Qwen3.6 35B A3B vs Qwen3.8 27B

Qwen3.8 27B leads llmrun Score 121.5 to 106.9; both fit 24 GB at Q4_K_M; Qwen3.6 35B A3B is 4.0× faster on RTX 4090 (~151 vs ~38 tok/s).

Model A · Alibaba

Qwen3.6 35B A3B

106.9llmrun Score

36.0B · 4.7B active · 256K context · Apache 2.0 · Apr 2026

VisionFunctions

Model B · Alibaba

Qwen3.8 27B

121.5llmrun Score

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

VisionFunctions

Which should you choose?

Choose Qwen3.6 35B A3B if you want…

4.0× faster on RTX 4090
~151 vs ~38 tok/s

Choose Qwen3.8 27B if you want…

Higher llmrun Score
121.5 vs 106.9
Stronger at reasoning
124.1 vs 106.6
Stronger at math
117.5 vs 109.0
Ahead on the benchmarks
4 of 4 shared boards
Fits a 12 GB GPU
IQ3_XXS · 12 GB; Qwen3.6 35B A3B needs 10.4 GB at its smallest quant
Lighter on memory
17.4 vs 22.0 GB at Q4_K_M

On your hardware

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

MemoryQwen3.6 35B A3BQwen3.8 27B

8 GB

RTX 4060 · 8 GB tier

Qwen3.6 35B A3B

Doesn't fit

smallest quant needs 10.4 GB

Qwen3.8 27B

Doesn't fit

smallest quant needs 8.8 GB

12 GB

RTX 3060 12GB · 12 GB tier

Qwen3.6 35B A3B

IQ2_S · ~114 tok/s

11.7 GB · up to 32K

Qwen3.8 27B

IQ3_XXS · ~20 tok/s

12 GB · up to 16Kbetter quant

16 GB

RTX 5060 Ti 16GB · 16 GB tier

Qwen3.6 35B A3B

Q2_K · ~108 tok/s

15.7 GB · up to 32K

Qwen3.8 27B

Q3_K_L · ~19 tok/s

15.4 GB · up to 16Kbetter quant

24 GBreference

RTX 4090 · 24 GB tier

Qwen3.6 35B A3B

Q4_K_M · ~151 tok/s

22 GB · up to 128Kfaster

Qwen3.8 27B

Q4_K_M · ~38 tok/s

17.9 GB · up to 64K

32 GB

RTX 5090 · 32 GB tier

Qwen3.6 35B A3B

Q4_K_M · ~213 tok/s

22 GB · up to 256Kfaster

Qwen3.8 27B

Q4_K_M · ~67 tok/s

17.9 GB · up to 256K

48 GB

RTX A6000 · 48 GB tier

Qwen3.6 35B A3B

Q4_K_M · ~125 tok/s

22 GB · up to 256Kfaster

Qwen3.8 27B

Q4_K_M · ~29 tok/s

17.9 GB · up to 256K

Mac 32 GB

Mac Mini M4 · Macs

Qwen3.6 35B A3B

Q4_K_M · ~24 tok/s

22 GB · up to 256Kfaster

Qwen3.8 27B

Q4_K_M · ~5 tok/s

17.9 GB · up to 128K

Mac 64 GB

Mac Studio M4 Max · Macs

Qwen3.6 35B A3B

Q4_K_M · ~64 tok/s

22 GB · up to 256Kfaster

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256K

Mac 128 GB

Mac Studio M4 Max · Macs

Qwen3.6 35B A3B

Q4_K_M · ~64 tok/s

22 GB · up to 256Kfaster

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256K

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

Qwen3.6 35B A3B Qwen3.8 27B

Overall

Qwen3.6 35B A3B

106.9104–110

Qwen3.8 27B

121.5119–124

Coding

Qwen3.6 35B A3B

105.299–112

Qwen3.8 27B

112.1105–119

Math

Qwen3.6 35B A3B

109.0104–114

Qwen3.8 27B

117.5111–125

Science

Qwen3.6 35B A3B

109.9101–119

Qwen3.8 27B

112.093–131

Reasoning

Qwen3.6 35B A3B

106.699–114

Qwen3.8 27B

124.1121–127

Qwen3.6 35B A3B · #33 of 92 open models · #3 of 34 that fit 24 GB

Qwen3.8 27B · #10 of 92 open models · #1 of 34 that fit 24 GB

Benchmarks

4 shared boards: Qwen3.6 35B A3B leads 0, Qwen3.8 27B leads 4 · Benchmarks imported Oct 2026

