NVIDIA RTX 4090

Headlines · 5

1. 6d
   Hobbyist boosts Strata decoding for Qwen3.8-Flash-Next

   A hobbyist running IQ3_S Qwen3.8-Flash-Next on Strata 0.1.43 with an RTX 4090, 48 GB RAM and a Ryzen 9 3900X reported 2,076-token prompt processing and an average decode rate of 95–105 tokens per second at a 200,000-token context. A separate grid-search result rose from 97 to 142 tokens per second with --adapt-async 1, --kv-resident 20480 and STRATA_ADAPT_LAG=2. The author also found that --ple-io ram, a large explicit --expert-cache and --no-prefill-borrow reduced throughput by 90%, 72% and 46%, respectively.

   r/LocalLLaMA · 🔥 0
2. 7d
   Lean-QwenFlash runs Qwen3.8-Flash-Next with low-memory NVMe offloading

   A developer reported that Lean-QwenFlash ran the 125B-parameter Qwen3.8-Flash-Next on an RTX 4090 with 16 GB of VRAM and 8 GB of allocated system RAM by directly offloading to an NVMe SSD. Using a 3.05 bpw configuration and a Q4 KV cache, the reported RTX 4090 results were 28–33 tokens per second for prose and 19–22 tokens per second for code at 8K context, with decode speeds of about 20.8 and 20.0 tokens per second at 100K and 262K context. An RTX 3080 Laptop test, with 16 GB of VRAM and 32 GB of RAM, reached about 18–21 tokens per second at 100K context. The developer also published setup instructions, model downloaders and packing scripts. The performance figures are self-reported in the original post.

   r/LocalLLaMA · 🔥 0
3. Oct 22
   WorldTUI trains a 360M model to simulate a terminal without executing commands

   Developer Simon Edwardsson fine-tuned Qwen2.5-Coder-0.5B into WorldTUI, a 360M-parameter model that predicts terminal screen changes from raw keypresses without a shell, filesystem or command execution. The model can imitate file creation, vim, tmux and other terminal interactions, but developer tests found unreliable filesystem behavior and limited success when combining familiar commands in new ways. A 208 MB int4 browser demo runs locally with WebGPU, while model weights were described as forthcoming.

   Hacker News 首页（100+ 分） · 🔥 0
4. Oct 18
   StreamingSwap brings real-time face swapping to 10-minute video streams

   A paper submitted to arXiv on 19 October 2026 presents StreamingSwap, a reference-guided flow-matching framework for real-time streaming video face swapping. The authors introduce a Joint Rec-ID Loss that balances explicit identity supervision and latent reconstruction according to noise level, plus Face-RoI Generation and Short-Context Rollout Training that cut the spatial tokens and temporal context needed per frame. They also release HumanFaceVid, described as 1,000 hours of cinematic training data with evaluation sets of 200 short and 200 long videos, and report competitive identity transfer and visual quality at 20 FPS on a single NVIDIA RTX 4090 with stable generation over videos up to 10 minutes long; those results are self-reported, with no independent measurement supplied.

   Hugging Face · Papers · 🔥 0
5. Oct 17
   Xolotl engine runs 552B DeepSeek-V4.1-Flash on a single RTX 4090, developer reports

   Reddit user indrasmirror released Xolotl, a Strata-based inference engine, claiming it runs the full 552B DeepSeek-V4.1-Flash on one gaming PC: a single RTX 4090 (24GB), a Ryzen 7 5700X, 90GB of DDR4 and an NVMe drive, with weights spread across VRAM, pinned RAM and NVMe and only the experts each token needs pulled in. The developer self-reports about 27 tok/s decode, 180–320 tok/s prefill, 512K context, and 21/21 HumanEval, 10/10 tool calls and 3/3 agentic bug-fix loops through the real server with thinking on; none of these figures has been independently verified. The post also says the same engine runs GLM-5.3-Flash, Qwen3.8-Flash-Next and Qwen3.8-27B, that a 152 GiB uncensored V4.1 quant is on Hugging Face, and that the 510GB DeepSeek-V4.1-Flash-1017 update will be abliterated and requantized within a couple of days.

   r/LocalLLaMA · 🔥 0

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