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Instinct MI250X (128GB)

The Instinct MI250X (128GB) provides 128 GB of memory with 3276 GB/s bandwidth, supporting local inference via ROCm and Vulkan acceleration.

Memory

128 GB

Usable Memory Ceiling

128 GB

Bandwidth

3276 GB/s

Max Inference Class

70B+ Models (Q4)

TDP

560W

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)OLMo 3.1 32B Instruct (32B)GLM-4.5-Air (106B (12B active))Llama 3.1 405B (405B)

Precision:

Best Models to Run on Instinct MI250X (128GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on Instinct MI250X (128GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#33

Qwen 3.8 27B

27B

INT4
Q8
FP16

136 tok/s

83 tok/s

45 tok/s

~877 ms

~882 ms

~892 ms

#41

Qwen 3.8 Flash

176B (6B active)

INT4

360 tok/s

~191 ms

#48

Agnes 3.0 Flash

33B

INT4
Q8
FP16

116 tok/s

70 tok/s

37 tok/s

~1.1s

~1.1s

~1.1s

#61

Sarvam-105B

106B (10.3B active)

INT4
Q8

262 tok/s

170 tok/s

~450 ms

~490 ms

#72

K2 Horizon MoVA 36B A4B

36B (4B active)

INT4
Q8
FP16

378 tok/s

301 tok/s

206 tok/s

~174 ms

~175 ms

~176 ms

#75

Ling 3.0 Flash VL

124B (5.5B active)

INT4
Q8

354 tok/s

239 tok/s

~321 ms

~378 ms

#83

Qwen3.5-27B

27B

INT4
Q8
FP16

136 tok/s

83 tok/s

45 tok/s

~877 ms

~882 ms

~892 ms

#84

Qwen3.5-122B-A10B

122B (10B active)

INT4
Q8

219 tok/s

144 tok/s

~461 ms

~543 ms

#92

Sarvam-30B

32B (2.4B active)

INT4
Q8
FP16

435 tok/s

371 tok/s

277 tok/s

~122 ms

~123 ms

~123 ms

#94

Qwen3.6 35B A3B

35B (3B active)

INT4
Q8
FP16

411 tok/s

341 tok/s

245 tok/s

~142 ms

~143 ms

~144 ms

#96

Muse Glimmer 30B

30B

INT4
Q8
FP16

125 tok/s

76 tok/s

41 tok/s

~973 ms

~978 ms

~989 ms

#100

Phi-4 Reasoning Plus

14B

INT4
Q8
FP16

170 tok/s

122 tok/s

74 tok/s

~464 ms

~466 ms

~472 ms

#101

MiMo V2 Flash

15B (309B active)

INT4
Q8
FP16

15 tok/s

8 tok/s

4 tok/s

~9.6s

~9.6s

~9.7s

#106

GLM-4.5-Air

106B (12B active)

INT4
Q8

91 tok/s

72 tok/s

~509 ms

~599 ms

#108

Gemma 4 26B A4B

25.2B (3.8B active)

INT4
Q8
FP16

392 tok/s

313 tok/s

216 tok/s

~159 ms

~160 ms

~162 ms

#109

Gemma 4 12B

11.95B

INT4
Q8
FP16

189 tok/s

138 tok/s

85 tok/s

~398 ms

~400 ms

~404 ms

#113

Qwen3.5-9B

9B

INT4
Q8
FP16

286 tok/s

198 tok/s

118 tok/s

~301 ms

~302 ms

~306 ms

#114

Qwen3.5-35B-A3B

35B (3B active)

INT4
Q8
FP16

411 tok/s

341 tok/s

245 tok/s

~142 ms

~143 ms

~144 ms

#114

Ling 3.0 Flash

124B (5.1B active)

INT4
Q8

364 tok/s

249 tok/s

~309 ms

~364 ms

#118

K2 Horizon 7B

7B

INT4
Q8
FP16

326 tok/s

234 tok/s

144 tok/s

~236 ms

~237 ms

~240 ms

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 Instinct MI250X (128GB).

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 3276 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 728 tok/s on an 8B Q4 model and 86 tok/s on a 70B Q4 model.

Frequently Asked Questions