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AMD RX 9070 (16GB)

The AMD RX 9070 (16GB) provides 16 GB of memory with 640 GB/s bandwidth, supporting local inference via ROCm and Vulkan acceleration.

Memory

16 GB

Usable Memory Ceiling

16 GB

Bandwidth

640 GB/s

Max Inference Class

14B Models (Q4)

TDP

220W

VRAM Scaling by Context Length

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

Gemma 3 270M (0.27B)NVIDIA Nemotron 3 Nano 30B-A3B (3.5B (30B active))Falcon3-10B (10B)Mixtral-8x7B-v0.1 (46.7B (7B active))

Precision:

Best Models to Run on AMD RX 9070 (16GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on AMD RX 9070 (16GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#48

Qwen 3.8 27B

27B

INT4

28 tok/s

~2.7s

#93

Qwen3.5-27B

27B

INT4

28 tok/s

~2.7s

#111

MiMo V2 Flash

15B (309B active)

INT4

3 tok/s

~27.7s

#112

Phi-4 Reasoning Plus

14B

INT4

41 tok/s

~1.2s

#117

Gemma 4 26B A4B

25.2B (3.8B active)

INT4

111 tok/s

~461 ms

#125

Qwen3.5-9B

9B

INT4
Q8

76 tok/s

48 tok/s

~801 ms

~809 ms

#128

K2 Horizon 7B

7B

INT4
Q8
FP16

91 tok/s

59 tok/s

30 tok/s

~629 ms

~635 ms

~758 ms

#135

Gemma 4 12B

11.95B

INT4
Q8

46 tok/s

29 tok/s

~1.1s

~1.3s

#140

Qwen3.5-4B

4B

INT4
Q8
FP16

126 tok/s

89 tok/s

54 tok/s

~372 ms

~375 ms

~383 ms

#143

GPT-OSS 20B

21B (3.6B active)

INT4

56 tok/s

~474 ms

#144

GLM-4V

9B

INT4
Q8

57 tok/s

38 tok/s

~806 ms

~882 ms

#150

NVIDIA Nemotron 3 Nano 30B-A3B

3.5B (30B active)

INT4
Q8
FP16

27 tok/s

16 tok/s

9 tok/s

~2.5s

~2.5s

~2.6s

#158

Granite 4.2 8B

8B

INT4
Q8

83 tok/s

53 tok/s

~714 ms

~721 ms

#159

Gemma 4 E4B

8B

INT4
Q8

83 tok/s

53 tok/s

~714 ms

~721 ms

#166

Phi-4

14B

INT4
Q8

54 tok/s

30 tok/s

~1.2s

~1.5s

#167

Gemma 3 27B

27B

INT4

28 tok/s

~2.7s

#178

OLMo 3 7B Think

7B

INT4
Q8

68 tok/s

49 tok/s

~633 ms

~638 ms

#179

DeepSeek-R1 14B

14B

INT4
Q8

56 tok/s

30 tok/s

~1.2s

~1.5s

#183

Ministral 3 14B

14B

INT4

41 tok/s

~1.2s

#186

Gemma 3 12B

12B

INT4
Q8

61 tok/s

36 tok/s

~1.1s

~1.2s

Inference Capacity

Maximum model parameter class runnable by weight precision.

Context:

4-bit

Q4

14B Models

8-bit

Q8

8B Models

16-bit

FP16

3B Models

Fine-Tuning Capacity

Hardware capacity for local training and adapter fine-tuning.

Context Length:

QLoRA

4-bit

14B Models

LoRA

16-bit

8B Models

Full Parameter Training

1B Models

Workload Recommendations

Guidance for optimal precision and operational ceilings on AMD RX 9070 (16GB).

Inference Sweet Spot

Optimal for 8B models across extended context (32k+). 14B models fit comfortably at Q4 precision with standard context.

Bandwidth & Speed Profile

With 640 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 142 tok/s on an 8B Q4 model and 17 tok/s on a 70B Q4 model.

Frequently Asked Questions