Mixtral 8x7B Instruct v0.1 vs Qwen3.6 35B A3B

Qwen3.6 35B A3B leads llmrun Score 106.8 to 65.8; both fit 24 GB (Mixtral 8x7B Instruct v0.1 at IQ3_M, Qwen3.6 35B A3B at Q4_K_M); Qwen3.6 35B A3B is 1.6× faster on RTX 4090 (~151 vs ~92 tok/s).

Model A · Mistral AI

Mixtral 8x7B Instruct v0.1

65.8llmrun Score

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

Chat

Model B · Alibaba

Qwen3.6 35B A3B

106.8llmrun Score

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

VisionFunctions

Which should you choose?

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

Also does chat
Qwen3.6 35B A3B doesn't list it

Choose Qwen3.6 35B A3B if you want…

Higher llmrun Score
106.8 vs 65.8
Stronger at reasoning
103.7 vs 71.0
1.6× faster on RTX 4090
~151 vs ~92 tok/s
Lighter on memory
22.0 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 v0.1Qwen3.6 35B A3B

8 GB

RTX 4060 · 8 GB tier

Mixtral 8x7B Instruct v0.1

Doesn't fit

smallest quant needs 15.3 GB

Qwen3.6 35B A3B

Doesn't fit

smallest quant needs 10.4 GB

12 GB

RTX 3060 12GB · 12 GB tier

Mixtral 8x7B Instruct v0.1

Doesn't fit

smallest quant needs 15.3 GB

Qwen3.6 35B A3B

IQ2_S · ~114 tok/s

11.7 GB · up to 32Kfits

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

Qwen3.6 35B A3B

Q2_K · ~108 tok/s

15.7 GB · up to 32K

24 GBreference

RTX 4090 · 24 GB tier

Mixtral 8x7B Instruct v0.1

IQ3_M · ~92 tok/s

23.5 GB · up to 16K

Qwen3.6 35B A3B

Q4_K_M · ~151 tok/s

22 GB · up to 128Kmore headroom

32 GB

RTX 5090 · 32 GB tier

Mixtral 8x7B Instruct v0.1

Q4_K_M · ~117 tok/s

30.5 GB · up to 16K

Qwen3.6 35B A3B

Q4_K_M · ~213 tok/s

22 GB · up to 256Kfaster

48 GB

RTX A6000 · 48 GB tier

Mixtral 8x7B Instruct v0.1

Q4_K_M · ~57 tok/s

30.5 GB · up to 32K

Qwen3.6 35B A3B

Q4_K_M · ~125 tok/s

22 GB · up to 256Kfaster

Mac 32 GB

Mac Mini M4 · Macs

Mixtral 8x7B Instruct v0.1

IQ4_XS · ~11 tok/s

27.6 GB · up to 16K

Qwen3.6 35B A3B

Q4_K_M · ~24 tok/s

22 GB · up to 256Kmore 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 32K

Qwen3.6 35B A3B

Q4_K_M · ~64 tok/s

22 GB · up to 256Kfaster

Mac 128 GB

Mac Studio M4 Max · Macs

Mixtral 8x7B Instruct v0.1

Q4_K_M · ~37 tok/s

30.5 GB · up to 32K

Qwen3.6 35B A3B

Q4_K_M · ~64 tok/s

22 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 8x7B Instruct v0.1 Qwen3.6 35B A3B

Overall

Mixtral 8x7B Instruct v0.1

65.859–73

Qwen3.6 35B A3B

106.8104–110

Coding

Mixtral 8x7B Instruct v0.1

no data

Qwen3.6 35B A3B

105.399–112

Math

Mixtral 8x7B Instruct v0.1

no data

Qwen3.6 35B A3B

109.0104–114

Science

Mixtral 8x7B Instruct v0.1

no data

Qwen3.6 35B A3B

110.1101–119

Reasoning

Mixtral 8x7B Instruct v0.1

71.058–84

Qwen3.6 35B A3B

103.796–112

Mixtral 8x7B Instruct v0.1 · #100 of 106 open models · #31 of 36 that fit 24 GB

Qwen3.6 35B A3B · #41 of 106 open models · #3 of 36 that fit 24 GB

Benchmarks

2 shared boards: Mixtral 8x7B Instruct v0.1 leads 0, Qwen3.6 35B A3B leads 2 · Benchmarks imported Nov 2026

BoardMixtral 8x7B Instruct v0.1Qwen3.6 35B A3B

GPQA Diamond

Mixtral 8x7B Instruct v0.1

30.6%#83/100 open

IndependentEpoch AI · Dec 2023

Qwen3.6 35B A3B

84.9%#23/100 open

IndependentEpoch AI · Apr 2026

DTBench

Mixtral 8x7B Instruct v0.1

49.6%#62/70 open

Lab-reportedEpoch AI · Dec 2023

Qwen3.6 35B A3B

73.9%#32/70 open

Lab-reportedEpoch AI · Apr 2026

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

Only Mixtral 8x7B Instruct v0.1 (4)

Only Qwen3.6 35B A3B (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.

