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AMD Ryzen AI 9 HX 370 (32GB system, 24GB GPU-accessible)

The AMD Ryzen AI 9 HX 370 (32GB system, 24GB GPU-accessible) provides 24 GB of memory with 90 GB/s bandwidth, supporting local inference via ROCm and Vulkan acceleration.

Memory

24 GB

Usable Memory Ceiling

24 GB

Bandwidth

89.6 GB/s

Max Inference Class

32B Models (Q4)

TDP

54W

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 3B (3B)Mistral-7B-v0.1 (7.3B)Kimi-VL-A3B-Instruct (16B (3B active))Nemotron 3.5 Bolt 74B A9B (74B)

Precision:

Best Models to Run on AMD Ryzen AI 9 HX 370 (32GB system, 24GB GPU-accessible)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on AMD Ryzen AI 9 HX 370 (32GB system, 24GB GPU-accessible).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#48

Qwen 3.8 27B

27B

INT4

5 tok/s

~28.1s

#83

K2 Horizon MoVA 36B A4B

36B (4B active)

INT4

22 tok/s

~6.0s

#93

Qwen3.5-27B

27B

INT4

5 tok/s

~28.1s

#105

Sarvam-30B

32B (2.4B active)

INT4

32 tok/s

~3.8s

#106

Qwen3.6 35B A3B

35B (3B active)

INT4

27 tok/s

~4.9s

#110

Muse Glimmer 30B

30B

INT4

4 tok/s

~31.2s

#111

MiMo V2 Flash

15B (309B active)

INT4
Q8

1 tok/s

1 tok/s

~307.7s

~336.3s

#112

Phi-4 Reasoning Plus

14B

INT4
Q8

6 tok/s

4 tok/s

~14.8s

~14.9s

#117

Gemma 4 26B A4B

25.2B (3.8B active)

INT4

25 tok/s

~5.0s

#125

Qwen3.5-9B

9B

INT4
Q8
FP16

14 tok/s

8 tok/s

4 tok/s

~9.6s

~9.6s

~10.6s

#126

Qwen3.5-35B-A3B

35B (3B active)

INT4

27 tok/s

~4.9s

#128

K2 Horizon 7B

7B

INT4
Q8
FP16

17 tok/s

10 tok/s

5 tok/s

~7.5s

~7.5s

~7.6s

#135

Gemma 4 12B

11.95B

INT4
Q8

7 tok/s

5 tok/s

~12.7s

~12.8s

#140

Qwen3.5-4B

4B

INT4
Q8
FP16

29 tok/s

17 tok/s

9 tok/s

~4.4s

~4.4s

~4.5s

#143

GPT-OSS 20B

21B (3.6B active)

INT4

11 tok/s

~4.8s

#144

GLM-4V

9B

INT4
Q8
FP16

10 tok/s

6 tok/s

3 tok/s

~9.6s

~9.7s

~10.6s

#150

NVIDIA Nemotron 3 Nano 30B-A3B

3.5B (30B active)

INT4
Q8
FP16

4 tok/s

2 tok/s

1 tok/s

~30.2s

~30.4s

~30.8s

#153

Qwen3-30B-A3B

30B (3B active)

INT4

29 tok/s

~4.4s

#158

Granite 4.2 8B

8B

INT4
Q8
FP16

15 tok/s

9 tok/s

5 tok/s

~8.5s

~8.6s

~8.7s

#159

Gemma 4 E4B

8B

INT4
Q8
FP16

15 tok/s

9 tok/s

5 tok/s

~8.5s

~8.6s

~8.7s

Inference Capacity

Maximum model parameter class runnable by weight precision.

Context:

4-bit

Q4

32B Models

8-bit

Q8

14B Models

16-bit

FP16

8B Models

Fine-Tuning Capacity

Hardware capacity for local training and adapter fine-tuning.

Context Length:

QLoRA

4-bit

32B Models

LoRA

16-bit

14B Models

Full Parameter Training

3B Models

Workload Recommendations

Guidance for optimal precision and operational ceilings on AMD Ryzen AI 9 HX 370 (32GB system, 24GB GPU-accessible).

Inference Sweet Spot

Optimized for 14B models at uncompressed or Q8 precision, and 32B models at Q4 with up to 32k context.

Bandwidth & Speed Profile

With 89.6 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 20 tok/s on an 8B Q4 model and 2 tok/s on a 70B Q4 model.

Frequently Asked Questions