This is the list of the SLMs I use on my Raspberry Pi5 (8GB RAM) with Ollama
Name | Size | Tag | Remark | Kind | URL | Good on Pi5 | Usable on Pi5 |
---|---|---|---|---|---|---|---|
codegemma:2b | 1.6GB | 2B | Fill-in-the-middle code completion | code | Link | ❌ | ✅ |
gemma:2b | 1.7GB | 2B | chat | Link | ❌ | ✅ | |
gemma2:2b | 1.6GB | 2B | chat | Link | ❌ | ✅ | |
all-minilm:22m | 46MB | 22M | Only Embeddings | embedding | Link | ✅ | ✅ |
all-minilm:33m | 67MB | 33M | Only Embeddings | embedding | Link | ✅ | ✅ |
deepseek-coder:1.3b | 776MB | 1.3B | Trained on both 87% code and 13% natural language | code | Link | ✅ | ✅ |
tinyllama | 638MB | 1.1B | chat | Link | ✅ | ✅ | |
tinydolphin | 637MB | 1.1B | chat | Link | ✅ | ✅ | |
phi3:mini | 2.4GB | 3B | chat | Link | ❌ | ✅ | |
phi3.5 | 2.2GB | 3B | chat | Link | ❌ | ✅ | |
granite-code:3b | 2.0GB | 3B | code | Link | ❌ | ✅ | |
qwen2.5:0.5b | 398MB | 0.5B | chat, tools | Link | ✅ | ✅ | |
qwen2.5:1.5b | 986MB | 1.5B | chat, tools | Link | ❌ | ✅ | |
qwen2.5:3b | 1.9GB | 3B | chat, tools | Link | ❌ | ✅ | |
qwen2.5-coder:1.5b | 986MB | 1.5B | code, tools | Link | ❌ | ✅ | |
qwen2:0.5b | 352MB | 0.5B | chat | Link | ✅ | ✅ | |
qwen2:1.5b | 934MB | 1.5B | chat | Link | ❌ | ✅ | |
qwen:0.5b | 395MB | 0.5B | chat | Link | ✅ | ✅ | |
qwen2-math:1.5b | 935MB | 1.5B | Specialized math language model | math | Link | ❌ | ✅ |
starcoder:1b | 726MB | 1B | Code generation model | code | Link | ✅ | ✅ |
starcoder2:3b | 1.7GB | 3B | code | Link | ❌ | ✅ | |
stablelm2:1.6b | 983MB | 1.6B | LLM trained on multilingual data in English, Spanish, German, Italian, French, Portuguese, and Dutch. | chat | Link | ✅ | ✅ |
stable-code:3b | 1.6GB | 3B | Coding model | code | Link | ❌ | ✅ |
rouge/replete-coder-qwen2-1.5b:Q8 | 1.9GB | 1.5B | Coding capabilities + non-coding data, fully cleaned and uncensored (mat+tool? to be tested) | code | Link | ❌ | ✅ |
dolphin-phi:2.7b | 1.6GB | 2.7B | uncensored | chat | Link | ❌ | ✅ |
CognitiveComputations/dolphin-gemma2:2b | 1.6GB | 2B | chat | Link | ❌ | ✅ | |
allenporter/xlam:1b | 873MB | 1B | tools | Link | ❌ | ✅ | |
sam4096/qwen2tools:0.5b | 352MB | 0.5B | tools | Link | ✅ | ✅ | |
sam4096/qwen2tools:1.5b | 935MB | 1.5B | tools | Link | ❌ | ✅ | |
mxbai-embed-large:335m | 670MB | 335M | Only Embeddings | embedding | Link | ✅ | ✅ |
nomic-embed-text:v1.5 | 274MB | 137M | Only Embeddings | embedding | Link | ✅ | ✅ |
yi-coder:1.5b | 866MB | 1.5B | Code | code | Link | ❌ | ✅ |
bge-m3 | 1.2GB | 567M | Only Embeddings | embedding | Link | ❌ | ✅ |
reader-lm:0.5b | 352MB | 0.5b | convert HTML to Markdown | conversion | Link | ✅ | ✅ |
reader-lm:1.5b | 935MB | 1.5b | convert HTML to Markdown | conversion | Link | ✅ | ✅ |
shieldgemma:2b | 1.7GB | 2b | evaluate the safety of text | safety | Link | ❌ | ✅ |
llama-guard3:1b | 1.6GB | 1b | evaluate the safety of text | safety | Link | ❌ | ✅ |
granite3-dense:2b | 1.6GB | 2b | chat, tools, embedding | Link | ❌ | ✅ | |
granite3-moe:1b | 822MB | 1b | chat, tools, embedding | Link | ✅ | ✅ | |
llama3.2:1b | 1.3GB | 1b | chat, tools | Link | ❌ | ✅ | |
llama3.2:3b | 2.0GB | 3b | chat, tools | Link | ❌ | ✅ | |
smollm:135m | 92MB | 135m | 🖐️ can run on a Pi 3A+ | 🤪 hard to control | chat | Link | ✅ |
smollm:360m | 229MB | 360m | 🖐️ can run well on a Pi 4 8GB | chat | Link | ✅ | ✅ |
smollm:1.7b | 991MB | 1.7b | chat | Link | ✅ | ✅ | |
smollm2:135m | 271MB | 135m | 🖐️ can run well on a Pi 4 8GB | chat, tools | Link | ✅ | ✅ |
smollm2:360m | 726MB | 360m | 🖐️ can run on a Pi 4 8GB | chat, tools | Link | ✅ | ✅ |
smollm2:1.7b | 1.8GB | 1.7b | chat, tools | Link | ❌ | ✅ |