Mixtral 8x7B Instruct v0.1 vs Qwen3.8 27B

Qwen3.8 27B leads llmrun Score 122.1 to 65.1; both fit 24 GB (Mixtral 8x7B Instruct v0.1 at IQ3_M, Qwen3.8 27B at Q4_K_M); Mixtral 8x7B Instruct v0.1 is 2.4× faster on RTX 4090 (~92 vs ~38 tok/s).

Model A · Mistral AI

Mixtral 8x7B Instruct v0.1

65.1llmrun Score

46.7B · 12.9B active · 32K context · Apache 2.0 · Dec 2023

Chat

Model B · Alibaba

Qwen3.8 27B

122.1llmrun Score

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

VisionFunctions

Which should you choose?

Choose Mixtral 8x7B Instruct v0.1 if you want…

2.4× faster on RTX 4090
~92 vs ~38 tok/s
Also does chat
Qwen3.8 27B doesn't list it

Choose Qwen3.8 27B if you want…

Higher llmrun Score
122.1 vs 65.1
Stronger at reasoning
124.0 vs 68.7
Fits a 12 GB GPU
IQ3_XXS · 12 GB; Mixtral 8x7B Instruct v0.1 needs 15.3 GB at its smallest quant
Lighter on memory
17.4 vs 28.6 GB at Q4_K_M
Longer context window
256K vs 32K tokens
Also does vision, function-calling
Mixtral 8x7B Instruct v0.1 doesn't list it

On your hardware

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

MemoryMixtral 8x7B Instruct v0.1Qwen3.8 27B

8 GB

RTX 4060 · 8 GB tier

Mixtral 8x7B Instruct v0.1

Doesn't fit

smallest quant needs 15.3 GB

Qwen3.8 27B

Doesn't fit

smallest quant needs 8.8 GB

12 GB

RTX 3060 12GB · 12 GB tier

Mixtral 8x7B Instruct v0.1

Doesn't fit

smallest quant needs 15.3 GB

Qwen3.8 27B

IQ3_XXS · ~20 tok/s

12 GB · up to 16Kfits

16 GB

RTX 5060 Ti 16GB · 16 GB tier

Mixtral 8x7B Instruct v0.1

IQ2_XXS · ~69 tok/s

15.3 GB · up to 16K

Qwen3.8 27B

Q3_K_L · ~19 tok/s

15.4 GB · up to 16Kbetter quant

24 GBreference

RTX 4090 · 24 GB tier

Mixtral 8x7B Instruct v0.1

IQ3_M · ~92 tok/s

23.5 GB · up to 16K

Qwen3.8 27B

Q4_K_M · ~38 tok/s

17.9 GB · up to 64Kmore headroom

32 GB

RTX 5090 · 32 GB tier

Mixtral 8x7B Instruct v0.1

Q4_K_M · ~117 tok/s

30.5 GB · up to 16Kfaster

Qwen3.8 27B

Q4_K_M · ~67 tok/s

17.9 GB · up to 256K

48 GB

RTX A6000 · 48 GB tier

Mixtral 8x7B Instruct v0.1

Q4_K_M · ~57 tok/s

30.5 GB · up to 32Kfaster

Qwen3.8 27B

Q4_K_M · ~29 tok/s

17.9 GB · up to 256K

Mac 32 GB

Mac Mini M4 · Macs

Mixtral 8x7B Instruct v0.1

IQ4_XS · ~11 tok/s

27.6 GB · up to 16K

Qwen3.8 27B

Q4_K_M · ~5 tok/s

17.9 GB · up to 128Kmore headroom

Mac 64 GB

Mac Studio M4 Max · Macs

Mixtral 8x7B Instruct v0.1

Q4_K_M · ~37 tok/s

30.5 GB · up to 32Kfaster

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256K

Mac 128 GB

Mac Studio M4 Max · Macs

Mixtral 8x7B Instruct v0.1

Q4_K_M · ~37 tok/s

30.5 GB · up to 32Kfaster

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

Mixtral 8x7B Instruct v0.1 Qwen3.8 27B

Overall

Mixtral 8x7B Instruct v0.1

65.158–72

Qwen3.8 27B

122.1120–124

Coding

Mixtral 8x7B Instruct v0.1

no data

Qwen3.8 27B

119.7114–125

Agents

Mixtral 8x7B Instruct v0.1

no data

Qwen3.8 27B

122.8117–129

Math

Mixtral 8x7B Instruct v0.1

no data

Qwen3.8 27B

117.5111–124

Science

Mixtral 8x7B Instruct v0.1

no data

Qwen3.8 27B

112.093–131

Reasoning

Mixtral 8x7B Instruct v0.1

68.755–82

Qwen3.8 27B

124.0121–127

Mixtral 8x7B Instruct v0.1 · #96 of 100 open models · #31 of 35 that fit 24 GB

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

Benchmarks

1 shared board: Mixtral 8x7B Instruct v0.1 leads 0, Qwen3.8 27B leads 1 · Benchmarks imported Oct 2026

