| Category | Chat Interfaces | LLM APIs & Inference |
| Pricing | Free (open-source) | Free tier available, pay-per-token for production |
| GitHub Stars | ✓ More stars | — |
| Platforms | macOS, Linux, Windows, Docker | Web |
| Key Features | - ✓ Multi-model
- ✓ Document chat
- ✓ Agents
- ✓ Custom tools
- ✓ Team management
| - ✓ LPU hardware — custom chips for inference, not repurposed GPUs
- ✓ GPT OSS 120B at 500 tok/s ($0.15/M input)
- ✓ GPT OSS 20B at 1000 tok/s ($0.075/M input)
- ✓ Llama 4 Scout 17B at 750 tok/s with 131K context + vision
- ✓ Qwen3-32B at 400 tok/s with 131K context
- ✓ Compound AI systems with web search + code execution
- ✓ Whisper transcription ($0.04-0.11/hour)
- ✓ OpenAI-compatible API — drop-in replacement
- ✓ Free developer tier: 250-300K TPM, 1K RPM
|
| Pros | - + All-in-one solution
- + Supports every major LLM
- + Built-in agents and RAG
- + Desktop app + Docker
- + Team/workspace management
| - + Fastest inference available (500-1000 tok/s)
- + Free tier with generous limits (250K+ tokens/min)
- + OpenAI-compatible API — swap one line of code
- + Latest open-source models (GPT OSS, Llama 4, Qwen3)
- + Compound AI for agentic workflows (search + code exec)
|
| Cons | - − Can be resource-heavy
- − Some features still in beta
- − UI could be more polished
- − Documentation gaps
| - − Cloud-only — cannot self-host LPU hardware
- − Rate limits on free tier (1K RPM)
- − Smaller model catalog than running locally via Ollama
|
| Tags | all-in-onechatragopen-source | inferencefastfreehardware |