Qwen3.8-Flash-Next
3 articles tagged with Qwen3.8-Flash-Next
Alibaba Releases Qwen3.8-Flash-Next: 125B-Parameter MoE Model Matches Larger Rivals at $0.16/$0.47 per Million Tokens
Alibaba's Qwen team released Qwen3.8-Flash-Next, a 125-billion-parameter mixture-of-experts model that activates just 6 billion parameters per token and previews architecture planned for Qwen4. The model outperforms the much larger Qwen3.7-Plus at roughly one-ninth the training cost and ships at $0.16 per million input tokens and $0.47 per million output tokens.
GLM-5.3-Flash and Qwen3.8-Flash-Next Appear on Hugging Face With No Model Cards or Benchmarks Yet Published
Three Hugging Face repositories tied to next-generation GLM and Qwen model lines have appeared online: zai-org/GLM-5.3-Flash, Qwen/Qwen3.8-Flash-Next, and a community GGUF quantization from unsloth. None currently ship with a completed model card, published benchmarks, or pricing.
Qwen3.8-Flash-Next Debuts with 125B-Parameter Hybrid Architecture, Previews Qwen4 Design
Qwen3.8-Flash-Next is an experimental preview of the architecture Alibaba's Qwen team plans to use for Qwen4, combining hybrid attention, gated residuals, and n-gram embeddings in a 125B-parameter model with only 6B activated per token. Unsloth has released Dynamic 3.0 GGUF quantizations for local inference.