Raspberry Pi 5

Hardware · Raspberry Pi

What AI models can the Raspberry Pi 5 (16 GB) run?

RAM
16.0 GB
Usable for models
13.6 GB
Memory bandwidth
17 GB/s
Runs models on
CPU cores
Released
2023
396 / 619 LLMs run Best: Gemma 4 12B 54 / 60 Image models run Best: FLUX 3 Image Klein 15 / 43 Video models run Best: LTX-Video 2B 65 / 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 13.6 GB of the 16.0 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 models85% (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 (16 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 (16 GB)

Best LLMs for the Raspberry Pi 5 (16 GB)

Quality Model Quant Memory Speed Runs
80Great quality (A) · 80 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 12BGoogle Q5_K_M 10.9 GB 1.2 tok/s Very slow
77Great quality (A) · 77 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. SenseNova Loop 9B PreviewSenseTime Q6_K 10.1 GB 1.3 tok/s Very slow
76Great quality (A) · 76 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.5 9BDeepReinforce Q6_K 9.9 GB 1.3 tok/s Very slow
75Great quality (A) · 75 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. Qwen3.5 9BAlibaba Q6_K 9.9 GB 1.3 tok/s Very slow
74Great quality (A) · 74 of 100: how capable the model is at Q6_K, whatever it runs on. Match score 76/100 (quality, fit, speed and memory use) sets the ranking. Ornith 1.0 9BDeepReinforce Q6_K 9.9 GB 1.3 tok/s Very slow
64Good quality (B) · 64 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. Gemma 4 26B-A4BGoogle Q2_K 12.4 GB 7.4 tok/s Slowtight fit
58Good quality (B) · 58 of 100: how capable the model is at Q3_K_M, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. Maple Preview (20B-A1B)DeepGrove Q3_K_M 11.7 GB 14.5 tok/s Runs welltight fit
61Good quality (B) · 61 of 100: how capable the model is at Q2_K, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. Raon-1 mini Preview (30B-A4B)KRAFTON Q2_K 13.3 GB 6.5 tok/s Slowtight fit
67Good quality (B) · 67 of 100: how capable the model is at Q5_K_M, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking. Nemotron 3.5 Bolt E4BNVIDIA Q5_K_M 7.5 GB 3.2 tok/s Slow
68Good quality (B) · 68 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. Phi-4 Reasoning Plus (14B)Microsoft Q4_K_M 12.3 GB 1.2 tok/s Very slowtight fit
68Good quality (B) · 68 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. Apriel 1.5 15B ThinkerServiceNow Q4_K_M 12.4 GB 1.2 tok/s Very slowtight fit
58Good quality (B) · 58 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. ERNIE 4.5 21B-A3B ThinkingBaidu Q3_K_M 12.9 GB 7.4 tok/s Slowtight fit

Best Image models for the Raspberry Pi 5 (16 GB)

Quality Model Quant Memory Speed Runs
90Excellent quality (A+) · 90 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 79/100 (quality, fit, speed and memory use) sets the ranking. FLUX 3 Image KleinBlack Forest Labs Q8 GGUF 12.8 GB 19.9 min Very slowtight fit
76Great quality (A) · 76 of 100: how capable the model is at FP8, whatever it runs on. Match score 78/100 (quality, fit, speed and memory use) sets the ranking. FLUX.2 [klein] 4BBlack Forest Labs FP8 10.2 GB 2.7 min Very slow
83Great quality (A) · 83 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. Z-Image TurboAlibaba (Tongyi) Q8 GGUF 13.0 GB 8.7 min Very slowtight fit
79Great quality (A) · 79 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-Image TurboBaidu Q4 GGUF 11.3 GB 11.6 min Very slow
81Great quality (A) · 81 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 75/100 (quality, fit, speed and memory use) sets the ranking. Z-ImageAlibaba (Tongyi) Q8 GGUF 13.0 GB 59.3 min Very slowtight fit
87Excellent quality (A+) · 87 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 74/100 (quality, fit, speed and memory use) sets the ranking. ERNIE-ImageBaidu Q8 GGUF 11.2 GB 80.5 min Very slowencoder unloaded after use

Best Video models for the Raspberry Pi 5 (16 GB)

Quality Model Quant Memory Speed Runs
49Fair quality (C) · 49 of 100: how capable the model is at FP8, whatever it runs on. Match score 65/100 (quality, fit, speed and memory use) sets the ranking. LTX-Video 2BLightricks FP8 10.8 GB 68.2 min Very slow
83Great quality (A) · 83 of 100: how capable the model is at FP8, whatever it runs on. Match score 64/100 (quality, fit, speed and memory use) sets the ranking. Bernini-R A14B (video generation + editing)ByteDance FP8 10.7 GB 42.6 h Very slowCPU offload
53Fair quality (C) · 53 of 100: how capable the model is at FP8, whatever it runs on. Match score 63/100 (quality, fit, speed and memory use) sets the ranking. Wan 2.1 T2V 1.3BAlibaba FP8 12.8 GB 10.9 h Very slowtight fit
44Fair quality (C) · 44 of 100: how capable the model is at FP8, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. CogVideoX 2BZhipu AI FP8 11.0 GB 2.7 h Very slow
76Great quality (A) · 76 of 100: how capable the model is at FP16, whatever it runs on. Match score 61/100 (quality, fit, speed and memory use) sets the ranking. HY-OmniWeaving (8.3B, unified video)Tencent FP16 10.7 GB 34.8 h Very slowCPU offload

Best Decision models for the Raspberry Pi 5 (16 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
90Excellent quality (A+) · 90 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. Qwen3 Reranker 4BAlibaba Q8_0 6.3 GB 23.3 s Very slow
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 2.6 GB 3.5 s Very slow
90Excellent quality (A+) · 90 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. Qwen3 Reranker 8BAlibaba Q8_0 10.7 GB 47.5 s Very slow
90Excellent quality (A+) · 90 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. Skywork Reward V2 Llama 3.1 8BSkywork Q8_0 10.4 GB 92.8 s Very slow
88Excellent quality (A+) · 88 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. zerank-2ZeroEntropy Q8_0 6.3 GB 23.3 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 2.6 GB 3.5 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

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.

Was this page helpful?