Mixtral 8x22B Instruct v0.1 vs Qwen3.8 27B

Qwen3.8 27B leads llmrun Score 122.1 to 71.6; only Qwen3.8 27B fits 24 GB (Q4_K_M); Mixtral 8x22B Instruct v0.1 needs 42.7 GB even at its smallest quant.

Model A · Mistral AI

Mixtral 8x22B Instruct v0.1

71.6llmrun Score

140.6B · 39.2B active · 64K context · Apache 2.0 · Apr 2024

ChatFunctions

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 8x22B Instruct v0.1 if you want…

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

Choose Qwen3.8 27B if you want…

Higher llmrun Score
122.1 vs 71.6
Stronger at reasoning
124.0 vs 76.2
Fits a 12 GB GPU
IQ3_XXS · 12 GB; Mixtral 8x22B Instruct v0.1 needs 42.7 GB at its smallest quant
Fits a Mac 32 GB
Q4_K_M · 17.9 GB; Mixtral 8x22B Instruct v0.1 needs 42.7 GB at its smallest quant
Lighter on memory
17.4 vs 85.2 GB at Q4_K_M
Longer context window
256K vs 64K tokens

On your hardware

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

MemoryMixtral 8x22B Instruct v0.1Qwen3.8 27B

8 GB

RTX 4060 · 8 GB tier

Mixtral 8x22B Instruct v0.1

Doesn't fit

smallest quant needs 42.7 GB

Qwen3.8 27B

Doesn't fit

smallest quant needs 8.8 GB

12 GB

RTX 3060 12GB · 12 GB tier

Mixtral 8x22B Instruct v0.1

Doesn't fit

smallest quant needs 42.7 GB

Qwen3.8 27B

IQ3_XXS · ~20 tok/s

12 GB · up to 16Kfits

16 GB

RTX 5060 Ti 16GB · 16 GB tier

Mixtral 8x22B Instruct v0.1

Doesn't fit

smallest quant needs 42.7 GB

Qwen3.8 27B

Q3_K_L · ~19 tok/s

15.4 GB · up to 16Kfits

24 GBreference

RTX 4090 · 24 GB tier

Mixtral 8x22B Instruct v0.1

Doesn't fit

smallest quant needs 42.7 GB

Qwen3.8 27B

Q4_K_M · ~38 tok/s

17.9 GB · up to 64Kfits

32 GB

RTX 5090 · 32 GB tier

Mixtral 8x22B Instruct v0.1

Doesn't fit

smallest quant needs 42.7 GB

Qwen3.8 27B

Q4_K_M · ~67 tok/s

17.9 GB · up to 256Kfits

48 GB

RTX A6000 · 48 GB tier

Mixtral 8x22B Instruct v0.1

IQ2_XS · ~37 tok/s

46.3 GB · up to 16K

Qwen3.8 27B

Q4_K_M · ~29 tok/s

17.9 GB · up to 256Kmore headroom

Mac 32 GB

Mac Mini M4 · Macs

Mixtral 8x22B Instruct v0.1

Doesn't fit

smallest quant needs 42.7 GB

Qwen3.8 27B

Q4_K_M · ~5 tok/s

17.9 GB · up to 128Kfits

Mac 64 GB

Mac Studio M4 Max · Macs

Mixtral 8x22B Instruct v0.1

IQ2_M · ~22 tok/s

51.5 GB · up to 32K

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256Kmore headroom

Mac 128 GB

Mac Studio M4 Max · Macs

Mixtral 8x22B Instruct v0.1

Q4_K_M · ~14 tok/s

88.4 GB · up to 64K

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256Kfaster

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 8x22B Instruct v0.1 Qwen3.8 27B

Overall

Mixtral 8x22B Instruct v0.1

71.666–78

Qwen3.8 27B

122.1120–124

Coding

Mixtral 8x22B Instruct v0.1

no data

Qwen3.8 27B

119.7114–125

Agents

Mixtral 8x22B Instruct v0.1

no data

Qwen3.8 27B

122.8117–129

Math

Mixtral 8x22B Instruct v0.1

no data

Qwen3.8 27B

117.5111–124

Science

Mixtral 8x22B Instruct v0.1

no data

Qwen3.8 27B

112.093–131

Reasoning

Mixtral 8x22B Instruct v0.1

76.265–87

Qwen3.8 27B

124.0121–127

Mixtral 8x22B Instruct v0.1 · #92 of 100 open models · #53 of 60 that fit ≤96 GB

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

Benchmarks

1 shared board: Mixtral 8x22B Instruct v0.1 leads 0, Qwen3.8 27B leads 1 · Benchmarks imported Oct 2026

