DeepSeek V3.2 Exp vs Qwen3.8 27B

Qwen3.8 27B leads llmrun Score 121.5 to 109.0; only Qwen3.8 27B fits 24 GB (Q4_K_M); DeepSeek V3.2 Exp needs 292.8 GB even at its smallest quant.

Model A · DeepSeek

DeepSeek V3.2 Exp

109.0llmrun Score

685.4B · 41B active · 160K context · MIT · Sep 2025

ChatFunctions

Model B · Alibaba

Qwen3.8 27B

121.5llmrun Score

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

VisionFunctions

Which should you choose?

Choose DeepSeek V3.2 Exp if you want…

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

Choose Qwen3.8 27B if you want…

Higher llmrun Score
121.5 vs 109.0
Stronger at science
112.0 vs 101.2
Stronger at reasoning
124.1 vs 113.4
Ahead on the benchmarks
5 of 6 shared boards
Fits a 12 GB GPU
IQ3_XXS · 12 GB; DeepSeek V3.2 Exp needs 292.8 GB at its smallest quant
Fits a Mac 32 GB
Q4_K_M · 17.9 GB; DeepSeek V3.2 Exp needs 292.8 GB at its smallest quant

On your hardware

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

MemoryDeepSeek V3.2 ExpQwen3.8 27B

8 GB

RTX 4060 · 8 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

Qwen3.8 27B

Doesn't fit

smallest quant needs 8.8 GB

12 GB

RTX 3060 12GB · 12 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

Qwen3.8 27B

IQ3_XXS · ~20 tok/s

12 GB · up to 16Kfits

16 GB

RTX 5060 Ti 16GB · 16 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

Qwen3.8 27B

Q3_K_L · ~19 tok/s

15.4 GB · up to 16Kfits

24 GBreference

RTX 4090 · 24 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

Qwen3.8 27B

Q4_K_M · ~38 tok/s

17.9 GB · up to 64Kfits

32 GB

RTX 5090 · 32 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

Qwen3.8 27B

Q4_K_M · ~67 tok/s

17.9 GB · up to 256Kfits

48 GB

RTX A6000 · 48 GB tier

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

Qwen3.8 27B

Q4_K_M · ~29 tok/s

17.9 GB · up to 256Kfits

Mac 32 GB

Mac Mini M4 · Macs

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

Qwen3.8 27B

Q4_K_M · ~5 tok/s

17.9 GB · up to 128Kfits

Mac 64 GB

Mac Studio M4 Max · Macs

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 GB

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256Kfits

Mac 128 GB

Mac Studio M4 Max · Macs

DeepSeek V3.2 Exp

Doesn't fit

smallest quant needs 292.8 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

DeepSeek V3.2 Exp Qwen3.8 27B

Overall

DeepSeek V3.2 Exp

109.0105–113

Qwen3.8 27B

121.5119–124

Coding

DeepSeek V3.2 Exp

106.8101–113

Qwen3.8 27B

112.1105–119

Math

DeepSeek V3.2 Exp

no data

Qwen3.8 27B

117.5111–125

Science

DeepSeek V3.2 Exp

101.280–122

Qwen3.8 27B

112.093–131

Reasoning

DeepSeek V3.2 Exp

113.4104–123

Qwen3.8 27B

124.1121–127

DeepSeek V3.2 Exp · #27 of 92 open models · #24 of 88 that fit ≤512 GB

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

Benchmarks

6 shared boards: DeepSeek V3.2 Exp leads 0, Qwen3.8 27B leads 5 · Benchmarks imported Oct 2026

BoardDeepSeek V3.2 ExpQwen3.8 27B

LMArena Text

DeepSeek V3.2 Exp

1424.8#28/186 open

ArenaLMArena · Oct 2026

Qwen3.8 27B

1438.1#22/186 open

ArenaLMArena · Oct 2026

LMArena WebDev

DeepSeek V3.2 Exp

1272.4#44/50 open

ArenaLMArena · Oct 2026

Qwen3.8 27B

1592.8#10/50 open

ArenaLMArena · Oct 2026

SciCode

DeepSeek V3.2 Exp

38.9%#32/65 open

Lab-reportedEpoch AI · Sep 2025

Qwen3.8 27B

46.6%#19/65 open

Lab-reportedEpoch AI · Aug 2026

CritPt

DeepSeek V3.2 Exp

2.9%#25/65 open

Lab-reportedEpoch AI · Sep 2025

Qwen3.8 27B

5.4%#15/65 open

Lab-reportedEpoch AI · Aug 2026

DTBench

DeepSeek V3.2 Exp

87.7%#10/68 open

Lab-reportedEpoch AI · Sep 2025

Qwen3.8 27B

88.0%#9/68 open

Lab-reportedEpoch AI · Aug 2026

LMCA

DeepSeek V3.2 Exp

29.1%#24/54 open

Lab-reportedEpoch AI · Sep 2025

Qwen3.8 27B

41.4%#7/54 open

Lab-reportedEpoch AI · Aug 2026

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

Only DeepSeek V3.2 Exp (6)

Only Qwen3.8 27B (8)

