Kimi K2.6 vs Qwen3.8 27B
Kimi K2.6 and Qwen3.8 27B match in llmrun Score, with values of 120.9 versus 122.1; only Qwen3.8 27B fits 24 GB (Q4_K_M); Kimi K2.6 needs 283.8 GB even at its smallest quant.
Model A · Moonshot AI
Kimi K2.61026.9B · 33.3B active · 256K context · Other · Apr 2026
Model B · Alibaba
Qwen3.8 27B27.8B · 256K context · Apache 2.0 · Aug 2026
Choose Kimi K2.6 if you want…
Stronger at science
121.5 vs 112.0
Choose Qwen3.8 27B if you want…
Stronger at reasoning
124.0 vs 117.7
Fits a 12 GB GPU
IQ3_XXS · 12 GB; Kimi K2.6 needs 283.8 GB at its smallest quant
Fits a Mac 32 GB
Q4_K_M · 17.9 GB; Kimi K2.6 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
Newer release
Aug 2026 vs Apr 2026
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 K2.6
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 K2.6
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 K2.6
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 K2.6
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 K2.6
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 K2.6
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 K2.6
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 K2.6
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 K2.6
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).
Overall
Kimi K2.6
Qwen3.8 27B
Coding
Kimi K2.6
Qwen3.8 27B
Agents
Kimi K2.6
Qwen3.8 27B
Math
Kimi K2.6
Qwen3.8 27B
Science
Kimi K2.6
Qwen3.8 27B
Reasoning
Kimi K2.6
Qwen3.8 27B
Kimi K2.6 · #12 of 100 open models · #10 of 96 that fit ≤640 GB
Qwen3.8 27B · #11 of 100 open models · #1 of 35 that fit 24 GB
Kimi K2.6
78.6#6/19 open
IndependentLiveBench · Jun 2026
Qwen3.8 27B
75.7#9/19 open
IndependentLiveBench · Jun 2026
Kimi K2.6
79.4#12/19 open
IndependentLiveBench · Jun 2026
Qwen3.8 27B
80.0#11/19 open
IndependentLiveBench · Jun 2026
Kimi K2.6
84.3#14/19 open
IndependentLiveBench · Jun 2026
Qwen3.8 27B
86.2#11/19 open
IndependentLiveBench · Jun 2026
Kimi K2.6
53.5%#4/66 open
Lab-reportedEpoch AI · Apr 2026
Qwen3.8 27B
46.6%#19/66 open
Lab-reportedEpoch AI · Aug 2026
Kimi K2.6
8.0%#13/66 open
Lab-reportedEpoch AI · Apr 2026
Qwen3.8 27B
5.4%#15/66 open
Lab-reportedEpoch AI · Aug 2026
Kimi K2.6
90.9%#5/68 open
Lab-reportedEpoch AI · Apr 2026
Qwen3.8 27B
88.0%#9/68 open
Lab-reportedEpoch AI · Aug 2026
Kimi K2.6
37.3%#12/54 open
Lab-reportedEpoch AI · Apr 2026
Qwen3.8 27B
41.4%#7/54 open
Lab-reportedEpoch AI · Aug 2026
Kimi K2.6
16.0%#15/26 open
Lab-reportedEpoch AI · Apr 2026
Qwen3.8 27B
16.0%#16/26 open
Lab-reportedEpoch AI · Aug 2026
26 more boards (other shared and single-model boards)
Kimi K2.6
1460.8#10/187 open
ArenaLMArena · Oct 2026
Qwen3.8 27B
1437.8#22/187 open
ArenaLMArena · Oct 2026
Kimi K2.6
1509.6#14/52 open
ArenaLMArena · Oct 2026
Qwen3.8 27B
1593.2#10/52 open
ArenaLMArena · Oct 2026
Only Kimi K2.6 (13)
- GPQA Diamond90.8%
- AIME 2024/202596.1%
- FrontierMath57.2%
- SimpleQA34.9%
- FrontierMath Tier 425.6%
- WeirdML55.9%
- Chess Puzzles20.0%
- EBR-bench2.4%
- Furniture Assembly21.7%
- Mystery Game Puzzles18.0%
- Vending-Bench 26204.6
- ALE-Bench1092.7
- ExploitBench18.4%
Only Qwen3.8 27B (11)
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 K2.6
440 GB358.2 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 K2.6
453 GB444.4 GB file
