Qwen3.8 27B vs QwQ 32B

Qwen3.8 27B leads llmrun Score 121.5 to 96.1; both fit 24 GB at Q4_K_M.

Model A · Alibaba

Qwen3.8 27B

121.5llmrun Score

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

VisionFunctions

Model B · Alibaba

QwQ 32B

96.1llmrun Score

32.8B · 40K context · Apache 2.0 · Mar 2025

ChatReasoningFunctions

Which should you choose?

Choose Qwen3.8 27B if you want…

Higher llmrun Score
121.5 vs 96.1
Fits a 12 GB GPU
IQ3_XXS · 12 GB; QwQ 32B needs 13.6 GB at its smallest quant
Lighter on memory
17.4 vs 20.5 GB at Q4_K_M
Longer context window
256K vs 40K tokens
Also does vision
QwQ 32B doesn't list it
Newer release
Aug 2026 vs Mar 2025

Choose QwQ 32B if you want…

Also does chat, reasoning
Qwen3.8 27B doesn't list it

On your hardware

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

MemoryQwen3.8 27BQwQ 32B

8 GB

RTX 4060 · 8 GB tier

Qwen3.8 27B

Doesn't fit

smallest quant needs 8.8 GB

QwQ 32B

Doesn't fit

smallest quant needs 13.6 GB

12 GB

RTX 3060 12GB · 12 GB tier

Qwen3.8 27B

IQ3_XXS · ~20 tok/s

12 GB · up to 16Kfits

QwQ 32B

Doesn't fit

smallest quant needs 13.6 GB

16 GB

RTX 5060 Ti 16GB · 16 GB tier

Qwen3.8 27B

Q3_K_L · ~19 tok/s

15.4 GB · up to 16Kbetter quant

QwQ 32B

IQ2_M · ~25 tok/s

15.7 GB · up to 16K

24 GBreference

RTX 4090 · 24 GB tier

Qwen3.8 27B

Q4_K_M · ~38 tok/s

17.9 GB · up to 64Kmore headroom

QwQ 32B

Q4_K_M · ~32 tok/stight

24.3 GB · up to 8K

32 GB

RTX 5090 · 32 GB tier

Qwen3.8 27B

Q4_K_M · ~67 tok/s

17.9 GB · up to 256Kfaster

QwQ 32B

Q4_K_M · ~57 tok/s

24.3 GB · up to 40K

48 GB

RTX A6000 · 48 GB tier

Qwen3.8 27B

Q4_K_M · ~29 tok/s

17.9 GB · up to 256Kfaster

QwQ 32B

Q4_K_M · ~24 tok/s

24.3 GB · up to 40K

Mac 32 GB

Mac Mini M4 · Macs

Qwen3.8 27B

Q4_K_M · ~5 tok/s

17.9 GB · up to 128Kfaster

QwQ 32B

Q4_K_M · ~4 tok/s

24.3 GB · up to 16K

Mac 64 GB

Mac Studio M4 Max · Macs

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256Kfaster

QwQ 32B

Q4_K_M · ~19 tok/s

24.3 GB · up to 40K

Mac 128 GB

Mac Studio M4 Max · Macs

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256Kfaster

QwQ 32B

Q4_K_M · ~19 tok/s

24.3 GB · up to 40K

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

Qwen3.8 27B QwQ 32B

Overall

Qwen3.8 27B

121.5119–124

QwQ 32B

96.193–99

Coding

Qwen3.8 27B

112.1105–119

QwQ 32B

no data

Math

Qwen3.8 27B

117.5111–125

QwQ 32B

no data

Science

Qwen3.8 27B

112.093–131

QwQ 32B

no data

Reasoning

Qwen3.8 27B

124.1121–127

QwQ 32B

no data

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

QwQ 32B · #59 of 92 open models · #16 of 34 that fit 24 GB

Benchmarks

1 shared board: Qwen3.8 27B leads 1, QwQ 32B leads 0 · Benchmarks imported Oct 2026