QuantMixtral 8x7B Instruct v0.1Qwen3.6 35B A3B

Q2_K

Mixtral 8x7B Instruct v0.1

20.4 GB15.6 GB file

32K 24.5 GB · 128K —

Qwen3.6 35B A3B

15.7 GB13.5 GB file

32K 15.9 GB · 128K 16.9 GB

Q3_K_S

Mixtral 8x7B Instruct v0.1

21.0 GB20.4 GB file

32K 25.0 GB · 128K —

Qwen3.6 35B A3B

16.1 GB15.4 GB file

32K 16.4 GB · 128K 17.4 GB

Q3_K_M

Mixtral 8x7B Instruct v0.1

23.3 GB20.4 GB file

32K 27.4 GB · 128K —

Qwen3.6 35B A3B

17.9 GB16.6 GB file

32K 18.2 GB · 128K 19.2 GB

Q4_0

Mixtral 8x7B Instruct v0.1

23.9 GB26.4 GB file

32K 28.0 GB · 128K —

Qwen3.6 35B A3B

18.4 GB19.8 GB file

32K 18.6 GB · 128K 19.6 GB

Q4_K_M

Mixtral 8x7B Instruct v0.1

28.6 GB26.4 GB file

32K 32.6 GB · 128K —

Qwen3.6 35B A3B

22.0 GB22.1 GB file

32K 22.2 GB · 128K 23.2 GB

Q5_K_M

Mixtral 8x7B Instruct v0.1

33.8 GB32.2 GB file

32K 37.9 GB · 128K —

Qwen3.6 35B A3B

26.0 GB26.5 GB file

32K 26.3 GB · 128K 27.3 GB

Q6_K

Mixtral 8x7B Instruct v0.1

39.1 GB38.4 GB file

32K 43.1 GB · 128K —

Qwen3.6 35B A3B

30.0 GB29.3 GB file

32K 30.3 GB · 128K 31.3 GB

Q8_0

Mixtral 8x7B Instruct v0.1

47.3 GB49.6 GB file

32K 51.3 GB · 128K —

Qwen3.6 35B A3B

36.3 GB36.9 GB file

32K 36.6 GB · 128K 37.6 GB

20 more quants

IQ2_XXS

Mixtral 8x7B Instruct v0.1

13.4 GB12.6 GB file

32K 17.4 GB · 128K —

Qwen3.6 35B A3B

10.3 GB10.8 GB file

32K 10.5 GB · 128K 11.5 GB

IQ2_XS

Mixtral 8x7B Instruct v0.1

14.6 GB13.9 GB file

32K 18.6 GB · 128K —

Qwen3.6 35B A3B

11.2 GB11.7 GB file

32K 11.4 GB · 128K 12.4 GB

IQ2_S

Mixtral 8x7B Instruct v0.1

15.2 GB14.1 GB file

32K 19.2 GB · 128K —

Qwen3.6 35B A3B

11.6 GB11.9 GB file

32K 11.9 GB · 128K 12.9 GB

IQ2_M

Mixtral 8x7B Instruct v0.1

16.3 GB15.5 GB file

32K 20.4 GB · 128K —

Qwen3.6 35B A3B

12.5 GB11.5 GB file

32K 12.8 GB · 128K 13.8 GB

IQ3_XXS

Mixtral 8x7B Instruct v0.1

18.7 GB18.2 GB file

32K 22.7 GB · 128K —

Qwen3.6 35B A3B

14.3 GB13.2 GB file

32K 14.6 GB · 128K 15.6 GB

Q2_K_S

Mixtral 8x7B Instruct v0.1

19.3 GB16.0 GB file

32K 23.3 GB · 128K —

Qwen3.6 35B A3B

14.8 GB12.2 GB file

32K 15.0 GB · 128K 16.0 GB

IQ3_XS

Mixtral 8x7B Instruct v0.1

19.8 GB19.4 GB file

32K 23.9 GB · 128K —

Qwen3.6 35B A3B

15.2 GB17.1 GB file

32K 15.5 GB · 128K 16.5 GB

IQ3_S

Mixtral 8x7B Instruct v0.1

20.4 GB20.4 GB file

32K 24.5 GB · 128K —

Qwen3.6 35B A3B

15.7 GB13.7 GB file

32K 15.9 GB · 128K 16.9 GB

IQ3_M

Mixtral 8x7B Instruct v0.1

21.6 GB21.4 GB file

32K 25.6 GB · 128K —

Qwen3.6 35B A3B

16.6 GB17.8 GB file

32K 16.8 GB · 128K 17.8 GB

Q3_K_L

Mixtral 8x7B Instruct v0.1

24.5 GB24.2 GB file

32K 28.5 GB · 128K —

Qwen3.6 35B A3B

18.8 GB17.8 GB file

32K 19.1 GB · 128K 20.1 GB

IQ4_XS

Mixtral 8x7B Instruct v0.1

25.7 GB25.4 GB file

32K 29.7 GB · 128K —

Qwen3.6 35B A3B

19.7 GB17.7 GB file

32K 20.0 GB · 128K 21.0 GB

IQ4_NL

