Qwen3.5-122B Heretic GGUF on Hugging Face

🔑 Enhanced Key Takeaways

• •Qwen3.5-122B-A10B is a Mixture-of-Experts (MoE) model with 10B active parameters out of 122B total, designed for higher intelligence per compute than dense scaling[3][4].
• •Unsloth provides state-of-the-art Dynamic GGUF quantizations for Qwen3.5 models, achieving 99.9% KL Divergence on benchmarks with over 150 tests and 9TB of artifacts[2][3].
• •The model series, including 122B-A10B, supports up to 1M context length in Flash variants and built-in tools, with strong practitioner feedback on local performance[4].

🛠️ Technical Deep Dive

• •MoE architecture: Qwen3.5-122B-A10B activates 10B parameters, balancing efficiency and performance[3][4].
• •Quantization insights: Unsloth benchmarks show ffn_up_exps, ffn_gate_exps optimal at 3-bit (iq3_xxs); avoid MXFP4 on attn_gate, attn_q, ssm_beta/alpha—prefer Q4_K[2].
• •GGUF updates: Fixed tool calling chat template bug across all quant types; 122B GGUFs pending re-upload as of Mar 2, 2026[2][3].
• •Hardware fit: Full 397B checkpoint ~807GB, but 3-bit GGUF fits 192GB RAM, 4-bit (MXFP4) on 256GB[3].

🔮 Future ImplicationsAI analysis grounded in cited sources

⏳ Timeline