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Our new blog post Smaller Models, Smarter Agents 🚀 https://huggingface.co/blog/yanghaojin/greenbit-3-bit-stronger-reasoning
DeepSeek’s R1-0528 proved that 8B can reason like 235B. Anthropic showed that multi-agent systems boost performance by 90%. The challenge? Both approaches burn massive compute and tokens.
💡 GreenBitAI cracked the code:
We launched the first 3-bit deployable reasoning model — DeepSeek-R1-0528-Qwen3-8B (3.2-bit).
✅ Runs complex multi-agent research tasks (e.g. Pop Mart market analysis)
✅ Executes flawlessly on an Apple M3 laptop in under 5 minutes
✅ 1351 tokens/s prefill, 105 tokens/s decode
✅ Near-FP16 reasoning quality with just 30–40% token usage
This is how extreme compression meets collaborative intelligence — making advanced reasoning practical on edge devices.
DeepSeek’s R1-0528 proved that 8B can reason like 235B. Anthropic showed that multi-agent systems boost performance by 90%. The challenge? Both approaches burn massive compute and tokens.
💡 GreenBitAI cracked the code:
We launched the first 3-bit deployable reasoning model — DeepSeek-R1-0528-Qwen3-8B (3.2-bit).
✅ Runs complex multi-agent research tasks (e.g. Pop Mart market analysis)
✅ Executes flawlessly on an Apple M3 laptop in under 5 minutes
✅ 1351 tokens/s prefill, 105 tokens/s decode
✅ Near-FP16 reasoning quality with just 30–40% token usage
This is how extreme compression meets collaborative intelligence — making advanced reasoning practical on edge devices.