 128K 857 GB

Qwen3.8 27B

23.7 GB22.0 GB file

32K 25.0 GB · 128K 30.4 GB

Q8_0

Kimi K2.7 Code

1031 GB~1026.9 GB file

32K 1029 GB · 128K 1036 GB

Qwen3.8 27B

28.5 GB29.0 GB file

32K 29.9 GB · 128K 35.2 GB

17 more quants

IQ2_XXS

Kimi K2.7 Code

286 GB317.8 GB file

32K 285 GB · 128K 292 GB

Qwen3.8 27B

8.4 GB7.3 GB file

32K 9.7 GB · 128K 15.1 GB

IQ2_XS

Kimi K2.7 Code

not listed

Qwen3.8 27B

9.1 GB9.1 GB file

32K 10.4 GB · 128K 15.8 GB

IQ2_S

Kimi K2.7 Code

325 GB334.8 GB file

32K 324 GB · 128K 330 GB

Qwen3.8 27B

9.4 GB8.4 GB file

32K 10.8 GB · 128K 16.1 GB

IQ2_M

Kimi K2.7 Code

350 GB318.0 GB file

32K 349 GB · 128K 356 GB

Qwen3.8 27B

10.1 GB10.5 GB file

32K 11.5 GB · 128K 16.8 GB

IQ3_XXS

Kimi K2.7 Code

402 GB376.9 GB file

32K 401 GB · 128K 407 GB

Qwen3.8 27B

11.5 GB10.9 GB file

32K 12.9 GB · 128K 18.2 GB

IQ3_XS

Kimi K2.7 Code

not listed

Qwen3.8 27B

12.2 GB10.4 GB file

32K 13.6 GB · 128K 18.9 GB

IQ3_S

Kimi K2.7 Code

440 GB418.8 GB file

32K 439 GB · 128K 446 GB

Qwen3.8 27B

12.6 GB12.0 GB file

32K 13.9 GB · 128K 19.3 GB

IQ3_M

Kimi K2.7 Code

not listed

Qwen3.8 27B

13.3 GB14.9 GB file

32K 14.6 GB · 128K 20.0 GB

Q3_K_L

Kimi K2.7 Code

530 GB493.9 GB file

32K 529 GB · 128K 536 GB

Qwen3.8 27B

15.0 GB14.1 GB file

32K 16.3 GB · 128K 21.7 GB

IQ4_XS

Kimi K2.7 Code

556 GB495.1 GB file

32K 555 GB · 128K 561 GB

Qwen3.8 27B

15.7 GB14.3 GB file

32K 17.0 GB · 128K 22.4 GB

IQ4_NL

Kimi K2.7 Code

not listed

Qwen3.8 27B

16.4 GB17.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_1

Kimi K2.7 Code

not listed

Qwen3.8 27B

16.4 GB17.5 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_S

Kimi K2.7 Code

not listed

Qwen3.8 27B

16.4 GB15.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_L

Kimi K2.7 Code

not listed

Qwen3.8 27B

17.8 GB18.8 GB file

32K 19.1 GB · 128K 24.5 GB

Q5_K_S

Kimi K2.7 Code

not listed

Qwen3.8 27B

19.9 GB18.7 GB file

32K 21.2 GB · 128K 26.6 GB

Q5_K_L

Kimi K2.7 Code

not listed

Qwen3.8 27B

20.9 GB21.5 GB file

32K 22.2 GB · 128K 27.6 GB

BF16

Kimi K2.7 Code

2058 GB~2053.8 GB file

32K 2056 GB · 128K 2063 GB

Qwen3.8 27B

56.3 GB54.7 GB file

32K 57.7 GB · 128K 63.0 GB

How to run each

Specifications

Specifications of Kimi K2.7 Code and Qwen3.8 27B
SpecKimi K2.7 CodeQwen3.8 27B
PublisherMoonshot AIAlibaba
Parameters1026.9B27.8B
Active parameters33B per token—
ArchitectureKimiK25ForConditionalGenerationQwen3_5ForConditionalGeneration
Context256K tokens256K tokens
ModalitiesVision, Code, Function-callingVision, Function-calling
LicenseOtherApache 2.0
ReleasedJun 2026Aug 2026

Frequently Asked Questions

Which is better, Kimi K2.7 Code or Qwen3.8 27B?

Qwen3.8 27B leads llmrun Score 122.1 to 118.1 (ranges overlap); only Qwen3.8 27B fits 24 GB (Q4_K_M); Kimi K2.7 Code needs 283.8 GB even at its smallest quant. Choose Kimi K2.7 Code for also does code; choose Qwen3.8 27B for higher llmrun Score and stronger at reasoning.

Which needs less VRAM, Kimi K2.7 Code or Qwen3.8 27B?

At Q4_K_M, Kimi K2.7 Code requires 620.0 GB while Qwen3.8 27B needs 17.4 GB, making Qwen3.8 27B the easier model to run on your local setup.

Can I run Kimi K2.7 Code or Qwen3.8 27B on a 16 GB GPU?

Kimi K2.7 Code does not fit (smallest quant needs 283.8 GB); Qwen3.8 27B fits at Q3_K_L.

Which has a longer context window, Kimi K2.7 Code or Qwen3.8 27B?

Kimi K2.7 Code supports 262,144 tokens and Qwen3.8 27B supports 262,144 tokens.

Kimi K2.7 Code vs Qwen3.8 27B — VRAM & GPU Comparison | llmrun