XingChen-AGI/Xing4.0-29B-Intent
archived · low-signalmodel
Xing4.0-29B-Intent is a schema-guided model for intent recognition and structured information extraction, developed from Xing4.0-29B-A4B, the Xing semantic large language model from China Telecom Artificial Intelligence Technology Co., Ltd. Mixture-of-experts, 31B total, 4B active (64 experts, 4 per token). Context: 256K tokens (config). License: apache-2.0.
- Org
- XingChen-AGI
- Released
- 2026-10-15
- Status
- archived · low-signal
- License
- apache-2.0 (permissive)
- Parameters
- 31.2B total, 4.0B active
- Architecture
- MoE · 64 experts, 4/token · Xing4_0ForCausalLM
- Context
- 262,144 tokens
- Task
- text-generation · text
- Signal
- 18 HF likes · 759 downloads
- Archived
- 2026-10-22 (no longer listed by the collector; stats as last seen)
Runs on
mixed: real files + estimate; need = weights + FP16 KV cache for 8K tokens + 1GB. A sizing calculation, not tested.
- Q4 ~20.1 GB (estimated size): 24GB GPU (3090 / 4090), 32GB GPU (5090), 24GB GPU (7900 XTX), Mac 36GB, CPU only, 32GB RAM (slow)
- Q8 ~34.6 GB (estimated size): 48GB GPU (RTX 6000 Ada / A6000), Mac 48GB, Mac 64GB (M1 Max), CPU only, 64GB RAM (slow)
- FP16 ~63.8 GB: 96GB GPU (RTX Pro 6000 Blackwell), 1× DGX Spark (128GB), 2× DGX Spark (256GB), Strix Halo 128GB unified (~96GB usable), Mac 96GB, Mac 128GB, Mac 192GB, Mac 256GB, Mac 512GB, CPU only, 128GB RAM (slow), CPU only, 256GB RAM (slow)
Links
First published here 2026-10-15 · updated 2026-10-22 · markdown · JSON