BoardQwen3.8 27BQwQ 32B

LMArena Text

Qwen3.8 27B

1438.1#22/186 open

ArenaLMArena · Oct 2026

QwQ 32B

1335.7#84/186 open

ArenaLMArena · Oct 2026

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

Only Qwen3.8 27B (13)

Only QwQ 32B (6)

VRAM by quantization

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

QuantQwen3.8 27BQwQ 32B

Q2_K

Qwen3.8 27B

12.6 GB10.8 GB file

32K 13.9 GB · 128K 19.3 GB

QwQ 32B

14.8 GB12.3 GB file

32K 22.8 GB · 128K —

Q3_K_S

Qwen3.8 27B

12.9 GB12.7 GB file

32K 14.2 GB · 128K 19.6 GB

QwQ 32B

15.2 GB14.4 GB file

32K 23.2 GB · 128K —

Q3_K_M

Qwen3.8 27B

14.3 GB13.4 GB file

32K 15.6 GB · 128K 21.0 GB

QwQ 32B

16.8 GB15.9 GB file

32K 24.9 GB · 128K —

Q4_0

Qwen3.8 27B

14.6 GB~13.9 GB file

32K 16.0 GB · 128K 21.4 GB

QwQ 32B

17.2 GB18.7 GB file

32K 25.3 GB · 128K —

Q4_K_M

Qwen3.8 27B

17.4 GB16.5 GB file

32K 18.8 GB · 128K 24.1 GB

QwQ 32B

20.5 GB19.9 GB file

32K 28.6 GB · 128K —

Q5_K_M

Qwen3.8 27B

20.5 GB19.8 GB file

32K 21.9 GB · 128K 27.3 GB

QwQ 32B

24.2 GB23.3 GB file

32K 32.2 GB · 128K —

Q6_K

Qwen3.8 27B

23.7 GB22.0 GB file

32K 25.0 GB · 128K 30.4 GB

QwQ 32B

27.9 GB26.9 GB file

32K 35.9 GB · 128K —

Q8_0

Qwen3.8 27B

28.5 GB29.0 GB file

32K 29.9 GB · 128K 35.2 GB

QwQ 32B

33.6 GB34.8 GB file

32K 41.7 GB · 128K —

20 more quants

IQ2_XXS

Qwen3.8 27B

8.4 GB7.3 GB file

32K 9.7 GB · 128K 15.1 GB

QwQ 32B

9.9 GB9.0 GB file

32K 17.9 GB · 128K —

IQ2_XS

Qwen3.8 27B

9.1 GB9.1 GB file

32K 10.4 GB · 128K 15.8 GB

QwQ 32B

10.7 GB10.0 GB file

32K 18.7 GB · 128K —

IQ2_S

Qwen3.8 27B

9.4 GB8.4 GB file

32K 10.8 GB · 128K 16.1 GB

QwQ 32B

11.1 GB10.4 GB file

32K 19.1 GB · 128K —

IQ2_M

Qwen3.8 27B

10.1 GB10.5 GB file

32K 11.5 GB · 128K 16.8 GB

QwQ 32B

11.9 GB11.3 GB file

32K 19.9 GB · 128K —

IQ3_XXS

Qwen3.8 27B

11.5 GB10.9 GB file

32K 12.9 GB · 128K 18.2 GB

QwQ 32B

13.5 GB12.8 GB file

32K 21.6 GB · 128K —

Q2_K_S

Qwen3.8 27B

not listed

QwQ 32B

13.9 GB11.5 GB file

32K 22.0 GB · 128K —

IQ3_XS

Qwen3.8 27B

12.2 GB10.4 GB file

32K 13.6 GB · 128K 18.9 GB

QwQ 32B

14.4 GB13.7 GB file

32K 22.4 GB · 128K —

IQ3_S

Qwen3.8 27B

12.6 GB12.0 GB file

32K 13.9 GB · 128K 19.3 GB

QwQ 32B

14.8 GB14.4 GB file

32K 22.8 GB · 128K —

IQ3_M

Qwen3.8 27B

13.3 GB14.9 GB file

32K 14.6 GB · 128K 20.0 GB

QwQ 32B

15.6 GB14.8 GB file

32K 23.6 GB · 128K —

Q3_K_L

Qwen3.8 27B

15.0 GB14.1 GB file

32K 16.3 GB · 128K 21.7 GB

QwQ 32B

