Magistral Small 2506 vs Qwen3.6 35B A3B

Qwen3.6 35B A3B leads llmrun Score 106.8 to 88.7; both fit 24 GB at Q4_K_M; Qwen3.6 35B A3B is 3.4× faster on RTX 4090 (~151 vs ~44 tok/s).

Model A · Mistral AI

Magistral Small 2506

88.7llmrun Score

23.6B · 40K context · Apache 2.0 · Jun 2025

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 Magistral Small 2506 if you want…

Lighter on memory
14.9 vs 22.0 GB at Q4_K_M
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 88.7
Stronger at reasoning
103.7 vs 88.1
3.4× faster on RTX 4090
~151 vs ~44 tok/s
Longer context window
256K vs 40K tokens
Also does vision, function-calling
Magistral Small 2506 doesn't list it
Newer release
Apr 2026 vs Jun 2025

On your hardware

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

MemoryMagistral Small 2506Qwen3.6 35B A3B

8 GB

RTX 4060 · 8 GB tier

Magistral Small 2506

Doesn't fit

smallest quant needs 10.1 GB

Qwen3.6 35B A3B

Doesn't fit

smallest quant needs 10.4 GB

12 GB

RTX 3060 12GB · 12 GB tier

Magistral Small 2506

IQ2_M · ~27 tok/s

11.6 GB · up to 16K

Qwen3.6 35B A3B

IQ2_S · ~114 tok/s

11.7 GB · up to 32K

16 GB

RTX 5060 Ti 16GB · 16 GB tier

Magistral Small 2506

Q4_K_M · ~20 tok/stight

17.8 GB · up to 4K

Qwen3.6 35B A3B

IQ3_S · ~108 tok/s

15.7 GB · up to 32Kmore headroom

24 GBreference

RTX 4090 · 24 GB tier

Magistral Small 2506

Q4_K_M · ~44 tok/s

17.8 GB · up to 40K

Qwen3.6 35B A3B

Q4_K_M · ~151 tok/s

22 GB · up to 128Kfaster

32 GB

RTX 5090 · 32 GB tier

Magistral Small 2506

Q4_K_M · ~78 tok/s

17.8 GB · up to 40K

Qwen3.6 35B A3B

Q4_K_M · ~213 tok/s

22 GB · up to 256Kfaster

48 GB

RTX A6000 · 48 GB tier

Magistral Small 2506

Q4_K_M · ~34 tok/s

17.8 GB · up to 40K

Qwen3.6 35B A3B

Q4_K_M · ~125 tok/s

22 GB · up to 256Kfaster

Mac 32 GB

Mac Mini M4 · Macs

Magistral Small 2506

Q4_K_M · ~6 tok/s

17.8 GB · up to 40K

Qwen3.6 35B A3B

Q4_K_M · ~24 tok/s

22 GB · up to 256Kfaster

Mac 64 GB

Mac Studio M4 Max · Macs

Magistral Small 2506

Q4_K_M · ~26 tok/s

17.8 GB · up to 40K

Qwen3.6 35B A3B

Q4_K_M · ~64 tok/s

22 GB · up to 256Kfaster

Mac 128 GB

Mac Studio M4 Max · Macs

Magistral Small 2506

Q4_K_M · ~26 tok/s

17.8 GB · up to 40K

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

Magistral Small 2506 Qwen3.6 35B A3B

Overall

Magistral Small 2506

88.784–93

Qwen3.6 35B A3B

106.8104–110

Coding

Magistral Small 2506

no data

Qwen3.6 35B A3B

105.399–112

Math

Magistral Small 2506

no data

Qwen3.6 35B A3B

109.0104–114

Science

Magistral Small 2506

no data

Qwen3.6 35B A3B

110.1101–119

Reasoning

Magistral Small 2506

88.172–104

Qwen3.6 35B A3B

103.796–112

Magistral Small 2506 · #70 of 100 open models · #19 of 35 that fit 24 GB

Qwen3.6 35B A3B · #37 of 100 open models · #4 of 35 that fit 24 GB

Benchmarks

2 shared boards: Magistral Small 2506 leads 0, Qwen3.6 35B A3B leads 2 · Benchmarks imported Oct 2026

BoardMagistral Small 2506Qwen3.6 35B A3B

GPQA Diamond

Magistral Small 2506

56.1%#47/98 open

IndependentEpoch AI · Jun 2025

Qwen3.6 35B A3B

84.9%#21/98 open

IndependentEpoch AI · Apr 2026

AIME 2024/2025

Magistral Small 2506

30.0%#50/86 open

IndependentEpoch AI · Jun 2025

Qwen3.6 35B A3B

86.7%#20/86 open

IndependentEpoch AI · Apr 2026

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

Only Magistral Small 2506 (2)

ARC-AGI-20.0%
ARC-AGI5.0%

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.

QuantMagistral Small 2506Qwen3.6 35B A3B

Q2_K

Magistral Small 2506

10.7 GB8.9 GB file

32K 17.0 GB · 128K —

Qwen3.6 35B A3B

15.7 GB13.5 GB file

32K 15.9 GB · 128K 16.9 GB

Q3_K_S

Magistral Small 2506

11.0 GB10.4 GB file

32K 17.3 GB · 128K —

Qwen3.6 35B A3B

16.1 GB15.4 GB file

32K 16.4 GB · 128K 17.4 GB

Q3_K_M

Magistral Small 2506

12.2 GB11.5 GB file

32K 18.5 GB · 128K —

Qwen3.6 35B A3B

17.9 GB16.6 GB file

32K 18.2 GB · 128K 19.2 GB

Q4_0

Magistral Small 2506

12.5 GB13.5 GB file

32K 18.8 GB · 128K —

Qwen3.6 35B A3B

18.4 GB~18.0 GB file

32K 18.6 GB · 128K 19.6 GB

Q4_K_M

Magistral Small 2506

14.9 GB14.3 GB file

32K 21.2 GB · 128K —

Qwen3.6 35B A3B

22.0 GB22.1 GB file

32K 22.2 GB · 128K 23.2 GB

Q5_K_M

Magistral Small 2506

17.5 GB16.8 GB file

32K 23.8 GB · 128K —

Qwen3.6 35B A3B

26.0 GB26.5 GB file

32K 26.3 GB · 128K 27.3 GB

Q6_K

Magistral Small 2506

20.2 GB19.3 GB file

32K 26.5 GB · 128K —

Qwen3.6 35B A3B

30.0 GB29.3 GB file

32K 30.3 GB · 128K 31.3 GB

Q8_0

Magistral Small 2506

24.3 GB25.1 GB file

32K 30.6 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

Magistral Small 2506

7.2 GB6.5 GB file

32K 13.5 GB · 128K —

Qwen3.6 35B A3B

10.3 GB10.8 GB file

32K 10.5 GB · 128K 11.5 GB

IQ2_XS

Magistral Small 2506

7.8 GB7.2 GB file

32K 14.1 GB · 128K —

Qwen3.6 35B A3B

11.2 GB11.7 GB file

32K 11.4 GB · 128K 12.4 GB

IQ2_S

Magistral Small 2506

8.1 GB7.5 GB file

32K 14.4 GB · 128K —

Qwen3.6 35B A3B

11.6 GB11.9 GB file

32K 11.9 GB · 128K 12.9 GB

IQ2_M

Magistral Small 2506

8.7 GB8.1 GB file

32K 15.0 GB · 128K —

Qwen3.6 35B A3B

12.5 GB11.5 GB file

32K 12.8 GB · 128K 13.8 GB

IQ3_XXS

Magistral Small 2506

9.9 GB9.3 GB file

32K 16.1 GB · 128K —

Qwen3.6 35B A3B

14.3 GB13.2 GB file

32K 14.6 GB · 128K 15.6 GB

Q2_K_S

Magistral Small 2506

10.2 GB8.3 GB file

32K 16.4 GB · 128K —

Qwen3.6 35B A3B

14.8 GB12.2 GB file

32K 15.0 GB · 128K 16.0 GB

IQ3_XS

Magistral Small 2506

10.4 GB9.9 GB file

32K 16.7 GB · 128K —

Qwen3.6 35B A3B

15.2 GB17.1 GB file

32K 15.5 GB · 128K 16.5 GB

IQ3_S

Magistral Small 2506

10.7 GB10.4 GB file

32K 17.0 GB · 128K —

Qwen3.6 35B A3B

15.7 GB13.7 GB file

32K 15.9 GB · 128K 16.9 GB

IQ3_M

Magistral Small 2506

11.3 GB10.7 GB file

32K 17.6 GB · 128K —

Qwen3.6 35B A3B

16.6 GB17.8 GB file

32K 16.8 GB · 128K 17.8 GB

Q3_K_L

Magistral Small 2506

12.8 GB12.4 GB file

32K 19.1 GB · 128K —

Qwen3.6 35B A3B

18.8 GB17.8 GB file

32K 19.1 GB · 128K 20.1 GB

IQ4_XS

Magistral Small 2506

13.4 GB12.8 GB file

32K 19.7 GB · 128K —

Qwen3.6 35B A3B

19.7 GB17.7 GB file

32K 20.0 GB · 128K 21.0 GB

IQ4_NL

Magistral Small 2506

14.0 GB13.5 GB file

32K 20.3 GB · 128K —

Qwen3.6 35B A3B

