Performance
Performance Notes and Limitations
For Generative AI workloads, measured performance on Genio 520 may be slightly lower than on Genio 720.
This gap is primarily due to DRAM bandwidth differences between the two platforms and might affect:
Token generation speed for LLMs.
End-to-end latency for diffusion-based image generation.
Multimodal pipelines that exchange large intermediate tensors between subsystems.
Important
The tables in this section provide representative numbers only. To obtain the most accurate performance for a specific use case, developers must deploy and run the workload directly on the target platform under the intended system configuration.
Note
The following symbols are used in the performance tables below:
--: To be released.Q3/E: Support planned for Q3 (estimated).X: Platform does not support this model.
Unless otherwise noted, all models listed below are supported on both Android and Yocto OS. Models or sections explicitly marked Android-only are not available on Yocto.
LLM Performance Comparison
Model |
Genio 360 |
Genio 420 |
Genio 520 |
Genio 720 |
MT8875 |
MT8883 |
MT8893 |
|---|---|---|---|---|---|---|---|
Qwen3-0.6B |
318.66 / 14.22 |
420.38 / 21.44 |
526.43 / 23.04 |
535.94 / 22.93 |
– |
– |
– |
Qwen3-1.7B |
152.67 / 8.69 |
222.83 / 13.03 |
258.83 / 13.72 |
262.73 / 13.84 |
235.67 / 6.20 |
834.02 / 25.18 |
1069.16 / 23.42 |
Qwen3-4B |
73.21 / 3.53 |
105.18 / 6.87 |
126.12 / 7.30 |
125.58 / 7.25 |
– |
– |
– |
Qwen3-8B |
X |
65.04 / 4.58 |
79.95 / 4.77 |
80.17 / 4.76 |
– |
– |
– |
Qwen2.5-1.5B-Instruct |
199.70 / 12.21 |
294.22 / 17.89 |
340.29 / 18.99 |
337.06 / 19.25 |
406.94 / 17.13 |
763.66 / 20.16 |
1621.85 / 38.57 |
Qwen2.5-3B-Instruct |
94.62 / 6.71 |
132.30 / 9.98 |
161.19 / 10.38 |
163.23 / 10.64 |
220.32 / 9.60 |
502.05 / 19.32 |
751.06 / 20.87 |
Qwen2.5-7B-Instruct |
X |
57.79 / 4.61 |
69.71 / 4.86 |
69.47 / 4.73 |
83.07 / 4.13 |
184.73 / 6.89 |
471.95 / 11.74 |
gemma3-1B (Text Only) |
359.43 / 16.58 |
513.69 / 24.58 |
598.27 / 27.23 |
583.01 / 26.44 |
680.41 / 21.02 |
1125.16 / 38.87 |
– |
gemma3-4B (Text-Only) |
92.76 / 3.44 |
149.00 / 5.69 |
176.90 / 5.90 |
176.79 / 5.93 |
– |
– |
– |
llama3.2-1B-Instruct |
233.97 / 15.94 |
329.32 / 21.58 |
385.77 / 24.76 |
400.57 / 24.92 |
– |
1372.57 / 43.47 |
2093.61 / 61.14 |
llama3.2-3B-Instruct |
X |
120.17 / 9.92 |
153.84 / 10.26 |
153.56 / 10.36 |
– |
611.76 / 19.89 |
1022.95 / 25.05 |
llama3-8b |
X |
49.23 / 4.39 |
56.47 / 4.66 |
55.87 / 4.64 |
– |
128.36 / 6.53 |
426.13 / 11.51 |
MiniCPM-2B-sft-bf16-llama-format |
X |
168.67 / 5.82 |
153.14 / 6.48 |
194.79 / 7.69 |
– |
– |
886.72 / 22.28 |
Phi-3-mini-4k-instruct |
74.79 / 4.45 |
101.94 / 6.30 |
126.82 / 7.26 |
127.56 / 7.28 |
– |
– |
– |
Phi-3.5-mini-instruct |
77.82 / 3.27 |
111.01 / 5.30 |
136.84 / 6.09 |
136.63 / 6.29 |
– |
