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glm4.7-flash
Z.ai
GLM-4.7-Flash: a 30B-A3B MoE built for agentic coding. Only ~3B parameters active per token, so it runs at small-model speed.
- size
- 30B-A3B
- vram
- ~20 GB
- license
- MIT
83% of a 24 GB card
#code #agentic #moe
devstral2-small
Mistral AI
Devstral Small 2 (24B, 2512): Mistral's second-generation agentic coder, with a 256K context, under Apache-2.0.
- size
- 24B
- vram
- ~16 GB
- license
- Apache-2.0
67% of a 24 GB card
#code #agentic #tools
granite-4.0-h-small
IBM
32B-parameter long-context instruct model with improved instruction following and tool calling, finetuned from Granite-4.0-H-Small-Base.
- size
- 32B
- vram
- ~21 GB
- license
- Apache-2.0
88% of a 24 GB card
#chat #instruct #large
magistral-small-2509
Mistral AI
24B reasoning model built on Mistral Small 3.2 with SFT from Magistral Medium traces and RL; 128K context window.
- size
- 24B
- vram
- ~16 GB
- license
- Apache-2.0
67% of a 24 GB card
#reasoning
embeddinggemma-300m
300M-parameter open embedding model from Google, built from Gemma 3 and trained on 100+ languages; 768-dim output with Matryoshka truncation.
- size
- 300M
- vram
- ~2 GB
- license
- Gemma
8% of a 24 GB card
#embedding #small
qwen3-4b-instruct-2507
Alibaba Qwen
Updated Qwen3-4B non-thinking model with better instruction following, reasoning and coding; 256K native context, no think blocks.
- size
- 4B
- vram
- ~4 GB
- license
- Apache-2.0
17% of a 24 GB card
#chat #instruct #small
qwen3-coder
Alibaba Qwen
Qwen3-Coder 30B-A3B: an agentic coding MoE with 256K context that runs at small-model speed on one GPU.
- size
- 30B-A3B
- vram
- ~19 GB
- license
- Apache-2.0
79% of a 24 GB card
#code #agentic #moe
smollm3
Hugging Face
SmolLM3 3B: a fully open small model with switchable reasoning, multilingual output and long context. Its training recipe is published too.
- size
- 3B
- vram
- ~2.5 GB
- license
- Apache-2.0
10% of a 24 GB card
#small #reasoning #multilingual
gemma3n-e4b
Google's Gemma 3n E4B instruction-tuned model for low-resource devices, effective 4B parameters, 32K context; this GGUF is text-only.
- size
- E4B
- vram
- ~6 GB
- license
- Gemma
25% of a 24 GB card
#chat #instruct #small
mistral-small-3.2-24b
Mistral AI
Mistral Small 3.1 update with better instruction following, fewer repetitive outputs and more robust function calling; text and image input.
- size
- 24B
- vram
- ~17 GB
- license
- Apache-2.0
71% of a 24 GB card
#chat #instruct #vision
qwen3-embedding-4b
Qwen
Qwen3 text embedding model with 4B parameters, 32K context, 100+ languages and embedding dimensions up to 2560 (user-defined sizes).
- size
- 4B
- vram
- ~6 GB
- license
- Apache-2.0
25% of a 24 GB card
#embedding #small
devstral
Mistral AI & All Hands
Devstral Small 24B: built for agentic coding. It navigates a repo, edits files and runs tests, the way the ArcFlare agent and OpenCode work.
- size
- 24B
- vram
- ~16 GB
- license
- Apache-2.0
67% of a 24 GB card
#code #agentic #tools
outetts
OuteAI
OuteTTS 1.0 0.6B: a small TTS model in 14 languages that clones a voice from a clip.
- size
- 0.6B
- vram
- ~2 GB
- license
- Apache-2.0
8% of a 24 GB card
#tts #speech #voice-cloning
mellum
JetBrains
Mellum 4B: JetBrains' completion model. A base model built for fill-in-the-middle autocomplete, not chat.
- size
- 4B
- vram
- ~5 GB
- license
- Apache-2.0
21% of a 24 GB card
#code #autocomplete #fim
seed-coder
ByteDance Seed
Seed-Coder 8B: a strong small coding model, with a separate reasoning variant. MIT licensed.
