Raspberry Pi 5

Hardware · Raspberry Pi

What AI models can the Raspberry Pi 5 (8 GB) run?

RAM
8.0 GB
Usable for models
6.4 GB
Memory bandwidth
17 GB/s
Runs models on
CPU cores
Released
2023
287 / 619 LLMs run Best: Nemotron Labs Dory 1.0 4B 44 / 60 Image models run Best: FLUX 3 Image Klein 6 / 43 Video models run Best: AnimateDiff v3 (SD 1.5) 59 / 70 Decision models run Best: OpenAI Privacy Filter

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 6.4 GB of the 8.0 GB (what Linux leaves free for a model). No NPU. Raspberry Pi’s AI Kit and AI HAT+ (Hailo-8L, 13 TOPS; Hailo-8, 26 TOPS) run vision models only. The AI HAT+ 2 (Hailo-10H, 40 TOPS, with its own 8 GB) also runs a few 1.5B LLMs, but in CNX Software’s test it was slower than the Pi’s own CPU.

More about this hardware

MakerRaspberry Pi
TypeSingle-board computer or edge AI board
Share of memory for models80% (what Linux typically leaves free on a board this size)
ChipBroadcom BCM2712
AI acceleratorNo NPU. Raspberry Pi’s AI Kit and AI HAT+ (Hailo-8L, 13 TOPS; Hailo-8, 26 TOPS) run vision models only. The AI HAT+ 2 (Hailo-10H, 40 TOPS, with its own 8 GB) also runs a few 1.5B LLMs, but in CNX Software’s test it was slower than the Pi’s own CPU.
Boards with this chipRaspberry Pi 5 · Raspberry Pi 500 / 500+ · Compute Module 5
Memory typeLPDDR4X-4267, 32-bit
Bandwidth figure17.1 GB/s, the chip’s rated memory speed
Note4× Cortex-A76 at 2.4 GHz. llama.cpp and Ollama run on the CPU; the VideoCore VII GPU isn’t used for LLMs. Speeds assume the CPU reads about 60% of the memory’s rated 17 GB/s, in line with published llama.cpp results (roughly 11-21 tokens/s for Llama 3.2 1B and about 5 for 3B at Q4_K_M). Use the Active Cooler. The 1 GB version leaves too little memory for language models and isn’t listed.
Specificationswww.raspberrypi.com

Apps that run models well on the Raspberry Pi 5 (8 GB)

Linux on ARM boards

  1. OllamaOne command with Ollama’s own build of this model.
  2. LM StudioPoint-and-click: search, download and chat in one window.
  3. llama.cppUsually the first to support new model architectures.
  4. Docker Model RunnerHandy if you already work in Docker.

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

1 product with the Raspberry Pi 5 (8 GB)

Best LLMs for the Raspberry Pi 5 (8 GB)

Quality Model Quant Memory Speed Runs
67Good quality (B) · 67 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. Nemotron Labs Dory 1.0 4BNVIDIA Q6_K 4.8 GB 3.0 tok/s Slow
64Good quality (B) · 64 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Nanbeige4.2 3BBOSS Zhipin (Nanbeige) Q4_K_M 5.1 GB 4.2 tok/s Slow
66Good quality (B) · 66 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Nemotron 3.5 Bolt E4BNVIDIA Q4_K_M 6.1 GB 3.9 tok/s Slowtight fit
64Good quality (B) · 64 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Spark-X2.6 4BSparkLLM Q5_K_M 4.3 GB 3.5 tok/s Slow
57Good quality (B) · 57 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 73/100 (quality, fit, speed and memory use) sets the ranking. Ling 3.0 Tiny (8B-A1.3B)Ant Group (inclusionAI) Q4_K_M 6.2 GB 12.9 tok/s Runs welltight fit
64Good quality (B) · 64 of 100: how capable the model is at Q4_K_M, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 E4BGoogle Q4_K_M 6.1 GB 3.9 tok/s Slowtight fit
65Good quality (B) · 65 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. SenseNova Loop 9B PreviewSenseTime Q3_K_M 6.3 GB 2.3 tok/s Very slowtight fit
64Good quality (B) · 64 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.5 9BDeepReinforce Q3_K_M 6.1 GB 2.3 tok/s Very slowtight fit
63Good quality (B) · 63 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 9BAlibaba Q3_K_M 6.1 GB 2.3 tok/s Very slowtight fit
60Good quality (B) · 60 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 4BAlibaba Q5_K_M 4.7 GB 3.1 tok/s Slow
59Good quality (B) · 59 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. TMax 4BAi2 Q5_K_M 4.4 GB 3.4 tok/s Slow
63Good quality (B) · 63 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.0 9BDeepReinforce Q3_K_M 6.1 GB 2.3 tok/s Very slowtight fit