BoardMixtral 8x7B Instruct v0.1Qwen3.8 27B

DTBench

Mixtral 8x7B Instruct v0.1

49.6%#60/68 open

Lab-reportedEpoch AI · Dec 2023

Qwen3.8 27B

88.0%#9/68 open

Lab-reportedEpoch AI · Aug 2026

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

LMArena Text

Mixtral 8x7B Instruct v0.1

1197.3#147/187 open

ArenaLMArena · Oct 2026

Qwen3.8 27B

1437.8#22/187 open

ArenaLMArena · Oct 2026

Only Mixtral 8x7B Instruct v0.1 (4)

Only Qwen3.8 27B (19)

VRAM by quantization

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

QuantMixtral 8x7B Instruct v0.1Qwen3.8 27B

Q2_K

Mixtral 8x7B Instruct v0.1

20.4 GB15.6 GB file

32K 24.5 GB · 128K —

Qwen3.8 27B

12.6 GB10.8 GB file

32K 13.9 GB · 128K 19.3 GB

Q3_K_S

Mixtral 8x7B Instruct v0.1

21.0 GB20.4 GB file

32K 25.0 GB · 128K —

Qwen3.8 27B

12.9 GB12.7 GB file

32K 14.2 GB · 128K 19.6 GB

Q3_K_M

Mixtral 8x7B Instruct v0.1

23.3 GB20.4 GB file

32K 27.4 GB · 128K —

Qwen3.8 27B

14.3 GB13.4 GB file

32K 15.6 GB · 128K 21.0 GB

Q4_0

Mixtral 8x7B Instruct v0.1

23.9 GB26.4 GB file

32K 28.0 GB · 128K —

Qwen3.8 27B

14.6 GB~13.9 GB file

32K 16.0 GB · 128K 21.4 GB

Q4_K_M

Mixtral 8x7B Instruct v0.1

28.6 GB26.4 GB file

32K 32.6 GB · 128K —

Qwen3.8 27B

17.4 GB16.5 GB file

32K 18.8 GB · 128K 24.1 GB

Q5_K_M

Mixtral 8x7B Instruct v0.1

33.8 GB32.2 GB file

32K 37.9 GB · 128K —

Qwen3.8 27B

20.5 GB19.8 GB file

32K 21.9 GB · 128K 27.3 GB

Q6_K

Mixtral 8x7B Instruct v0.1

39.1 GB38.4 GB file

32K 43.1 GB · 128K —

Qwen3.8 27B

23.7 GB22.0 GB file

32K 25.0 GB · 128K 30.4 GB

Q8_0

Mixtral 8x7B Instruct v0.1

47.3 GB49.6 GB file

32K 51.3 GB · 128K —

Qwen3.8 27B

28.5 GB29.0 GB file

32K 29.9 GB · 128K 35.2 GB

20 more quants

IQ2_XXS

Mixtral 8x7B Instruct v0.1

13.4 GB12.6 GB file

32K 17.4 GB · 128K —

Qwen3.8 27B

8.4 GB7.3 GB file

32K 9.7 GB · 128K 15.1 GB

IQ2_XS

Mixtral 8x7B Instruct v0.1

14.6 GB13.9 GB file

32K 18.6 GB · 128K —

Qwen3.8 27B

9.1 GB9.1 GB file

32K 10.4 GB · 128K 15.8 GB

IQ2_S

Mixtral 8x7B Instruct v0.1

15.2 GB14.1 GB file

32K 19.2 GB · 128K —

Qwen3.8 27B

9.4 GB8.4 GB file

32K 10.8 GB · 128K 16.1 GB

IQ2_M

Mixtral 8x7B Instruct v0.1

16.3 GB15.5 GB file

32K 20.4 GB · 128K —

Qwen3.8 27B

10.1 GB10.5 GB file

32K 11.5 GB · 128K 16.8 GB

IQ3_XXS

Mixtral 8x7B Instruct v0.1

18.7 GB18.2 GB file

32K 22.7 GB · 128K —

Qwen3.8 27B

11.5 GB10.9 GB file

32K 12.9 GB · 128K 18.2 GB

Q2_K_S

Mixtral 8x7B Instruct v0.1

19.3 GB16.0 GB file

32K 23.3 GB · 128K —

Qwen3.8 27B

not listed

IQ3_XS

Mixtral 8x7B Instruct v0.1

19.8 GB19.4 GB file

32K 23.9 GB · 128K —

Qwen3.8 27B

12.2 GB10.4 GB file

32K 13.6 GB · 128K 18.9 GB

IQ3_S

Mixtral 8x7B Instruct v0.1

20.4 GB20.4 GB file

32K 24.5 GB · 128K —

Qwen3.8 27B

12.6 GB12.0 GB file

32K 13.9 GB · 128K 19.3 GB

IQ3_M

Mixtral 8x7B Instruct v0.1

21.6 GB21.4 GB file

32K 25.6 GB · 128K —

Qwen3.8 27B

13.3 GB14.9 GB file

32K 14.6 GB · 128K 20.0 GB

Q3_K_L

Mixtral 8x7B Instruct v0.1

24.5 GB24.2 GB file

32K 28.5 GB · 128K —