17.6 GB17.2 GB file

32K 25.7 GB · 128K —

IQ4_XS

Qwen3.8 27B

15.7 GB14.3 GB file

32K 17.0 GB · 128K 22.4 GB

QwQ 32B

18.5 GB17.7 GB file

32K 26.5 GB · 128K —

IQ4_NL

Qwen3.8 27B

16.4 GB17.4 GB file

32K 17.7 GB · 128K 23.1 GB

QwQ 32B

19.3 GB18.7 GB file

32K 27.3 GB · 128K —

Q4_1

Qwen3.8 27B

16.4 GB17.5 GB file

32K 17.7 GB · 128K 23.1 GB

QwQ 32B

19.3 GB20.6 GB file

32K 27.3 GB · 128K —

Q4_K_S

Qwen3.8 27B

16.4 GB15.4 GB file

32K 17.7 GB · 128K 23.1 GB

QwQ 32B

19.3 GB18.8 GB file

32K 27.3 GB · 128K —

Q4_K_L

Qwen3.8 27B

17.8 GB18.8 GB file

32K 19.1 GB · 128K 24.5 GB

QwQ 32B

20.9 GB20.4 GB file

32K 29.0 GB · 128K —

Q5_0

Qwen3.8 27B

not listed

QwQ 32B

21.3 GB22.6 GB file

32K 29.4 GB · 128K —

Q5_1

Qwen3.8 27B

not listed

QwQ 32B

23.4 GB24.6 GB file

32K 31.4 GB · 128K —

Q5_K_S

Qwen3.8 27B

19.9 GB18.7 GB file

32K 21.2 GB · 128K 26.6 GB

QwQ 32B

23.4 GB22.6 GB file

32K 31.4 GB · 128K —

Q5_K_L

Qwen3.8 27B

20.9 GB21.5 GB file

32K 22.2 GB · 128K 27.6 GB

QwQ 32B

24.6 GB23.7 GB file

32K 32.6 GB · 128K —

BF16

Qwen3.8 27B

56.3 GB54.7 GB file

32K 57.7 GB · 128K 63.0 GB

QwQ 32B

66.4 GB65.5 GB file

32K 74.4 GB · 128K —

How to run each

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 →

QwQ 32B

Ollama · Q4_K_M

$ollama run hf.co/MaziyarPanahi/QwQ-32B-GGUF:Q4_K_M

All ways to run QwQ 32B →

Specifications

Specifications of Qwen3.8 27B and QwQ 32B
Spec	Qwen3.8 27B	QwQ 32B
Publisher	Alibaba	Alibaba
Parameters	27.8B	32.8B
Architecture	Qwen3_5ForConditionalGeneration	Qwen2ForCausalLM
Context	256K tokens	40K tokens
Modalities	Vision, Function-calling	Chat, Reasoning, Function-calling
License	Apache 2.0	Apache 2.0
Released	Aug 2026	Mar 2025

Frequently Asked Questions

Which is better, Qwen3.8 27B or QwQ 32B?

Qwen3.8 27B leads llmrun Score 121.5 to 96.1; both fit 24 GB at Q4_K_M. Choose Qwen3.8 27B for higher llmrun Score and fits a 12 GB GPU; choose QwQ 32B for also does chat, reasoning.

Which needs less VRAM, Qwen3.8 27B or QwQ 32B?

At Q4_K_M, Qwen3.8 27B requires 17.4 GB while QwQ 32B needs 20.5 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 38 tok/s for Qwen3.8 27B (Q4_K_M) and 32 tok/s for QwQ 32B (Q4_K_M), so Qwen3.8 27B is faster. Estimates, ±20%.

Can I run Qwen3.8 27B or QwQ 32B on a 16 GB GPU?

Qwen3.8 27B fits at Q3_K_L; QwQ 32B fits at IQ2_M.

Which has a longer context window, Qwen3.8 27B or QwQ 32B?

Qwen3.8 27B supports 262,144 tokens and QwQ 32B supports 40,960 tokens.