The most open version is here! Qwen3.8-Flash-Next Strata Edition AI Large Language Model Local Deployment Tutorial｜MTP Acceleration, Works on 8GB Graphics Card
Please choose your quantization! Qwen3.8 27B Q8XL Q6XL Q5XL Q4XL IQ4XL YMQM YMQCFGM XLGSQRCO-IQ3S Test them one by one!
Qwen3.8-27b (Q5_K_XL/Q4_K_M) vs v4flash vs v4Pro
［ninfer v100X2］v100 achieves new glories! qwen3.8 27b nvfp4 2000t/s prefill, 115t/s decode
Qwen3.8 Flash Next IQ3_S Strata Local Deployment Test - Cost Less Than 30,000
[Most Comprehensive Test] Deploying Qwen3.8 27B nvfp4 on V100 with vLLM + dFlash2: Decode speed improved by 3x, Prefill speed improved by 15x
Qwen 3.8 Flash: Small model far exceeds Max, this time Qianwen didn’t cheat the score! AI six-category ability test
8G can run Qwen3.8 27B! Bonsai2-27B Review Report: Comparison with Qwen3.8-27B-GSQ-RCO
Four major Flash model tests: GLM-5.3-flash | Qwen3.8-flash | DeepSeek-V4-Flash | Gemini3.7-flash
qwen3.8-flash-next-iq3_s is no longer just a toy; it's truly within reach for those on a budget. Under 10,000 yuan, it's the closest thing to a production-ready local model.
Unbelievable, Qwen3.6 27B generation speed soared to 184t/s, how did I do it?
39.5 Tokens per second! Qianwen 3.8 27B 2080Ti 22B single-card local deployment speedup.
【Save Money Tips】A 500-yuan NVIDIA V100 16G can run vllm: qwen3.8 27b, with speeds up to 200 tokens/s
[Chinese Dub] Qwen3.8-Flash-Next: Video memory is no longer the only bottleneck for local large models
Qwen 4 (Suspected) Evaluation Report! How Capable Is It Really?
Qwen3.8-Flash-Next suddenly open-sourced! Running the 125B model locally, if you don't have enough VRAM, the hard drive can compensate, and it actually runs! Deployment hands-on test is here | Zero Degree Commentary
16G GPU runs Qwen3.8 27B smoothly! 80K+ context without losing intelligence: Qwen3.8 27B community modded version hits the charts!
2080ti, Strata local deployment Qwen3.8 Flash Next! Very awesome! Very powerful! Very big pitfall!
Local deployment of Qwen3.8-Flash-Next-Q4_K_M with 12+64, supporting 1M context
vLLM-Omni-v0.28.0 stunningly released
