mlx-community/Youtu-LLM-2B-4bit

Youtu-LLM-2B 4-bit MLX

MLX-optimized 4-bit quantized version of tencent/Youtu-LLM-2B for Apple Silicon.

Quick Start

pip install mlx-lm

mlx_lm.generate \
  --model mlx-community/Youtu-LLM-2B-4bit \
  --prompt "Hello, what can you do?" \
  --max-tokens 100

Model Details

• Base Model: tencent/Youtu-LLM-2B
• Parameters: 1.96B
• Quantization: 4-bit (4.5 bits/weight)
• Context: 128K tokens
• Architecture: Dense MLA (Multi-head Latent Attention)
• Framework: MLX (Apple Silicon optimized)

Performance (M3 Ultra)

Quant	Prompt	Generation	Memory
bf16	118 tok/s	112 tok/s	4.7GB
4-bit	202 tok/s	205 tok/s	1.3GB

Features

• Reasoning Mode: Uses <think> tags for Chain of Thought
• 128K Context: Long document understanding
• Agentic: Strong on SWE-Bench, GAIA benchmarks
• Edge-friendly: Runs on any Apple Silicon Mac

Benchmarks (vs Qwen3-4B)

Benchmark	Youtu-LLM-2B	Qwen3-4B
HumanEval	95.9%	95.4%
SWE-Bench	17.7%	5.7%
GAIA	33.9%	25.5%

Other Quantizations

• Full precision (4.4GB)
• 4-bit (1.2GB)

Technical Note

Converted using deepseek_v2 architecture mapping (compatible MLA implementation).

License

See original model license.