Mistral Medium 3.5 128B vs Qwen3.8 27B

Qwen3.8 27B leads llmrun Score 122.0 to 102.1; only Qwen3.8 27B fits 24 GB (Q4_K_M); Mistral Medium 3.5 128B needs 41.3 GB even at its smallest quant.

Run Mistral Medium 3.5 128B in the cloud →

Model A · Mistral AI

Mistral Medium 3.5 128B

102.1llmrun Score

127.7B · 256K context · Other · Mar 2026

ChatFunctions

Model B · Alibaba

Qwen3.8 27B

122.0llmrun Score

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

VisionFunctions

Which should you choose?

Choose Mistral Medium 3.5 128B if you want…

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

Choose Qwen3.8 27B if you want…

Higher llmrun Score
122.0 vs 102.1
Stronger at reasoning
124.0 vs 101.5
Stronger at coding
119.0 vs 102.2
Ahead on the benchmarks
6 of 6 shared boards
Fits a 12 GB GPU
IQ3_XXS · 12 GB; Mistral Medium 3.5 128B needs 41.3 GB at its smallest quant
Fits a Mac 32 GB
Q4_K_M · 17.9 GB; Mistral Medium 3.5 128B needs 41.3 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%.

MemoryMistral Medium 3.5 128BQwen3.8 27B

8 GB

RTX 4060 · 8 GB tier

Mistral Medium 3.5 128B

Doesn't fit

smallest quant needs 41.3 GB

Qwen3.8 27B

Doesn't fit

smallest quant needs 8.8 GB

12 GB

RTX 3060 12GB · 12 GB tier

Mistral Medium 3.5 128B

Doesn't fit

smallest quant needs 41.3 GB

Qwen3.8 27B

IQ3_XXS · ~20 tok/s

12 GB · up to 16Kfits

16 GB

RTX 5060 Ti 16GB · 16 GB tier

Mistral Medium 3.5 128B

Doesn't fit

smallest quant needs 41.3 GB

Qwen3.8 27B

Q3_K_L · ~19 tok/s

15.4 GB · up to 16Kfits

24 GBreference

RTX 4090 · 24 GB tier

Mistral Medium 3.5 128B

Doesn't fit

smallest quant needs 41.3 GB

Qwen3.8 27B

Q4_K_M · ~38 tok/s

17.9 GB · up to 64Kfits

32 GB

RTX 5090 · 32 GB tier

Mistral Medium 3.5 128B

Doesn't fit

smallest quant needs 41.3 GB

Qwen3.8 27B

Q4_K_M · ~67 tok/s

17.9 GB · up to 256Kfits

48 GB

RTX A6000 · 48 GB tier

Mistral Medium 3.5 128B

IQ2_S · ~12 tok/s

46.1 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

Mistral Medium 3.5 128B

Doesn't fit

smallest quant needs 41.3 GB

Qwen3.8 27B

Q4_K_M · ~5 tok/s

17.9 GB · up to 128Kfits

Mac 64 GB

Mac Studio M4 Max · Macs

Mistral Medium 3.5 128B

IQ3_S · ~7 tok/s

60.5 GB · up to 16K

Qwen3.8 27B

Q4_K_M · ~22 tok/s

17.9 GB · up to 256Kmore headroom

Mac 128 GB

Mac Studio M4 Max · Macs

Mistral Medium 3.5 128B

Q4_K_M · ~5 tok/s

82.8 GB · up to 128K

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

Mistral Medium 3.5 128B Qwen3.8 27B

Overall

Mistral Medium 3.5 128B

102.197–107

Qwen3.8 27B

122.0120–124

Coding

Mistral Medium 3.5 128B

102.296–108

Qwen3.8 27B

119.0113–125

Agents

Mistral Medium 3.5 128B

no data

Qwen3.8 27B

122.7116–129

Math

Mistral Medium 3.5 128B

no data

Qwen3.8 27B

117.5110–125

Science

Mistral Medium 3.5 128B

101.380–123

Qwen3.8 27B

111.993–131

Reasoning

Mistral Medium 3.5 128B

101.593–110

Qwen3.8 27B

124.0121–127

Mistral Medium 3.5 128B · #53 of 106 open models · #20 of 62 that fit ≤96 GB

Qwen3.8 27B · #14 of 106 open models · #1 of 36 that fit 24 GB

Benchmarks

6 shared boards: Mistral Medium 3.5 128B leads 0, Qwen3.8 27B leads 6 · Benchmarks imported Nov 2026

