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dan-omni-smolm2
sodan/dan-omni-smolm2
dan-omni-smolm2 is a text generation model from sodan. Use it when you need the model to write or continue text. The card lists the license as apache-2.0.
Ultra-lightweight model based on SmolLM2. Designed for extreme edge deployment — runs comfortably on any device with 512 MB RAM. Fastest in the Dan Omni family at 62 tok/s.
All-time downloads
107
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Repo size
271 MB
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0
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Repo makeup
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.gguf271 MB · 100%
At a glance
- Task
- Text Generation
- License
- apache-2.0
- Access
- Public
- Created
- Aug 27, 2026
- Updated
- Aug 27, 2026
- SHA
- 5e9e79b4
Try a prompt
Model card
From the Hugging Face model README
dan-omni-smolm2
Ultra-lightweight model based on SmolLM2. Designed for extreme edge deployment — runs comfortably on any device with 512 MB RAM. Fastest in the Dan Omni family at 62 tok/s.
Model Description
| Property | Value |
|---|---|
| Base Model | HuggingFace SmolLM2 |
| Fine-tuning | Full fine-tune on mobile instruction data |
| Context Length | 4096 tokens |
| Parameters | ~1.7B |
| File Size | 259 MB |
| RAM Usage | ~400 MB at inference |
System Prompt
You are dan, a helpful AI assistant for mobile devices. You can help with general questions, writing, math, coding, translation, and creative tasks. Keep answers concise and natural. Don't explain your architecture unless asked.
Benchmarks
Tested on Intel i9-9880H @ 2.30GHz, 16GB RAM, Ollama runtime.
| Category | Avg tok/s | Prompt tok/s | Tokens | Time |
|---|---|---|---|---|
| Reasoning | 60.0 | 545.1 | 26 | 0.4s |
| Coding | 62.3 | 545.1 | 43 | 0.7s |
| Creative Writing | 61.2 | 545.1 | 79 | 1.3s |
| Instruction Following | 62.4 | 545.1 | 56 | 0.9s |
| Math | 63.6 | 545.1 | 26 | 0.4s |
| General Knowledge | 63.6 | 545.1 | 26 | 0.4s |
| Average | 62.2 | 545.1 | 43 | 0.7s |
Comparison vs Competitors
| Model | Size | Speed | Quality | RAM |
|---|---|---|---|---|
| dan-omni-smolm2 | 259 MB | 62.2 tok/s | Medium | ~400 MB |
| SmolLM2-135M (base) | 140 MB | ~80 tok/s | Low | ~250 MB |
| LFM2-1.2B | ~0.7 GB | ~45 tok/s | Medium-High | ~1 GB |
| Gemma 4 E2B | ~1.4 GB | ~35 tok/s | High | ~2 GB |
| dan-omni-3b | 2.0 GB | 11.3 tok/s | High | ~2.5 GB |
Why dan-omni-smolm2? 5.5x faster than dan-omni-3b, 12x smaller. Fine-tuned for instruction following — not just a base model. Runs on Raspberry Pi, old phones, IoT devices.
Speed Comparison
| Model | Parameters | Size | Speed | Quality |
|---|---|---|---|---|
| dan-omni-3b | 3B | 2.0 GB | 11.3 tok/s | High |
| dan-omni-3b-q3s | 3B | 1.5 GB | 12.8 tok/s | Med-High |
| dan-omni-smolm2 | ~1.7B | 259 MB | 62.2 tok/s | Medium |
Dan Omni Model Family
| Model | Size | Speed | Use Case |
|---|---|---|---|
| dan-omni-3b | 3.5 GB | 11.3 tok/s | Full multimodal (text + vision) |
| dan-omni-3b-mobile | 1.2 GB | 9.8 tok/s | Compressed for mobile, 2K context |
| dan-omni-3b-q3s | 1.5 GB | 12.8 tok/s | Aggressive quantization |
| dan-omni-smolm2 | 259 MB | 62.2 tok/s | Ultralight, fastest |
| dan-omni-smolm2-v2 | 259 MB | 62.1 tok/s | Improved quality variant |
Usage
ollama pull sodan/dan-omni-smolm2
ollama run sodan/dan-omni-smolm2
./llama-cli -m dan-omni-smolm2.gguf -p "Hello" --ctx-size 4096
Intended Use
- Raspberry Pi / Arduino-class devices
- Old phones with limited RAM
- Real-time chat requiring <100ms response time
- Classification, simple Q&A, translation
- Prototyping and experimentation
Limitations
- Noticeably weaker reasoning than 3B models
- May struggle with multi-step math
- Shorter, simpler responses by nature
- Best paired with a larger model in a cascade
License
Apache 2.0
- Task
- Text Generation
- License
- apache-2.0
- Languages
- en
- Created
- Aug 27, 2026
- Updated
- Aug 27, 2026