32K 452 GB · 128K 459 GB
Qwen3.8 27B
12.9 GB12.7 GB file
32K 14.2 GB · 128K 19.6 GB
Q3_K_M
Kimi K2.6
504 GB466.9 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 K2.6
517 GB583.7 GB file
32K 516 GB · 128K 523 GB
Qwen3.8 27B
14.6 GB~13.9 GB file
32K 16.0 GB · 128K 21.4 GB
Q4_K_M
Kimi K2.6
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 K2.6
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 K2.6
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 K2.6
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 K2.6
286 GB271.5 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 K2.6
312 GB303.2 GB file
32K 311 GB · 128K 318 GB
Qwen3.8 27B
9.1 GB9.1 GB file
32K 10.4 GB · 128K 15.8 GB
IQ2_S
Kimi K2.6
325 GB308.8 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 K2.6
350 GB341.7 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 K2.6
402 GB426.6 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 K2.6
427 GB466.4 GB file
32K 426 GB · 128K 433 GB
Qwen3.8 27B
12.2 GB10.4 GB file
32K 13.6 GB · 128K 18.9 GB
IQ3_S
Kimi K2.6
440 GB405.3 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 K2.6
466 GB488.1 GB file
32K 465 GB · 128K 472 GB
Qwen3.8 27B
13.3 GB14.9 GB file
32K 14.6 GB · 128K 20.0 GB
Q3_K_L
Kimi K2.6
530 GB487.5 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 K2.6
556 GB546.2 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 K2.6
not listed
Qwen3.8 27B
16.4 GB17.4 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_1
Kimi K2.6
not listed
Qwen3.8 27B
16.4 GB17.5 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_K_S
Kimi K2.6
not listed
Qwen3.8 27B
16.4 GB15.4 GB file
32K 17.7 GB · 128K 23.1 GB
Q4_K_L
Kimi K2.6
not listed
Qwen3.8 27B
17.8 GB18.8 GB file
32K 19.1 GB · 128K 24.5 GB
Q5_K_S
Kimi K2.6
not listed
Qwen3.8 27B
19.9 GB18.7 GB file
32K 21.2 GB · 128K 26.6 GB
Q5_K_L
Kimi K2.6
not listed
Qwen3.8 27B
20.9 GB21.5 GB file
32K 22.2 GB · 128K 27.6 GB
BF16
Kimi K2.6
2058 GB2053.2 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
Kimi K2.6
Ollama · Q4_K_M
ollama run hf.co/unsloth/Kimi-K2.6-GGUFQwen3.8 27B
Ollama · Q4_K_M
ollama run hf.co/unsloth/Qwen3.8-27B-GGUF:Q4_K_M| Spec | Kimi K2.6 | Qwen3.8 27B |
|---|---|---|
| Publisher | Moonshot AI | Alibaba |
| Parameters | 1026.9B | 27.8B |
| Active parameters | 33B per token | — |
| Architecture | KimiK25ForConditionalGeneration | Qwen3_5ForConditionalGeneration |
| Context | 256K tokens | 256K tokens |
| Modalities | Vision, Function-calling | Vision, Function-calling |
| License | Other | Apache 2.0 |
| Released | Apr 2026 | Aug 2026 |
Frequently Asked Questions
Which is better, Kimi K2.6 or Qwen3.8 27B?
Kimi K2.6 and Qwen3.8 27B match in llmrun Score, with values of 120.9 versus 122.1; only Qwen3.8 27B fits 24 GB (Q4_K_M); Kimi K2.6 needs 283.8 GB even at its smallest quant. Choose Kimi K2.6 for stronger at science; choose Qwen3.8 27B for stronger at reasoning and fits a 12 GB GPU.
Which needs less VRAM, Kimi K2.6 or Qwen3.8 27B?
At Q4_K_M, Kimi K2.6 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 K2.6 or Qwen3.8 27B on a 16 GB GPU?
Kimi K2.6 does not fit (smallest quant needs 283.8 GB); Qwen3.8 27B fits at Q3_K_L.
Which has a longer context window, Kimi K2.6 or Qwen3.8 27B?
Kimi K2.6 supports 262,144 tokens and Qwen3.8 27B supports 262,144 tokens.