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AMD Ryzen AI MAX+ 395 (128GB system, 96GB GPU-accessible)

The AMD Ryzen AI MAX+ 395 (128GB system, 96GB GPU-accessible) provides 96 GB of memory with 256 GB/s bandwidth, supporting local inference via ROCm and Vulkan acceleration.

Memory

96 GB

Usable Memory Ceiling

96 GB

Bandwidth

256 GB/s

Max Inference Class

70B+ Models (Q4)

TDP

120W

VRAM Scaling by Context Length

Estimated memory requirements as context length increases. Curves crossing above the reference line indicate Out of Memory (OOM).

DeepSeek-R1 14B (14B)Muse Glimmer 30B (30B)Qwen2.5-72B (72B)GLM-5.3 Flash (313.3B (17.3B active))

Precision:

Best Models to Run on AMD Ryzen AI MAX+ 395 (128GB system, 96GB GPU-accessible)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on AMD Ryzen AI MAX+ 395 (128GB system, 96GB GPU-accessible).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#42

Qwen 3.8 Flash

176B (6B active)

INT4

50 tok/s

~1.3s

#48

Qwen 3.8 27B

27B

INT4
Q8
FP16

13 tok/s

8 tok/s

4 tok/s

~5.7s

~5.7s

~5.9s

#72

Sarvam-105B

106B (10.3B active)

INT4

32 tok/s

~2.9s

#83

K2 Horizon MoVA 36B A4B

36B (4B active)

INT4
Q8
FP16

58 tok/s

39 tok/s

23 tok/s

~1.1s

~1.1s

~1.1s

#88

Ling 3.0 Flash VL

124B (5.5B active)

INT4

51 tok/s

~2.1s

#93

Qwen3.5-27B

27B

INT4
Q8
FP16

13 tok/s

8 tok/s

4 tok/s

~5.7s

~5.7s

~5.9s

#97

Qwen3.5-122B-A10B

122B (10B active)

INT4

25 tok/s

~3.0s

#105

Sarvam-30B

32B (2.4B active)

INT4
Q8
FP16

76 tok/s

56 tok/s

35 tok/s

~779 ms

~784 ms

~795 ms

#106

Qwen3.6 35B A3B

35B (3B active)

INT4
Q8
FP16

68 tok/s

48 tok/s

29 tok/s

~908 ms

~914 ms

~928 ms

#107

Nemotron 3.5 Bolt 74B A9B

74B

INT4
Q8

5 tok/s

3 tok/s

~15.4s

~16.9s

#110

Muse Glimmer 30B

30B

INT4
Q8
FP16

12 tok/s

7 tok/s

4 tok/s

~6.3s

~6.4s

~6.5s

#111

MiMo V2 Flash

15B (309B active)

INT4
Q8
FP16

1 tok/s

1 tok/s

1 tok/s

~62.0s

~62.7s

~64.1s

#112

Phi-4 Reasoning Plus

14B

INT4
Q8
FP16

18 tok/s

12 tok/s

7 tok/s

~3.0s

~3.0s

~3.1s

#117

Gemma 4 26B A4B

25.2B (3.8B active)

INT4
Q8
FP16

62 tok/s

42 tok/s

24 tok/s

~1.0s

~1.0s

~1.0s

#119

GLM-4.5-Air

106B (12B active)

INT4

9 tok/s

~3.3s

#124

Ling 3.0 Flash

124B (5.1B active)

INT4

54 tok/s

~2.0s

#125

Qwen3.5-9B

9B

INT4
Q8
FP16

36 tok/s

22 tok/s

11 tok/s

~1.9s

~2.0s

~2.0s

#126

Qwen3.5-35B-A3B

35B (3B active)

INT4
Q8
FP16

68 tok/s

48 tok/s

29 tok/s

~908 ms

~914 ms

~928 ms

#128

K2 Horizon 7B

7B

INT4
Q8
FP16

45 tok/s

27 tok/s

14 tok/s

~1.5s

~1.5s

~1.6s

#135

Gemma 4 12B

11.95B

INT4
Q8
FP16

20 tok/s

14 tok/s

8 tok/s

~2.6s

~2.6s

~2.6s

Inference Capacity

Maximum model parameter class runnable by weight precision.

Context:

4-bit

Q4

70B+ Models

8-bit

Q8

70B Models

16-bit

FP16

32B Models

Fine-Tuning Capacity

Hardware capacity for local training and adapter fine-tuning.

Context Length:

QLoRA

4-bit

70B+ Models

LoRA

16-bit

70B Models

Full Parameter Training

7B-8B Models

Workload Recommendations

Guidance for optimal precision and operational ceilings on AMD Ryzen AI MAX+ 395 (128GB system, 96GB GPU-accessible).

Inference Sweet Spot

Suitable for 70B parameter models at Q4/Q8 with extended 32k context windows, or high-throughput batching of smaller dense architectures.

Bandwidth & Speed Profile

With 256 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 57 tok/s on an 8B Q4 model and 7 tok/s on a 70B Q4 model.

Frequently Asked Questions