Model Releases
Qwen 3.8 flash next is based on Qwen 4 architecture, if the announced Qwen 4 27b is also the same architecture with n-grams does it mean I can actually have faster inference on a single 3090 without tweaking much?
I wish Qwen also released dataset and method to fully train a model ourselves but it is what it is. However, I come here with my stupid question because someone can answer it better. And will the mode
I wish Qwen also released dataset and method to fully train a model ourselves but it is what it is. However, I come here with my stupid question because someone can answer it better. And will the model still be an over thinker of faster inference will make up for that. submitted by /u/politefella0 [link] [comments]
Related
- Qwen3.8-Flash-Next on 2x3090 + DDR4: 17 → 25-29 t/s decode with the expert cache PR
- My Qwen3.8-Flash-Next recipe for single GB10/DGX Spark, uses Intel AutoRound int4 quant and vLLM, fp8 ngram table offloaded to local SSD or external RDMA server. At mtp=3 c=1, code is ~47.5t/s, json is ~60t/s. Prefix cache is ON.
- You can offload most of Qwen3.8-Flash-Next's KV cache to RAM with little decode slowdown
- [[megathread-qwen38-flash-next---release-day|[Megathread] Qwen3.8-Flash-Next - Release Day]]
Source: r/LocalLLaMA | 2026-09-26