BoardMixtral 8x22B Instruct v0.1Qwen3.8 27B

DTBench

Mixtral 8x22B Instruct v0.1

55.1%#54/68 open

Lab-reportedEpoch AI · Apr 2024

Qwen3.8 27B

88.0%#9/68 open

Lab-reportedEpoch AI · Aug 2026

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

LMArena Text

Mixtral 8x22B Instruct v0.1

1229.7#135/187 open

ArenaLMArena · Oct 2026

Qwen3.8 27B

1437.8#22/187 open

ArenaLMArena · Oct 2026

Only Mixtral 8x22B Instruct v0.1 (5)

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 8x22B Instruct v0.1Qwen3.8 27B

Q2_K

Mixtral 8x22B Instruct v0.1

60.5 GB52.1 GB file

32K 67.6 GB · 128K —

Qwen3.8 27B

12.6 GB10.8 GB file

32K 13.9 GB · 128K 19.3 GB

Q3_K_S

Mixtral 8x22B Instruct v0.1

62.3 GB61.5 GB file

32K 69.4 GB · 128K —

Qwen3.8 27B

12.9 GB12.7 GB file

32K 14.2 GB · 128K 19.6 GB

Q3_K_M

Mixtral 8x22B Instruct v0.1

69.3 GB67.8 GB file

32K 76.4 GB · 128K —

Qwen3.8 27B

14.3 GB13.4 GB file

32K 15.6 GB · 128K 21.0 GB

Q4_0

Mixtral 8x22B Instruct v0.1

not listed

Qwen3.8 27B

14.6 GB~13.9 GB file

32K 16.0 GB · 128K 21.4 GB

Q4_K_M

Mixtral 8x22B Instruct v0.1

85.2 GB85.6 GB file

32K 92.2 GB · 128K —

Qwen3.8 27B

17.4 GB16.5 GB file

32K 18.8 GB · 128K 24.1 GB

Q5_K_M

Mixtral 8x22B Instruct v0.1

101 GB100.0 GB file

32K 108 GB · 128K —

Qwen3.8 27B

20.5 GB19.8 GB file

32K 21.9 GB · 128K 27.3 GB

Q6_K

Mixtral 8x22B Instruct v0.1

117 GB~116.0 GB file

32K 124 GB · 128K —

Qwen3.8 27B

23.7 GB22.0 GB file

32K 25.0 GB · 128K 30.4 GB

Q8_0

Mixtral 8x22B Instruct v0.1

141 GB149.4 GB file

32K 148 GB · 128K —

Qwen3.8 27B

28.5 GB29.0 GB file

32K 29.9 GB · 128K 35.2 GB

17 more quants

IQ2_XXS

Mixtral 8x22B Instruct v0.1

39.4 GB37.9 GB file

32K 46.5 GB · 128K —

Qwen3.8 27B

8.4 GB7.3 GB file

32K 9.7 GB · 128K 15.1 GB

IQ2_XS

Mixtral 8x22B Instruct v0.1

43.0 GB42.0 GB file

32K 50.0 GB · 128K —

Qwen3.8 27B

9.1 GB9.1 GB file

32K 10.4 GB · 128K 15.8 GB

IQ2_S

Mixtral 8x22B Instruct v0.1

44.7 GB42.6 GB file

32K 51.8 GB · 128K —

Qwen3.8 27B

9.4 GB8.4 GB file

32K 10.8 GB · 128K 16.1 GB

IQ2_M

Mixtral 8x22B Instruct v0.1

48.2 GB46.7 GB file

32K 55.3 GB · 128K —

Qwen3.8 27B

10.1 GB10.5 GB file

32K 11.5 GB · 128K 16.8 GB

IQ3_XXS

Mixtral 8x22B Instruct v0.1

not listed

Qwen3.8 27B

11.5 GB10.9 GB file

32K 12.9 GB · 128K 18.2 GB

IQ3_XS

Mixtral 8x22B Instruct v0.1

58.8 GB58.2 GB file

32K 65.8 GB · 128K —

Qwen3.8 27B

12.2 GB10.4 GB file

32K 13.6 GB · 128K 18.9 GB

IQ3_S

Mixtral 8x22B Instruct v0.1

not listed

Qwen3.8 27B

12.6 GB12.0 GB file

32K 13.9 GB · 128K 19.3 GB

IQ3_M

Mixtral 8x22B Instruct v0.1

not listed

Qwen3.8 27B

13.3 GB14.9 GB file

