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Instinct MI210 (64GB)

The Instinct MI210 (64GB) provides 64 GB of memory with 1638 GB/s bandwidth, supporting local inference via ROCm and Vulkan acceleration.

Memory

64 GB

Usable Memory Ceiling

64 GB

Bandwidth

1638 GB/s

Max Inference Class

70B+ 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).

DeepSeek-R1 14B (14B)Nemotron 3.5 Lightning 30B A3B (30B (3B active))Llama 3.1 70B (70B)Step 3.5 Flash (196.81B (11B active))

Precision:

Best Models to Run on Instinct MI210 (64GB)

Inference throughput, memory compatibility, and generation speeds for open-weights LLMs on Instinct MI210 (64GB).

Sort by:

Context:

KV Cache:

GPUs:

RankModelParametersPrecisionTPS (Approx.)TTFTCan Run

#33

Qwen 3.8 27B

27B

INT4
Q8
FP16

75 tok/s

44 tok/s

22 tok/s

~1.8s

~1.9s

~2.0s

#48

Agnes 3.0 Flash

33B

INT4
Q8
FP16

63 tok/s

37 tok/s

17 tok/s

~2.2s

~2.3s

~2.7s

#61

Sarvam-105B

106B (10.3B active)

INT4

155 tok/s

~1.0s

#72

K2 Horizon MoVA 36B A4B

36B (4B active)

INT4
Q8

263 tok/s

195 tok/s

~364 ms

~365 ms

#75

Ling 3.0 Flash VL

124B (5.5B active)

INT4

217 tok/s

~793 ms

#83

Qwen3.5-27B

27B

INT4
Q8
FP16

75 tok/s

44 tok/s

22 tok/s

~1.8s

~1.9s

~2.0s

#84

Qwen3.5-122B-A10B

122B (10B active)

INT4

118 tok/s

~1.1s

#92

Sarvam-30B

32B (2.4B active)

INT4
Q8
FP16

323 tok/s

257 tok/s

157 tok/s

~254 ms

~255 ms

~302 ms

#94

Qwen3.6 35B A3B

35B (3B active)

INT4
Q8

297 tok/s

229 tok/s

~297 ms

~298 ms

#96

Muse Glimmer 30B

30B

INT4
Q8
FP16

69 tok/s

40 tok/s

19 tok/s

~2.0s

~2.1s

~2.4s

#100

Phi-4 Reasoning Plus

14B

INT4
Q8
FP16

98 tok/s

67 tok/s

39 tok/s

~976 ms

~981 ms

~991 ms

#101

MiMo V2 Flash

15B (309B active)

INT4
Q8
FP16

8 tok/s

4 tok/s

2 tok/s

~20.2s

~20.3s

~20.5s

#108

Gemma 4 26B A4B

25.2B (3.8B active)

INT4
Q8
FP16

278 tok/s

205 tok/s

122 tok/s

~333 ms

~334 ms

~366 ms

#109

Gemma 4 12B

11.95B

INT4
Q8
FP16

110 tok/s

77 tok/s

45 tok/s

~836 ms

~840 ms

~849 ms

#113

Qwen3.5-9B

9B

INT4
Q8
FP16

182 tok/s

116 tok/s

65 tok/s

~631 ms

~635 ms

~641 ms

#114

Qwen3.5-35B-A3B

35B (3B active)

INT4
Q8

297 tok/s

229 tok/s

~297 ms

~298 ms

#114

Ling 3.0 Flash

124B (5.1B active)

INT4

226 tok/s

~762 ms

#118

K2 Horizon 7B

7B

INT4
Q8
FP16

216 tok/s

142 tok/s

81 tok/s

~495 ms

~497 ms

~502 ms

#126

Qwen3 Next 80B A3B

80B (79B active)

INT4

21 tok/s

~5.8s

#128

NVIDIA Nemotron 3 Nano 30B-A3B

3.5B (30B active)

INT4
Q8
FP16

66 tok/s

39 tok/s

21 tok/s

~2.0s

~2.0s

~2.0s

Inference Capacity

Maximum model parameter class runnable by weight precision.

Context:

4-bit

Q4

70B+ Models

8-bit

Q8

32B Models

16-bit

FP16

14B 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 MI210 (64GB).

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 1638 GB/s aggregate bandwidth, batch size 1 inference operates in a memory-bandwidth bound regime. Generates approximately 364 tok/s on an 8B Q4 model and 43 tok/s on a 70B Q4 model.

Frequently Asked Questions