BoardMistral Medium 3.5 128BQwen3.8 27B

SciCode

Mistral Medium 3.5 128B

40.2%#36/72 open

Lab-reportedEpoch AI · Apr 2026

Qwen3.8 27B

46.6%#24/72 open

Lab-reportedEpoch AI · Aug 2026

CritPt

Mistral Medium 3.5 128B

0.0%#73/84 open

Lab-reportedEpoch AI · Apr 2026

Qwen3.8 27B

5.4%#20/84 open

Lab-reportedEpoch AI · Aug 2026

DTBench

Mistral Medium 3.5 128B

75.5%#30/70 open

Lab-reportedEpoch AI · Apr 2026

Qwen3.8 27B

88.0%#10/70 open

Lab-reportedEpoch AI · Aug 2026

LMCA

Mistral Medium 3.5 128B

26.1%#28/56 open

Lab-reportedEpoch AI · Apr 2026

Qwen3.8 27B

41.4%#7/56 open

Lab-reportedEpoch AI · Aug 2026

ProofBench

Mistral Medium 3.5 128B

9.0%#22/31 open

Lab-reportedEpoch AI · Apr 2026

Qwen3.8 27B

16.0%#19/31 open

Lab-reportedEpoch AI · Aug 2026

Surface Evolver Bench

Mistral Medium 3.5 128B

26.9%#12/15 open

Lab-reportedEpoch AI · Apr 2026

Qwen3.8 27B

45.0%#7/15 open

Lab-reportedEpoch AI · Aug 2026

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

LMArena Text

Mistral Medium 3.5 128B

1426.4#28/188 open

ArenaLMArena · Oct 2026

Qwen3.8 27B

1435.6#24/188 open

ArenaLMArena · Oct 2026

LMArena WebDev

Mistral Medium 3.5 128B

1264.0#50/55 open

ArenaLMArena · Oct 2026

Qwen3.8 27B

1589.8#11/55 open

ArenaLMArena · Oct 2026

Only Mistral Medium 3.5 128B (3)

Only Qwen3.8 27B (13)