BoardQwen3.6 35B A3BQwen3.8 27B

SciCode

Qwen3.6 35B A3B

35.8%#41/65 open

Lab-reportedEpoch AI · Apr 2026

Qwen3.8 27B

46.6%#19/65 open

Lab-reportedEpoch AI · Aug 2026

CritPt

Qwen3.6 35B A3B

0.3%#44/65 open

Lab-reportedEpoch AI · Apr 2026

Qwen3.8 27B

5.4%#15/65 open

Lab-reportedEpoch AI · Aug 2026

DTBench

Qwen3.6 35B A3B

73.9%#30/68 open

Lab-reportedEpoch AI · Apr 2026

Qwen3.8 27B

88.0%#9/68 open

Lab-reportedEpoch AI · Aug 2026

LMCA

Qwen3.6 35B A3B

29.7%#19/54 open

Lab-reportedEpoch AI · Apr 2026

Qwen3.8 27B

41.4%#7/54 open

Lab-reportedEpoch AI · Aug 2026

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

Surface Evolver Bench

Qwen3.6 35B A3B

44.4%#8/13 open

Lab-reportedEpoch AI · Apr 2026

Qwen3.8 27B

45.0%#7/13 open

Lab-reportedEpoch AI · Aug 2026

Only Qwen3.6 35B A3B (7)

Only Qwen3.8 27B (9)