– |
– |
DeepSeek-R1-Distill-Qwen-1.5B |
183.94 / 7.60 |
298.68 / 11.19 |
341.88 / 11.70 |
331.12 / 11.62 |
– |
– |
1057.25 / 25.68 |
DeepSeek-R1-Distill-Qwen-7B |
X |
56.47 / 4.60 |
67.80 / 4.84 |
67.59 / 4.83 |
– |
– |
448.17 / 11.69 |
DeepSeek-R1-Distill-Llama-8B |
X |
X |
X |
36.65 / 4.58 |
– |
– |
425.79 / 11.36 |
VLM Performance Comparison
Model |
Genio 360 |
Genio 420 |
Genio 520 |
Genio 720 |
MT8875 |
MT8883 |
MT8893 |
|---|---|---|---|---|---|---|---|
Qwen3VL-2B |
0.66 / 120.62 / 13.2906 |
0.49 / 173.16 / 13.4803 |
0.42 / 124.25 / 13.7964 |
0.43 / 199.75 / 14.4286 |
– |
– |
– |
InternVL3-1B |
2.99 / 49.25 / 3.10 |
2.42 / 69.37 / 6.00 |
1.77 / 80.49 / 6.20 |
1.79 / 79.84 / 6.35 |
– |
– |
0.51 / 183.64 / 14.09 |
Speech Recognition Performance Comparison
Model |
Genio 360 |
Genio 420 |
Genio 520 |
Genio 720 |
MT8875 |
MT8883 |
MT8893 |
|---|---|---|---|---|---|---|---|
Whisper |
Q3/E |
Q3/E |
Q3/E |
Q3/E |
Q3/E |
Q3/E |
Q3/E |
Android-only Models
The following model categories are supported on Android only and are not available on Yocto.
LLM — Android-only Models
Model |
Genio 360 |
Genio 420 |
Genio 520 |
Genio 720 |
MT8875 |
MT8883 |
MT8893 |
|---|---|---|---|---|---|---|---|
llava1.5-7b-speculative-decoding |
X |
58.62 / 2.99 |
73.12 / 3.40 |
73.11 / 3.40 |
– |
138.76 / 4.46 |
267.98 / 6.78 |
medusa_v1_0_vicuna_7b_v1.5 |
X |
X |
X |
91.82 / 10.56 |
– |
– |
501.05 / 22.79 |
vicuna1.5-7b-tree-speculative-decoding-plus |
X |
X |
X |
84.90 / 12.65 |
– |
– |
454.58 / 22.72 |
Stable Diffusion Performance Comparison
Model |
Genio 360 |
Genio 420 |
Genio 520 |
Genio 720 |
MT8875 |
MT8883 |
MT8893 |
|---|---|---|---|---|---|---|---|
Stable Diffusion v2.1 base model with controlnet |
216219 / 143784 |
39995 / 38425 |
35480 / 30421 |
35461 / 30365 |
– |
– |
– |
Stable Diffusion v.1.5 controlnet |
65449 / 53267 |
43507 / 42111 |
34483 / 33057 |
33870 / 32763 |
– |
– |
– |
CLIP Performance Comparison
Model |
Genio 360 |
Genio 420 |
Genio 520 |
Genio 720 |
MT8875 |
MT8883 |
MT8893 |
|---|---|---|---|---|---|---|---|
img_encoder_proj_clip_vit_large_dynamic |
1362.52 / 435.94 |
619.67 / 421.55 |
488.69 / 314.31 |
473.82 / 309.29 |
– |
– |
358.61 / 51.14 |
img_encoder_proj_openclip_vit_big_g_dynamic |
14997.09 / 5177.00 |
6371.25 / 5221.64 |
12595.05 / 4092.66 |
4870.33 / 3974.65 |
– |
– |
1390.56 / 517.13 |
img_encoder_proj_openclip_vit_h_dynamic |
2440.64 / 1457.64 |
1760.07 / 1392.31 |
1376.49 / 1023.27 |
1331.19 / 1026.39 |
– |
– |
591.93 / 147.47 |
text_encoder_clip_vit_large |
755.48 / 65.62 |
408.53 / 58.81 |
366.14 / 44.80 |
297.77 / 42.24 |
– |
– |
308.72 / 18.94 |
text_encoder_openclip_vit_h |
1857.49 / 203.44 |
794.72 / 149.17 |
679.66 / 128.66 |
607.12 / 125.44 |
– |
– |
510.92 / 48.49 |
Per-platform Performance
Detailed per-model performance data for each platform: