Rockchip RK3566

Hardware · Rockchip

What AI models can the Rockchip RK3566 / RK3568 (4 GB) run?

RAM
4.0 GB
Usable for models
2.8 GB
Memory bandwidth
13 GB/s
Runs models on
CPU cores
Released
2021

Models run on the CPU cores here, so the memory’s speed and how fast those cores can read it set the pace: small models (about 1-4B) are usable, bigger ones are slow. We plan around 2.8 GB of the 4.0 GB (what Linux leaves free for a model). 0.8 TOPS NPU (about 1 TOPS on the RK3568) for small vision models through Rockchip’s RKNN toolkit.

More about this hardware

MakerRockchip
TypeSingle-board computer or edge AI board
Share of memory for models70% (what Linux typically leaves free on a board this size)
ChipRockchip RK3566
AI accelerator0.8 TOPS NPU (about 1 TOPS on the RK3568) for small vision models through Rockchip’s RKNN toolkit.
Boards with this chipRadxa ROCK 3A / 3C / ZERO 3 · Orange Pi 3B · Pine64 Quartz64 · FriendlyElec NanoPi R5S
Memory typeLPDDR4/LPDDR4X or DDR4 up to 3200 MT/s, 32-bit
Bandwidth figure12.8 GB/s, the chip’s rated memory speed
Note4× Cortex-A55 at 1.8 GHz (RK3566) or 2.0 GHz (RK3568), Mali-G52 2EE GPU, up to 8 GB. Entry level: small models only, at a few tokens per second. Four A55 cores can’t read memory at anything near its rated speed, so we assume 20% (estimate).
Specificationswww.cnx-software.com

Apps that run models well on the Rockchip RK3566 / RK3568 (4 GB)

For a typical model that fits in memory. Each model page picks the best app for that model on this hardware. All apps

Best LLMs for the Rockchip RK3566 / RK3568 (4 GB)

Quality Model Quant Memory Speed Runs
57Good quality (B) · 57 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM5 2BOpenBMB Q4_K_M 2.7 GB 1.7 tok/s Very slowtight fit
47Fair quality (C) · 47 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. LFM3 1.7BLiquid AI Q3_K_M 1.8 GB 3.3 tok/s Slow
46Fair quality (C) · 46 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking. Spark-X2.6 4BSparkLLM Q2_K 2.8 GB 1.7 tok/s Very slowtight fit
39Basic quality (D) · 39 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. MiniCPM-OCR 1.0 1.3BOpenBMB Q4_K_M 1.7 GB 3.4 tok/s Slow
42Fair quality (C) · 42 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. TMax 4BAi2 Q2_K 2.8 GB 1.7 tok/s Very slowtight fit
30Basic quality (D) · 30 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. Unlimited OCR 2 (3B-A0.6B)Baidu Q2_K 2.7 GB 11.5 tok/s Runs welltight fit
39Basic quality (D) · 39 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. PaddleOCR-VL 1.6 0.9BBaidu Q4_K_M 1.6 GB 4.5 tok/s Slow
41Fair quality (C) · 41 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. LFM2.5 2.6BLiquid AI Q4_K_M 2.6 GB 1.6 tok/s Very slowtight fit
41Fair quality (C) · 41 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. Jamba Reasoning 3BAI21 Labs Q4_K_M 2.8 GB 1.4 tok/s Very slowtight fit
38Basic quality (D) · 38 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 60/100 (quality, fit, speed and memory use) sets the ranking. TeleOCRXingChen-AGI Q4_K_M 2.6 GB 3.1 tok/s Slowtight fit
39Basic quality (D) · 39 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking. Jamba2 3BAI21 Labs Q4_K_M 2.7 GB 1.4 tok/s Very slowtight fit
28Basic quality (D) · 28 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 59/100 (quality, fit, speed and memory use) sets the ranking. Unlimited OCR (3B-A0.6B)Baidu Q2_K 2.7 GB 11.5 tok/s Runs welltight fit

Best Image models for the Rockchip RK3566 / RK3568 (4 GB)

Quality Model Quant Memory Speed Runs
28Basic quality (D) · 28 of 100: how capable the model is at FP16, whatever it runs on. Match score 54/100 (quality, fit, speed and memory use) sets the ranking. SD TurboStability AI FP16 2.6 GB 30 s Runs welltight fit · encoder unloaded after use
42Fair quality (C) · 42 of 100: how capable the model is at FP16, whatever it runs on. Match score 54/100 (quality, fit, speed and memory use) sets the ranking. Realistic Vision V5.1SG161222 FP16 2.5 GB 7.6 min Very slowtight fit · encoder unloaded after use
40Fair quality (C) · 40 of 100: how capable the model is at FP16, whatever it runs on. Match score 53/100 (quality, fit, speed and memory use) sets the ranking. DreamShaper 8Lykon FP16 2.5 GB 7.6 min Very slowtight fit · encoder unloaded after use
30Basic quality (D) · 30 of 100: how capable the model is at FP16, whatever it runs on. Match score 51/100 (quality, fit, speed and memory use) sets the ranking. LCM DreamShaper v7Tsinghua (LCM) FP16 2.5 GB 1.6 min Slowtight fit · encoder unloaded after use
50Fair quality (C) · 50 of 100: how capable the model is at FP16, whatever it runs on. Match score 51/100 (quality, fit, speed and memory use) sets the ranking. PixArt-Σ XL 1024PixArt FP16 2.3 GB 11.8 min Very slowCPU offload
35Basic quality (D) · 35 of 100: how capable the model is at FP16, whatever it runs on. Match score 50/100 (quality, fit, speed and memory use) sets the ranking. Stable Diffusion 1.5Stability AI / Runway FP16 2.5 GB 7.6 min Very slowtight fit · encoder unloaded after use

Best Video models for the Rockchip RK3566 / RK3568 (4 GB)

Quality Model Quant Memory Speed Runs
35Basic quality (D) · 35 of 100: how capable the model is at FP16, whatever it runs on. Match score 42/100 (quality, fit, speed and memory use) sets the ranking. AnimateDiff v3 (SD 1.5)Shanghai AI Lab FP16 2.6 GB 2.6 h Very slowtight fit · CPU offload

Best Decision models for the Rockchip RK3566 / RK3568 (4 GB)

Quality Model Quant Memory Speed Runs
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3.5Jina AI Q8_0 1.7 GB 25.9 s Very slow
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3Jina AI Q8_0 1.7 GB 25.9 s Very slow
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. GLiNER2.5 DecideFastino Q8_0 1.2 GB 11.4 s Very slow
81Great quality (A) · 81 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. mxbai-rerank-large v2Mixedbread Q6_K 2.1 GB 66.2 s Very slow
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. FRIDA-DecisionsSber AI Q8_0 1.7 GB 19.0 s Very slow
80Great quality (A) · 80 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 0.6BAlibaba Q8_0 1.7 GB 25.9 s Very slow
78Great quality (A) · 78 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. OpenAI Privacy FilterOpenAI Q8_0 2.4 GB 1.2 s Slowtight fit
76Great quality (A) · 76 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. Llama Prompt Guard 2 86MMeta Q8_0 1.0 GB 13.0 s Very slow

Best LLMs by task on this hardware Open in Model Finder

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.

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