VRAM by quantization

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

QuantMistral Medium 3.5 128BQwen3.8 27B

Q2_K

Mistral Medium 3.5 128B

55.3 GB46.6 GB file

32K 66.4 GB · 128K 102 GB

Qwen3.8 27B

12.6 GB10.8 GB file

32K 13.9 GB · 128K 19.3 GB

Q3_K_S

Mistral Medium 3.5 128B

56.9 GB54.4 GB file

32K 68.0 GB · 128K 103 GB

Qwen3.8 27B

12.9 GB12.7 GB file

32K 14.2 GB · 128K 19.6 GB

Q3_K_M

Mistral Medium 3.5 128B

63.3 GB60.6 GB file

32K 74.4 GB · 128K 110 GB

Qwen3.8 27B

14.3 GB13.4 GB file

32K 15.6 GB · 128K 21.0 GB

Q4_0

Mistral Medium 3.5 128B

64.9 GB71.0 GB file

32K 76.0 GB · 128K 111 GB

Qwen3.8 27B

14.6 GB~13.9 GB file

32K 16.0 GB · 128K 21.4 GB

Q4_K_M

Mistral Medium 3.5 128B

77.7 GB74.9 GB file

32K 88.7 GB · 128K 124 GB

Qwen3.8 27B

17.4 GB16.5 GB file

32K 18.8 GB · 128K 24.1 GB

Q5_K_M

Mistral Medium 3.5 128B

92.0 GB88.3 GB file

32K 103 GB · 128K 139 GB

Qwen3.8 27B

20.5 GB19.8 GB file

32K 21.9 GB · 128K 27.3 GB

Q6_K

Mistral Medium 3.5 128B

106 GB102.6 GB file

32K 117 GB · 128K 153 GB

Qwen3.8 27B

23.7 GB22.0 GB file

32K 25.0 GB · 128K 30.4 GB

Q8_0

Mistral Medium 3.5 128B

129 GB132.9 GB file

32K 140 GB · 128K 175 GB

Qwen3.8 27B

28.5 GB29.0 GB file

32K 29.9 GB · 128K 35.2 GB

18 more quants

IQ2_XXS

Mistral Medium 3.5 128B

36.2 GB34.9 GB file

32K 47.2 GB · 128K 82.7 GB

Qwen3.8 27B

8.4 GB7.3 GB file

32K 9.7 GB · 128K 15.1 GB

IQ2_XS

Mistral Medium 3.5 128B

39.4 GB43.4 GB file

32K 50.4 GB · 128K 85.9 GB

Qwen3.8 27B

9.1 GB9.1 GB file

32K 10.4 GB · 128K 15.8 GB

IQ2_S

Mistral Medium 3.5 128B

41.0 GB46.1 GB file

32K 52.0 GB · 128K 87.5 GB

Qwen3.8 27B

9.4 GB8.4 GB file

32K 10.8 GB · 128K 16.1 GB

IQ2_M

Mistral Medium 3.5 128B

44.1 GB44.1 GB file

32K 55.2 GB · 128K 90.7 GB

Qwen3.8 27B

10.1 GB10.5 GB file

32K 11.5 GB · 128K 16.8 GB

IQ3_XXS

Mistral Medium 3.5 128B

50.5 GB49.3 GB file

32K 61.6 GB · 128K 97.0 GB

Qwen3.8 27B

11.5 GB10.9 GB file

32K 12.9 GB · 128K 18.2 GB

Q2_K_S

Mistral Medium 3.5 128B

52.1 GB43.0 GB file

32K 63.2 GB · 128K 98.6 GB

Qwen3.8 27B

not listed

IQ3_XS

Mistral Medium 3.5 128B

53.7 GB54.9 GB file

32K 64.8 GB · 128K 100 GB

Qwen3.8 27B

12.2 GB10.4 GB file

32K 13.6 GB · 128K 18.9 GB

IQ3_S

Mistral Medium 3.5 128B

55.3 GB54.5 GB file

32K 66.4 GB · 128K 102 GB

Qwen3.8 27B

12.6 GB12.0 GB file

32K 13.9 GB · 128K 19.3 GB

IQ3_M

Mistral Medium 3.5 128B

58.5 GB59.5 GB file

32K 69.6 GB · 128K 105 GB

Qwen3.8 27B

13.3 GB14.9 GB file

32K 14.6 GB · 128K 20.0 GB

Q3_K_L

Mistral Medium 3.5 128B

66.5 GB67.0 GB file

32K 77.6 GB · 128K 113 GB

Qwen3.8 27B

15.0 GB14.1 GB file

32K 16.3 GB · 128K 21.7 GB

IQ4_XS

Mistral Medium 3.5 128B

69.7 GB67.1 GB file

32K 80.8 GB · 128K 116 GB

Qwen3.8 27B

15.7 GB14.3 GB file

32K 17.0 GB · 128K 22.4 GB

IQ4_NL

Mistral Medium 3.5 128B

72.9 GB70.9 GB file

32K 83.9 GB · 128K 119 GB

Qwen3.8 27B

16.4 GB17.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_1

Mistral Medium 3.5 128B

72.9 GB78.5 GB file

32K 83.9 GB · 128K 119 GB

Qwen3.8 27B

16.4 GB17.5 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_S

Mistral Medium 3.5 128B

72.9 GB71.2 GB file

32K 83.9 GB · 128K 119 GB

Qwen3.8 27B

16.4 GB15.4 GB file

32K 17.7 GB · 128K 23.1 GB

Q4_K_L

Mistral Medium 3.5 128B

79.3 GB79.6 GB file

32K 90.3 GB · 128K 126 GB

Qwen3.8 27B

17.8 GB18.8 GB file

32K 19.1 GB · 128K 24.5 GB

Q5_K_S

Mistral Medium 3.5 128B

88.8 GB86.2 GB file

32K 99.9 GB · 128K 135 GB

Qwen3.8 27B

19.9 GB18.7 GB file

32K 21.2 GB · 128K 26.6 GB

Q5_K_L

Mistral Medium 3.5 128B

93.6 GB92.1 GB file

32K 105 GB · 128K 140 GB

Qwen3.8 27B

20.9 GB21.5 GB file

32K 22.2 GB · 128K 27.6 GB

BF16

Mistral Medium 3.5 128B

256 GB250.1 GB file

32K 268 GB · 128K 303 GB

Qwen3.8 27B

56.3 GB54.7 GB file

32K 57.7 GB · 128K 63.0 GB

How to run each

Mistral Medium 3.5 128B

Ollama · Q4_K_M

$ollama run hf.co/unsloth/Mistral-Medium-3.5-128B-GGUF:Q4_K_M

All ways to run Mistral Medium 3.5 128B →

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 Mistral Medium 3.5 128B and Qwen3.8 27B
Spec	Mistral Medium 3.5 128B	Qwen3.8 27B
Publisher	Mistral AI	Alibaba
Parameters	127.7B	27.8B
Architecture	Mistral3ForConditionalGeneration	Qwen3_5ForConditionalGeneration
Context	256K tokens	256K tokens
Modalities	Chat, Function-calling	Vision, Function-calling
License	Other	Apache 2.0
Released	Mar 2026	Aug 2026

Frequently Asked Questions

Which is better, Mistral Medium 3.5 128B or Qwen3.8 27B?

Qwen3.8 27B leads llmrun Score 122.0 to 102.1; only Qwen3.8 27B fits 24 GB (Q4_K_M); Mistral Medium 3.5 128B needs 41.3 GB even at its smallest quant. Choose Mistral Medium 3.5 128B for also does chat; choose Qwen3.8 27B for higher llmrun Score and stronger at reasoning.

Which needs less VRAM, Mistral Medium 3.5 128B or Qwen3.8 27B?

At Q4_K_M, Mistral Medium 3.5 128B requires 77.7 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 Mistral Medium 3.5 128B or Qwen3.8 27B on a 16 GB GPU?

Mistral Medium 3.5 128B does not fit (smallest quant needs 41.3 GB); Qwen3.8 27B fits at Q3_K_L.

Which has a longer context window, Mistral Medium 3.5 128B or Qwen3.8 27B?

Mistral Medium 3.5 128B supports 262,144 tokens and Qwen3.8 27B supports 262,144 tokens.