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 V3.2 ExpQwen3.8 27B

Q2_K

DeepSeek V3.2 Exp

295 GB~291.3 GB file

32K 294 GB · 128K 301 GB

Qwen3.8 27B

12.6 GB10.8 GB file

32K 13.9 GB · 128K 19.3 GB

Q3_K_S

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

12.9 GB12.7 GB file

32K 14.2 GB · 128K 19.6 GB

Q3_K_M

DeepSeek V3.2 Exp

338 GB~334.1 GB file

32K 337 GB · 128K 344 GB

Qwen3.8 27B

14.3 GB13.4 GB file

32K 15.6 GB · 128K 21.0 GB

Q4_0

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

14.6 GB~13.9 GB file

32K 16.0 GB · 128K 21.4 GB

Q4_K_M

DeepSeek V3.2 Exp

415 GB~411.2 GB file

32K 414 GB · 128K 421 GB

Qwen3.8 27B

17.4 GB16.5 GB file

32K 18.8 GB · 128K 24.1 GB

Q5_K_M

DeepSeek V3.2 Exp

492 GB~488.4 GB file

32K 491 GB · 128K 498 GB

Qwen3.8 27B

20.5 GB19.8 GB file

32K 21.9 GB · 128K 27.3 GB

Q6_K

DeepSeek V3.2 Exp

569 GB~565.5 GB file

32K 568 GB · 128K 575 GB

Qwen3.8 27B

23.7 GB22.0 GB file

32K 25.0 GB · 128K 30.4 GB

Q8_0

DeepSeek V3.2 Exp

689 GB~685.4 GB file

32K 688 GB · 128K 695 GB

Qwen3.8 27B

28.5 GB29.0 GB file

32K 29.9 GB · 128K 35.2 GB

17 more quants

IQ2_XXS

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

8.4 GB7.3 GB file

32K 9.7 GB · 128K 15.1 GB

IQ2_XS

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

9.1 GB9.1 GB file

32K 10.4 GB · 128K 15.8 GB

IQ2_S

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

9.4 GB8.4 GB file

32K 10.8 GB · 128K 16.1 GB

IQ2_M

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

10.1 GB10.5 GB file

32K 11.5 GB · 128K 16.8 GB

IQ3_XXS

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

11.5 GB10.9 GB file

32K 12.9 GB · 128K 18.2 GB

IQ3_XS

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

12.2 GB10.4 GB file

32K 13.6 GB · 128K 18.9 GB

IQ3_S

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

12.6 GB12.0 GB file

32K 13.9 GB · 128K 19.3 GB

IQ3_M

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

13.3 GB14.9 GB file

32K 14.6 GB · 128K 20.0 GB

Q3_K_L

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

15.0 GB14.1 GB file

32K 16.3 GB · 128K 21.7 GB

IQ4_XS

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

15.7 GB14.3 GB file

32K 17.0 GB · 128K 22.4 GB

IQ4_NL

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

16.4 GB17.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_1

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

16.4 GB17.5 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_S

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

16.4 GB15.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_L

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

17.8 GB18.8 GB file

32K 19.1 GB · 128K 24.5 GB

Q5_K_S

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

19.9 GB18.7 GB file

32K 21.2 GB · 128K 26.6 GB

Q5_K_L

DeepSeek V3.2 Exp

not listed

Qwen3.8 27B

20.9 GB21.5 GB file

32K 22.2 GB · 128K 27.6 GB

BF16

DeepSeek V3.2 Exp

1375 GB~1370.8 GB file

32K 1373 GB · 128K 1380 GB

Qwen3.8 27B

56.3 GB54.7 GB file

32K 57.7 GB · 128K 63.0 GB

How to run each

DeepSeek V3.2 Exp

No local recipe · Q4_K_M

No GGUF repo entry exists for this model yet.

All ways to run DeepSeek V3.2 Exp →

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 DeepSeek V3.2 Exp and Qwen3.8 27B
Spec	DeepSeek V3.2 Exp	Qwen3.8 27B
Publisher	DeepSeek	Alibaba
Parameters	685.4B	27.8B
Active parameters	41B per token	—
Architecture	DeepseekV32ForCausalLM	Qwen3_5ForConditionalGeneration
Context	160K tokens	256K tokens
Modalities	Chat, Function-calling	Vision, Function-calling
License	MIT	Apache 2.0
Released	Sep 2025	Aug 2026

Frequently Asked Questions

Which is better, DeepSeek V3.2 Exp or Qwen3.8 27B?

Qwen3.8 27B leads llmrun Score 121.5 to 109.0; only Qwen3.8 27B fits 24 GB (Q4_K_M); DeepSeek V3.2 Exp needs 292.8 GB even at its smallest quant. Choose DeepSeek V3.2 Exp for also does chat; choose Qwen3.8 27B for higher llmrun Score and stronger at science.

Which needs less VRAM, DeepSeek V3.2 Exp or Qwen3.8 27B?

At Q4_K_M, DeepSeek V3.2 Exp requires 415.1 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 DeepSeek V3.2 Exp or Qwen3.8 27B on a 16 GB GPU?

DeepSeek V3.2 Exp does not fit (smallest quant needs 292.8 GB); Qwen3.8 27B fits at Q3_K_L.

Which has a longer context window, DeepSeek V3.2 Exp or Qwen3.8 27B?

DeepSeek V3.2 Exp supports 163,840 tokens and Qwen3.8 27B supports 262,144 tokens.