32K 14.6 GB · 128K 20.0 GB

Q3_K_L

Mixtral 8x22B Instruct v0.1

72.8 GB72.6 GB file

32K 79.9 GB · 128K —

Qwen3.8 27B

15.0 GB14.1 GB file

32K 16.3 GB · 128K 21.7 GB

IQ4_XS

Mixtral 8x22B Instruct v0.1

76.4 GB76.4 GB file

32K 83.4 GB · 128K —

Qwen3.8 27B

15.7 GB14.3 GB file

32K 17.0 GB · 128K 22.4 GB

IQ4_NL

Mixtral 8x22B 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 8x22B Instruct v0.1

not listed

Qwen3.8 27B

16.4 GB17.5 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_S

Mixtral 8x22B Instruct v0.1

79.9 GB80.5 GB file

32K 86.9 GB · 128K —

Qwen3.8 27B

16.4 GB15.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_L

Mixtral 8x22B Instruct v0.1

not listed

Qwen3.8 27B

17.8 GB18.8 GB file

32K 19.1 GB · 128K 24.5 GB

Q5_K_S

Mixtral 8x22B Instruct v0.1

97.5 GB97.0 GB file

32K 105 GB · 128K —

Qwen3.8 27B

19.9 GB18.7 GB file

32K 21.2 GB · 128K 26.6 GB

Q5_K_L

Mixtral 8x22B Instruct v0.1

not listed

Qwen3.8 27B

20.9 GB21.5 GB file

32K 22.2 GB · 128K 27.6 GB

BF16

Mixtral 8x22B Instruct v0.1

282 GB~281.3 GB file

32K 289 GB · 128K —

Qwen3.8 27B

56.3 GB54.7 GB file

32K 57.7 GB · 128K 63.0 GB

How to run each

Mixtral 8x22B Instruct v0.1

Ollama · Q4_K_M

$ollama run hf.co/MaziyarPanahi/Mixtral-8x22B-Instruct-v0.1-GGUF:Q4_K_M

All ways to run Mixtral 8x22B 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 8x22B Instruct v0.1 and Qwen3.8 27B
Spec	Mixtral 8x22B Instruct v0.1	Qwen3.8 27B
Publisher	Mistral AI	Alibaba
Parameters	140.6B	27.8B
Active parameters	39B per token	—
Architecture	MixtralForCausalLM	Qwen3_5ForConditionalGeneration
Context	64K tokens	256K tokens
Modalities	Chat, Function-calling	Vision, Function-calling
License	Apache 2.0	Apache 2.0
Released	Apr 2024	Aug 2026

Frequently Asked Questions

Which is better, Mixtral 8x22B Instruct v0.1 or Qwen3.8 27B?

Qwen3.8 27B leads llmrun Score 122.1 to 71.6; only Qwen3.8 27B fits 24 GB (Q4_K_M); Mixtral 8x22B Instruct v0.1 needs 42.7 GB even at its smallest quant. Choose Mixtral 8x22B Instruct v0.1 for also does chat; choose Qwen3.8 27B for higher llmrun Score and stronger at reasoning.

Which needs less VRAM, Mixtral 8x22B Instruct v0.1 or Qwen3.8 27B?

At Q4_K_M, Mixtral 8x22B Instruct v0.1 requires 85.2 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 Mixtral 8x22B Instruct v0.1 or Qwen3.8 27B on a 16 GB GPU?

Mixtral 8x22B Instruct v0.1 does not fit (smallest quant needs 42.7 GB); Qwen3.8 27B fits at Q3_K_L.

Which has a longer context window, Mixtral 8x22B Instruct v0.1 or Qwen3.8 27B?

Mixtral 8x22B Instruct v0.1 supports 65,536 tokens and Qwen3.8 27B supports 262,144 tokens.