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AMD RX 6900 XT (16GB)

The AMD RX 6900 XT (16GB) provides 16 GB of memory with 512 GB/s bandwidth, supporting local inference via ROCm and Vulkan acceleration.

Memory

16 GB

Usable Memory Ceiling

16 GB

Bandwidth

512 GB/s

Max Inference Class

14B Models (Q4)

TDP

300W

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 6900 XT (16GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on AMD RX 6900 XT (16GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#48

Qwen 3.8 27B

27B

INT4

23 tok/s

~8.5s

#93

Qwen3.5-27B

27B

INT4

23 tok/s

~8.5s

#111

MiMo V2 Flash

15B (309B active)

INT4

2 tok/s

~86.3s

#112

Phi-4 Reasoning Plus

14B

INT4

34 tok/s

~3.8s

#117

Gemma 4 26B A4B

25.2B (3.8B active)

INT4

97 tok/s

~1.4s

#125

Qwen3.5-9B

9B

INT4
Q8

64 tok/s

40 tok/s

~2.5s

~2.5s

#128

K2 Horizon 7B

7B

INT4
Q8
FP16

77 tok/s

50 tok/s

25 tok/s

~1.9s

~1.9s

~2.3s

#135

Gemma 4 12B

11.95B

INT4
Q8

38 tok/s

24 tok/s

~3.3s

~3.9s

#140

Qwen3.5-4B

4B

INT4
Q8
FP16

111 tok/s

76 tok/s

45 tok/s

~1.1s

~1.1s

~1.2s

#143

GPT-OSS 20B

21B (3.6B active)

INT4

47 tok/s

~1.4s

#144

GLM-4V

9B

INT4
Q8

47 tok/s

32 tok/s

~2.5s

~2.7s

#150

NVIDIA Nemotron 3 Nano 30B-A3B

3.5B (30B active)

INT4
Q8
FP16

22 tok/s

13 tok/s

7 tok/s

~7.8s

~7.8s

~7.9s

#158

Granite 4.2 8B

8B

INT4
Q8

70 tok/s

44 tok/s

~2.2s

~2.2s

#159

Gemma 4 E4B

8B

INT4
Q8

70 tok/s

44 tok/s

~2.2s

~2.2s

#166

Phi-4

14B

INT4
Q8

45 tok/s

25 tok/s

~3.8s

~4.5s

#167

Gemma 3 27B

27B

INT4

23 tok/s

~8.5s

#178

OLMo 3 7B Think

7B

INT4
Q8

57 tok/s

41 tok/s

~1.9s

~2.0s

#179

DeepSeek-R1 14B

14B

INT4
Q8

47 tok/s

25 tok/s

~3.8s

~4.5s

#183

Ministral 3 14B

14B

INT4

34 tok/s

~3.8s

#186

Gemma 3 12B

12B

INT4
Q8

51 tok/s

30 tok/s

~3.3s

~3.6s

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 6900 XT (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 512 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 114 tok/s on an 8B Q4 model and 13 tok/s on a 70B Q4 model.

Frequently Asked Questions