- size
- 8B
- vram
- ~7 GB
- license
- MIT
29% of a 24 GB card
#code #small #reasoning
qwen3-0-6b
Alibaba Qwen
Qwen3 0.6B causal language model with switchable thinking and non-thinking modes, 32K context and 100+ languages.
- size
- 0.6B
- vram
- ~2 GB
- license
- Apache-2.0
8% of a 24 GB card
#chat #instruct #small
qwen3-1-7b
Alibaba Qwen
Qwen3 1.7B causal language model with switchable thinking and non-thinking modes, 32K context and 100+ languages.
- size
- 1.7B
- vram
- ~3 GB
- license
- Apache-2.0
13% of a 24 GB card
#chat #instruct #small
moondream
vikhyat
A tiny, fast vision-language model that runs almost anywhere — captioning and visual Q&A on the edge.
- size
- 1.8B
- vram
- ~3 GB
- license
- Apache-2.0
13% of a 24 GB card
#vision #small #captioning
hunyuan3d-2mini
Tencent Hunyuan
Hunyuan3D-2 mini turns a single image into a clean 3D mesh. 0.6B parameters — the smallest Hunyuan shape model, and the one to start with.
- size
- 0.6B
- vram
- ~5 GB
- license
- Tencent Hunyuan Community
21% of a 24 GB card
#3d #image-to-3d #mesh
mistral-small3.1
Mistral AI
Mistral Small 3.1 24B: fast general model with image understanding and 128K context, under Apache-2.0.
- size
- 24B
- vram
- ~16 GB
- license
- Apache-2.0
67% of a 24 GB card
#vision #chat #tools
gemma3-4b
Google's multimodal Gemma 3 4B instruction-tuned model: text and image input, text output, 128K context, 140+ languages.
- size
- 4B
- vram
- ~5 GB
- license
- Gemma
21% of a 24 GB card
#chat #instruct #vision
phi4-mini
Microsoft
Phi-4-mini 3.8B: strong maths and reasoning for its size, 128K context and function calling, under MIT.
- size
- 3.8B
- vram
- ~3 GB
- license
- MIT
13% of a 24 GB card
#small #math #tools
smolvlm2-2.2b-instruct
Hugging Face
Lightweight multimodal model that processes video, image and text inputs to generate text; about 5.2GB of GPU RAM for video inference.
- size
- 2.2B
- vram
- ~4 GB
- license
- Apache-2.0
17% of a 24 GB card
#vision #small
nomic-embed-text-v2-moe
Nomic AI
Multilingual mixture-of-experts text embedding model (475M total, 305M active) supporting about 100 languages with Matryoshka embeddings.
- size
- 475M
- vram
- ~2 GB
- license
- Apache-2.0
8% of a 24 GB card
#embedding #small
kokoro
hexgrad
Kokoro 82M: a tiny, fast TTS model with good preset voices. It runs on any GPU, or on the CPU.
- size
- 82M
- vram
- ~1 GB
- license
- Apache-2.0
4% of a 24 GB card
#tts #speech #small
smollm2-1-7b-instruct
Hugging Face
1.7B compact instruct model trained on 11T tokens with SFT and DPO; supports rewriting, summarization and function calling.
- size
- 1.7B
- vram
- ~3 GB
- license
- Apache-2.0
13% of a 24 GB card
#chat #instruct #small
llama3.2
Meta
Meta's 3B multilingual instruction-tuned text model, optimized for dialogue, agentic retrieval and summarization tasks.
- size
- 3B
- vram
- ~3 GB
- license
- Llama 3.2 Community
13% of a 24 GB card
#chat #instruct #small
llama3.2-1b
Meta
Meta's 1B multilingual instruction-tuned text model, optimized for dialogue, agentic retrieval and summarization tasks.
- size
- 1B
- vram
- ~2 GB
- license
- Llama 3.2 Community
8% of a 24 GB card
#chat #instruct #small
nomic-embed-text
Nomic AI
English text embedding model with Matryoshka representation learning for resizable embeddings; requires task instruction prefixes.
- size
- 137M
- vram
- ~2 GB
- license
- Apache-2.0
8% of a 24 GB card
#embedding #small
bge-m3
BAAI
Multi-functionality, multilingual (100+ languages) and multi-granularity embedding model handling inputs up to 8192 tokens.
- size
- 568M
- vram
- ~2 GB
- license
- MIT
8% of a 24 GB card
#embedding #small