Mixtral 8x7B Instruct v0.1

26.8 GB26.5 GB file

32K 30.9 GB · 128K —

Qwen3.6 35B A3B

20.6 GB18.0 GB file

32K 20.9 GB · 128K 21.9 GB

Q4_1

Mixtral 8x7B Instruct v0.1

26.8 GB29.3 GB file

32K 30.9 GB · 128K —

Qwen3.6 35B A3B

20.6 GB22.9 GB file

32K 20.9 GB · 128K 21.9 GB

Q4_K_S

Mixtral 8x7B Instruct v0.1

26.8 GB26.7 GB file

32K 30.9 GB · 128K —

Qwen3.6 35B A3B

20.6 GB20.9 GB file

32K 20.9 GB · 128K 21.9 GB

Q4_K_L

Mixtral 8x7B Instruct v0.1

not listed

Qwen3.6 35B A3B

22.4 GB22.7 GB file

32K 22.7 GB · 128K 23.7 GB

Q5_0

Mixtral 8x7B Instruct v0.1

29.8 GB32.2 GB file

32K 33.8 GB · 128K —

Qwen3.6 35B A3B

22.9 GB24.1 GB file

32K 23.1 GB · 128K 24.1 GB

Q5_1

Mixtral 8x7B Instruct v0.1

32.7 GB35.1 GB file

32K 36.7 GB · 128K —

Qwen3.6 35B A3B

25.1 GB26.1 GB file

32K 25.4 GB · 128K 26.4 GB

Q5_K_S

Mixtral 8x7B Instruct v0.1

32.7 GB32.2 GB file

32K 36.7 GB · 128K —

Qwen3.6 35B A3B

25.1 GB24.9 GB file

32K 25.4 GB · 128K 26.4 GB

Q5_K_L

Mixtral 8x7B Instruct v0.1

not listed

Qwen3.6 35B A3B

26.5 GB26.2 GB file

32K 26.7 GB · 128K 27.7 GB

BF16

Mixtral 8x7B Instruct v0.1

94.0 GB~93.4 GB file

32K 98.0 GB · 128K —

Qwen3.6 35B A3B

72.3 GB69.4 GB file

32K 72.5 GB · 128K 73.6 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 →

Qwen3.6 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 →

Specifications

Specifications of Mixtral 8x7B Instruct v0.1 and Qwen3.6 35B A3B
Spec	Mixtral 8x7B Instruct v0.1	Qwen3.6 35B A3B
Publisher	Mistral AI	Alibaba
Parameters	46.7B	36.0B
Active parameters	13B per token	4.7B per token
Architecture	MixtralForCausalLM	Qwen3_5MoeForConditionalGeneration
Context	32K tokens	256K tokens
Modalities	Chat	Vision, Function-calling
License	Apache 2.0	Apache 2.0
Released	Dec 2023	Apr 2026

Frequently Asked Questions

Which is better, Mixtral 8x7B Instruct v0.1 or Qwen3.6 35B A3B?

Qwen3.6 35B A3B leads llmrun Score 106.8 to 65.8; both fit 24 GB (Mixtral 8x7B Instruct v0.1 at IQ3_M, Qwen3.6 35B A3B at Q4_K_M); Qwen3.6 35B A3B is 1.6× faster on RTX 4090 (~151 vs ~92 tok/s). Choose Mixtral 8x7B Instruct v0.1 for also does chat; choose Qwen3.6 35B A3B for higher llmrun Score and stronger at reasoning.

Which needs less VRAM, Mixtral 8x7B Instruct v0.1 or Qwen3.6 35B A3B?

At Q4_K_M, Mixtral 8x7B Instruct v0.1 requires 28.6 GB while Qwen3.6 35B A3B needs 22.0 GB, making Qwen3.6 35B A3B 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 151 tok/s for Qwen3.6 35B A3B (Q4_K_M), so Qwen3.6 35B A3B is faster. Estimates, ±20%.

Can I run Mixtral 8x7B Instruct v0.1 or Qwen3.6 35B A3B on a 16 GB GPU?

Mixtral 8x7B Instruct v0.1 fits at IQ2_XXS; Qwen3.6 35B A3B fits at Q2_K.

Which has a longer context window, Mixtral 8x7B Instruct v0.1 or Qwen3.6 35B A3B?

Mixtral 8x7B Instruct v0.1 supports 32,768 tokens and Qwen3.6 35B A3B supports 262,144 tokens.