Qwen3.8 27B

15.0 GB14.1 GB file

32K 16.3 GB · 128K 21.7 GB

IQ4_XS

Mixtral 8x7B Instruct v0.1

25.7 GB25.1 GB file

32K 29.7 GB · 128K —

Qwen3.8 27B

15.7 GB14.3 GB file

32K 17.0 GB · 128K 22.4 GB

IQ4_NL

Mixtral 8x7B Instruct v0.1

not listed

Qwen3.8 27B

16.4 GB17.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_1

Mixtral 8x7B Instruct v0.1

26.8 GB29.3 GB file

32K 30.9 GB · 128K —

Qwen3.8 27B

16.4 GB17.5 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_S

Mixtral 8x7B Instruct v0.1

26.8 GB26.7 GB file

32K 30.9 GB · 128K —

Qwen3.8 27B

16.4 GB15.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_L

Mixtral 8x7B Instruct v0.1

not listed

Qwen3.8 27B

17.8 GB18.8 GB file

32K 19.1 GB · 128K 24.5 GB

Q5_0

Mixtral 8x7B Instruct v0.1

29.8 GB32.2 GB file

32K 33.8 GB · 128K —

Qwen3.8 27B

not listed

Q5_1

Mixtral 8x7B Instruct v0.1

32.7 GB35.1 GB file

32K 36.7 GB · 128K —

Qwen3.8 27B

not listed

Q5_K_S

Mixtral 8x7B Instruct v0.1

32.7 GB32.2 GB file

32K 36.7 GB · 128K —

Qwen3.8 27B

19.9 GB18.7 GB file

32K 21.2 GB · 128K 26.6 GB

Q5_K_L

Mixtral 8x7B Instruct v0.1

not listed

Qwen3.8 27B

20.9 GB21.5 GB file

32K 22.2 GB · 128K 27.6 GB

BF16

Mixtral 8x7B Instruct v0.1

94.0 GB~93.4 GB file

32K 98.0 GB · 128K —

Qwen3.8 27B

56.3 GB54.7 GB file

32K 57.7 GB · 128K 63.0 GB

How to run each

Mixtral 8x7B Instruct v0.1

Ollama · Q4_K_M

$ollama run hf.co/TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF:Q4_K_M

All ways to run Mixtral 8x7B Instruct v0.1 →

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 Mixtral 8x7B Instruct v0.1 and Qwen3.8 27B
Spec	Mixtral 8x7B Instruct v0.1	Qwen3.8 27B
Publisher	Mistral AI	Alibaba
Parameters	46.7B	27.8B
Active parameters	13B per token	—
Architecture	MixtralForCausalLM	Qwen3_5ForConditionalGeneration
Context	32K tokens	256K tokens
Modalities	Chat	Vision, Function-calling
License	Apache 2.0	Apache 2.0
Released	Dec 2023	Aug 2026

Frequently Asked Questions

Which is better, Mixtral 8x7B Instruct v0.1 or Qwen3.8 27B?

Qwen3.8 27B leads llmrun Score 122.1 to 65.1; both fit 24 GB (Mixtral 8x7B Instruct v0.1 at IQ3_M, Qwen3.8 27B at Q4_K_M); Mixtral 8x7B Instruct v0.1 is 2.4× faster on RTX 4090 (~92 vs ~38 tok/s). Choose Mixtral 8x7B Instruct v0.1 for 2.4× faster on RTX 4090 and also does chat; choose Qwen3.8 27B for higher llmrun Score and stronger at reasoning.

Which needs less VRAM, Mixtral 8x7B Instruct v0.1 or Qwen3.8 27B?

At Q4_K_M, Mixtral 8x7B Instruct v0.1 requires 28.6 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 92 tok/s for Mixtral 8x7B Instruct v0.1 (IQ3_M) and 38 tok/s for Qwen3.8 27B (Q4_K_M), so Mixtral 8x7B Instruct v0.1 is faster. Estimates, ±20%.

Can I run Mixtral 8x7B Instruct v0.1 or Qwen3.8 27B on a 16 GB GPU?

Mixtral 8x7B Instruct v0.1 fits at IQ2_XXS; Qwen3.8 27B fits at Q3_K_L.

Which has a longer context window, Mixtral 8x7B Instruct v0.1 or Qwen3.8 27B?

Mixtral 8x7B Instruct v0.1 supports 32,768 tokens and Qwen3.8 27B supports 262,144 tokens.