20.6 GB18.0 GB file

32K 20.9 GB · 128K 21.9 GB

Q4_1

Magistral Small 2506

14.0 GB14.9 GB file

32K 20.3 GB · 128K —

Qwen3.6 35B A3B

20.6 GB22.9 GB file

32K 20.9 GB · 128K 21.9 GB

Q4_K_S

Magistral Small 2506

14.0 GB13.5 GB file

32K 20.3 GB · 128K —

Qwen3.6 35B A3B

20.6 GB20.9 GB file

32K 20.9 GB · 128K 21.9 GB

Q4_K_L

Magistral Small 2506

15.2 GB14.8 GB file

32K 21.5 GB · 128K —

Qwen3.6 35B A3B

22.4 GB22.7 GB file

32K 22.7 GB · 128K 23.7 GB

Q5_0

Magistral Small 2506

not listed

Qwen3.6 35B A3B

22.9 GB24.1 GB file

32K 23.1 GB · 128K 24.1 GB

Q5_1

Magistral Small 2506

not listed

Qwen3.6 35B A3B

25.1 GB26.1 GB file

32K 25.4 GB · 128K 26.4 GB

Q5_K_S

Magistral Small 2506

16.9 GB16.3 GB file

32K 23.2 GB · 128K —

Qwen3.6 35B A3B

25.1 GB24.9 GB file

32K 25.4 GB · 128K 26.4 GB

Q5_K_L

Magistral Small 2506

17.8 GB17.2 GB file

32K 24.1 GB · 128K —

Qwen3.6 35B A3B

26.5 GB26.2 GB file

32K 26.7 GB · 128K 27.7 GB

BF16

Magistral Small 2506

47.9 GB47.2 GB file

32K 54.2 GB · 128K —

Qwen3.6 35B A3B

72.3 GB69.4 GB file

32K 72.5 GB · 128K 73.6 GB

How to run each

Magistral Small 2506

Ollama · Q4_K_M

$ollama run hf.co/bartowski/mistralai_Magistral-Small-2506-GGUF:Q4_K_M

All ways to run Magistral Small 2506 →

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 Magistral Small 2506 and Qwen3.6 35B A3B
Spec	Magistral Small 2506	Qwen3.6 35B A3B
Publisher	Mistral AI	Alibaba
Parameters	23.6B	36.0B
Active parameters	—	4.7B per token
Architecture	MistralForCausalLM	Qwen3_5MoeForConditionalGeneration
Context	40K tokens	256K tokens
Modalities	Chat	Vision, Function-calling
License	Apache 2.0	Apache 2.0
Released	Jun 2025	Apr 2026

Frequently Asked Questions

Which is better, Magistral Small 2506 or Qwen3.6 35B A3B?

Qwen3.6 35B A3B leads llmrun Score 106.8 to 88.7; both fit 24 GB at Q4_K_M; Qwen3.6 35B A3B is 3.4× faster on RTX 4090 (~151 vs ~44 tok/s). Choose Magistral Small 2506 for lighter on memory and also does chat; choose Qwen3.6 35B A3B for higher llmrun Score and stronger at reasoning.

Which needs less VRAM, Magistral Small 2506 or Qwen3.6 35B A3B?

At Q4_K_M, Magistral Small 2506 requires 14.9 GB while Qwen3.6 35B A3B needs 22.0 GB, making Magistral Small 2506 the easier model to run on your local setup.

Which is faster on RTX 4090?

Estimated decode speed on RTX 4090 is about 44 tok/s for Magistral Small 2506 (Q4_K_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 Magistral Small 2506 or Qwen3.6 35B A3B on a 16 GB GPU?

Magistral Small 2506 fits at Q4_K_M; Qwen3.6 35B A3B fits at IQ3_S.

Which has a longer context window, Magistral Small 2506 or Qwen3.6 35B A3B?

Magistral Small 2506 supports 40,960 tokens and Qwen3.6 35B A3B supports 262,144 tokens.