Best Image models for the Raspberry Pi 5 (8 GB)

Quality Model Quant Memory Speed Runs
84Great quality (A) · 84 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image KleinBlack Forest Labs Q4 GGUF 5.7 GB 21.8 min Very slowtight fit · encoder unloaded after use
76Great quality (A) · 76 of 100: how capable the model is at FP8, whatever it runs on. Match score 71/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4BBlack Forest Labs FP8 6.2 GB 2.9 min Very slowtight fit · encoder unloaded after use
76Great quality (A) · 76 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. MOSS-Image SFTOpenMOSS Q4 GGUF 5.4 GB 53.5 min Very slowencoder unloaded after use
78Great quality (A) · 78 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. Z-Image TurboAlibaba (Tongyi) Q4 GGUF 6.1 GB 9.5 min Very slowtight fit · encoder unloaded after use
76Great quality (A) · 76 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 68/100 (quality, fit, speed and memory use) sets the ranking. Z-ImageAlibaba (Tongyi) Q4 GGUF 6.1 GB 64.9 min Very slowtight fit · encoder unloaded after use
39Basic quality (D) · 39 of 100: how capable the model is at FP8, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking. SDXL TurboStability AI FP8 4.2 GB 25 s Runs well

Best Video models for the Raspberry Pi 5 (8 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 59/100 (quality, fit, speed and memory use) sets the ranking. AnimateDiff v3 (SD 1.5)Shanghai AI Lab FP16 4.7 GB 60.6 min Very slow
49Fair quality (C) · 49 of 100: how capable the model is at FP8, whatever it runs on. Match score 58/100 (quality, fit, speed and memory use) sets the ranking. LTX-Video 2BLightricks FP8 6.1 GB 71.6 min Very slowtight fit · encoder unloaded after use
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 50/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 5BZhipu AI FP8 5.9 GB 10.6 h Very slowtight fit · CPU offload
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 50/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 5B I2VZhipu AI FP8 6.1 GB 10.6 h Very slowtight fit · CPU offload
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 50/100 (quality, fit, speed and memory use) sets the ranking. Wan 2.1 T2V 1.3BAlibaba FP8 6.0 GB 14.2 h Very slowtight fit · CPU offload

Best Decision models for the Raspberry Pi 5 (8 GB)

Quality Model Quant Memory Speed Runs
78Great quality (A) · 78 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 85/100 (quality, fit, speed and memory use) sets the ranking. OpenAI Privacy FilterOpenAI Q8_0 2.4 GB 159 ms Runs well
86Excellent quality (A+) · 86 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3.5Jina AI Q8_0 2.0 GB 3.5 s Very slow
89Excellent quality (A+) · 89 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 81/100 (quality, fit, speed and memory use) sets the ranking. Qwen3 Reranker 4BAlibaba Q6_K 4.7 GB 23.2 s Very slow
84Great quality (A) · 84 of 100: how capable the model is at Q8_0, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. Jina Reranker v3Jina AI Q8_0 2.0 GB 3.5 s Very slow
87Excellent quality (A+) · 87 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 80/100 (quality, fit, speed and memory use) sets the ranking. zerank-2ZeroEntropy Q6_K 4.7 GB 23.2 s Very slow
80Great quality (A) · 80 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. GLiNER2.5 DecideFastino Q8_0 1.2 GB 1.5 s Very slow
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. Shieldstral 1.0 3BMistral AI Q8_0 5.4 GB 22.3 s Very slow
80Great quality (A) · 80 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. FRIDA-DecisionsSber AI Q8_0 1.7 GB 2.5 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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