VRAM by quantization

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

QuantQwen3.6 35B A3BQwen3.8 27B

Q2_K

Qwen3.6 35B A3B

15.7 GB13.5 GB file

32K 15.9 GB · 128K 16.9 GB

Qwen3.8 27B

12.6 GB10.8 GB file

32K 13.9 GB · 128K 19.3 GB

Q3_K_S

Qwen3.6 35B A3B

16.1 GB15.4 GB file

32K 16.4 GB · 128K 17.4 GB

Qwen3.8 27B

12.9 GB12.7 GB file

32K 14.2 GB · 128K 19.6 GB

Q3_K_M

Qwen3.6 35B A3B

17.9 GB16.6 GB file

32K 18.2 GB · 128K 19.2 GB

Qwen3.8 27B

14.3 GB13.4 GB file

32K 15.6 GB · 128K 21.0 GB

Q4_0

Qwen3.6 35B A3B

18.4 GB~18.0 GB file

32K 18.6 GB · 128K 19.6 GB

Qwen3.8 27B

14.6 GB~13.9 GB file

32K 16.0 GB · 128K 21.4 GB

Q4_K_M

Qwen3.6 35B A3B

22.0 GB22.1 GB file

32K 22.2 GB · 128K 23.2 GB

Qwen3.8 27B

17.4 GB16.5 GB file

32K 18.8 GB · 128K 24.1 GB

Q5_K_M

Qwen3.6 35B A3B

26.0 GB26.5 GB file

32K 26.3 GB · 128K 27.3 GB

Qwen3.8 27B

20.5 GB19.8 GB file

32K 21.9 GB · 128K 27.3 GB

Q6_K

Qwen3.6 35B A3B

30.0 GB29.3 GB file

32K 30.3 GB · 128K 31.3 GB

Qwen3.8 27B

23.7 GB22.0 GB file

32K 25.0 GB · 128K 30.4 GB

Q8_0

Qwen3.6 35B A3B

36.3 GB36.9 GB file

32K 36.6 GB · 128K 37.6 GB

Qwen3.8 27B

28.5 GB29.0 GB file

32K 29.9 GB · 128K 35.2 GB

20 more quants

IQ2_XXS

Qwen3.6 35B A3B

10.3 GB10.8 GB file

32K 10.5 GB · 128K 11.5 GB

Qwen3.8 27B

8.4 GB7.3 GB file

32K 9.7 GB · 128K 15.1 GB

IQ2_XS

Qwen3.6 35B A3B

11.2 GB11.7 GB file

32K 11.4 GB · 128K 12.4 GB

Qwen3.8 27B

9.1 GB9.1 GB file

32K 10.4 GB · 128K 15.8 GB

IQ2_S

Qwen3.6 35B A3B

11.6 GB11.9 GB file

32K 11.9 GB · 128K 12.9 GB

Qwen3.8 27B

9.4 GB8.4 GB file

32K 10.8 GB · 128K 16.1 GB

IQ2_M

Qwen3.6 35B A3B

12.5 GB11.5 GB file

32K 12.8 GB · 128K 13.8 GB

Qwen3.8 27B

10.1 GB10.5 GB file

32K 11.5 GB · 128K 16.8 GB

IQ3_XXS

Qwen3.6 35B A3B

14.3 GB13.2 GB file

32K 14.6 GB · 128K 15.6 GB

Qwen3.8 27B

11.5 GB10.9 GB file

32K 12.9 GB · 128K 18.2 GB

Q2_K_S

Qwen3.6 35B A3B

14.8 GB12.2 GB file

32K 15.0 GB · 128K 16.0 GB

Qwen3.8 27B

not listed

IQ3_XS

Qwen3.6 35B A3B

15.2 GB17.1 GB file

32K 15.5 GB · 128K 16.5 GB

Qwen3.8 27B

12.2 GB10.4 GB file

32K 13.6 GB · 128K 18.9 GB

IQ3_S

Qwen3.6 35B A3B

15.7 GB13.7 GB file

32K 15.9 GB · 128K 16.9 GB

Qwen3.8 27B

12.6 GB12.0 GB file

32K 13.9 GB · 128K 19.3 GB

IQ3_M

Qwen3.6 35B A3B

16.6 GB17.8 GB file

32K 16.8 GB · 128K 17.8 GB

Qwen3.8 27B

13.3 GB14.9 GB file

32K 14.6 GB · 128K 20.0 GB

Q3_K_L

Qwen3.6 35B A3B

18.8 GB17.8 GB file

32K 19.1 GB · 128K 20.1 GB

Qwen3.8 27B

15.0 GB14.1 GB file

32K 16.3 GB · 128K 21.7 GB

IQ4_XS

Qwen3.6 35B A3B

19.7 GB17.7 GB file

32K 20.0 GB · 128K 21.0 GB

Qwen3.8 27B

15.7 GB14.3 GB file

32K 17.0 GB · 128K 22.4 GB

IQ4_NL

Qwen3.6 35B A3B

20.6 GB18.0 GB file

32K 20.9 GB · 128K 21.9 GB

Qwen3.8 27B

16.4 GB17.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_1

Qwen3.6 35B A3B

20.6 GB22.9 GB file

32K 20.9 GB · 128K 21.9 GB

Qwen3.8 27B

16.4 GB17.5 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_S

Qwen3.6 35B A3B

20.6 GB20.9 GB file

32K 20.9 GB · 128K 21.9 GB

Qwen3.8 27B

16.4 GB15.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_L

Qwen3.6 35B A3B

22.4 GB22.7 GB file

32K 22.7 GB · 128K 23.7 GB

Qwen3.8 27B

17.8 GB18.8 GB file

32K 19.1 GB · 128K 24.5 GB

Q5_0

Qwen3.6 35B A3B

22.9 GB24.1 GB file

32K 23.1 GB · 128K 24.1 GB

Qwen3.8 27B

not listed

Q5_1

Qwen3.6 35B A3B

25.1 GB26.1 GB file

32K 25.4 GB · 128K 26.4 GB

Qwen3.8 27B

not listed

Q5_K_S

Qwen3.6 35B A3B

25.1 GB24.9 GB file

32K 25.4 GB · 128K 26.4 GB

Qwen3.8 27B

19.9 GB18.7 GB file

32K 21.2 GB · 128K 26.6 GB

Q5_K_L

Qwen3.6 35B A3B

26.5 GB26.2 GB file

32K 26.7 GB · 128K 27.7 GB

Qwen3.8 27B

20.9 GB21.5 GB file

32K 22.2 GB · 128K 27.6 GB

BF16

Qwen3.6 35B A3B

72.3 GB69.4 GB file

32K 72.5 GB · 128K 73.6 GB

Qwen3.8 27B

56.3 GB54.7 GB file

32K 57.7 GB · 128K 63.0 GB

How to run each

Qwen3.6 35B A3B

Ollama · Q4_K_M

$ollama run hf.co/unsloth/Qwen3.6-35B-A3B-GGUF:Q4_K_M

All ways to run Qwen3.6 35B A3B →

Qwen3.8 27B

Ollama · Q4_K_M

$ollama run hf.co/unsloth/Qwen3.8-27B-GGUF:Q4_K_M

All ways to run Qwen3.8 27B →

Specifications

Specifications of Qwen3.6 35B A3B and Qwen3.8 27B
Spec	Qwen3.6 35B A3B	Qwen3.8 27B
Publisher	Alibaba	Alibaba
Parameters	36.0B	27.8B
Active parameters	4.7B per token	—
Architecture	Qwen3_5MoeForConditionalGeneration	Qwen3_5ForConditionalGeneration
Context	256K tokens	256K tokens
Modalities	Vision, Function-calling	Vision, Function-calling
License	Apache 2.0	Apache 2.0
Released	Apr 2026	Aug 2026

Frequently Asked Questions

Which is better, Qwen3.6 35B A3B or Qwen3.8 27B?

Qwen3.8 27B leads llmrun Score 121.5 to 106.9; both fit 24 GB at Q4_K_M; Qwen3.6 35B A3B is 4.0× faster on RTX 4090 (~151 vs ~38 tok/s). Choose Qwen3.6 35B A3B for 4.0× faster on RTX 4090; choose Qwen3.8 27B for higher llmrun Score and stronger at reasoning.

Which needs less VRAM, Qwen3.6 35B A3B or Qwen3.8 27B?

At Q4_K_M, Qwen3.6 35B A3B requires 22.0 GB while Qwen3.8 27B needs 17.4 GB, making Qwen3.8 27B the easier model to run on your local setup.

Which is faster on RTX 4090?

Estimated decode speed on RTX 4090 is about 151 tok/s for Qwen3.6 35B A3B (Q4_K_M) and 38 tok/s for Qwen3.8 27B (Q4_K_M), so Qwen3.6 35B A3B is faster. Estimates, ±20%.

Can I run Qwen3.6 35B A3B or Qwen3.8 27B on a 16 GB GPU?

Qwen3.6 35B A3B fits at Q2_K; Qwen3.8 27B fits at Q3_K_L.

Which has a longer context window, Qwen3.6 35B A3B or Qwen3.8 27B?

Qwen3.6 35B A3B supports 262,144 tokens and Qwen3.8 27B supports 262,144 tokens.