Releases·Tool Release
sfxnz releases vLLM recipe to serve DeepSeek-V4.1-Flash EXL3 across two DGX Spark (GB10) nodes
A GitHub recipe by sfxnz documents serving DeepSeek-V4.1-Flash EXL3 2.0bpw via vLLM at tensor-parallel 2 across two NVIDIA DGX Spark (GB10) nodes. It matters to practitioners running large MoE models on unified-memory hardware, since native weights don't fit. The recipe covers networking, memory, and download specifics for multi-node setup.
22 engagement1 sourceThu, Sep 10, 2026, 11:21 PM
AI Overview
- sfxnz's GitHub recipe serves DeepSeek-V4.1-Flash at EXL3 2.0 bpw (MCG) tensor-parallel 2 across two DGX Spark GB10 nodes
- Native MXFP4/MXFP8 DeepSeek-V4.1-Flash weights total about 511 GB and exceed 2x Spark UMA capacity
- Pack revision 2.0bpw-mcg is about 334 GB per node; ~340 GB free disk, Docker, and passwordless SSH to the worker are required
- Engram weights stay on NVMe via DSV41_ENGRAM_DISK=1; NCCL_IB_HCA must be pinned because two of GB10's four HCAs are DOWN
- Thinking defaults to off; omitting chat_template_kwargs enables thinking at effort 50, and small max_tokens returns empty content
- Default recipe settings: HEAD_IP=10.100.8.1, WORKER_HOST=spark2, IFACE=enp1s0f1np1, HCA=rocep1s0f1
Related
Releases·Tool Release
vLLM v0.30.0 ships DeepSeek-V4.1-Flash support, weight-cache fast start, and watermarking in 762-commit release
The vLLM project released v0.30.0, featuring 762 commits from 315 contributors (104 new). The release adds support for DeepSeek-V4.1-Flash, GLM-5.3-Flash, Kimi K3, Qwen3.8-Flash-Next, and Cohere Compass, plus a persistent per-GPU weight-cache daemon for fast engine restarts, Gumbel-max watermarking, and the HiSparse host-resident KV tier.
The vLLM project released v0.30.0, featuring 762 commits from 315 contributors (104 new). The release adds support for DeepSeek-V4.1-Flash, GLM-5.3-Flash, Kimi K3, Qwen3.8-Flash-Next, and Cohere Compass, plus a persistent per-GPU weight-cache daemon for fast engine restarts, Gumbel-max watermarking, and the HiSparse host-resident KV tier.
0 engagement1 sourcegithubTue, Sep 22, 2026, 05:20 AM
Social·Community
Users report DSpark draft model slow with DeepSeek-V4-Flash on llama-server
Users testing DeepSeek-V4-Flash-0731 with llama-server report that the DSpark draft model delivers only 1-2 tokens per second, far slower than the MTP draft model's 30-40 t/s. They seek advice on configuring speculative decoding correctly, while another user asks how to free OS RAM when serving the model on 2x DGX Spark systems.
Users testing DeepSeek-V4-Flash-0731 with llama-server report that the DSpark draft model delivers only 1-2 tokens per second, far slower than the MTP draft model's 30-40 t/s. They seek advice on configuring speculative decoding correctly, while another user asks how to free OS RAM when serving the model on 2x DGX Spark systems.
030129 engagement3 sourcesredditSat, Aug 8, 2026, 12:00 AM
Social·Community
Users run DeepSeek V4 Flash on single GH200 with DSpark UVA offload
A user shares a reference setup for running DeepSeek-V4-Flash-0731 on a single NVIDIA GH200 using DSpark and UVA offload, since the 284B MoE model does not fit in 144GB HBM. The post credits prior work by u/TimAndTimi and u/Reddactor's blog series, and details the hardware and model specs.
A user shares a reference setup for running DeepSeek-V4-Flash-0731 on a single NVIDIA GH200 using DSpark and UVA offload, since the 284B MoE model does not fit in 144GB HBM. The post credits prior work by u/TimAndTimi and u/Reddactor's blog series, and details the hardware and model specs.
14 engagement1 sourceredditMon, Aug 17, 2026, 02:38 PM
Developments·Paper
Reddit post spotlights top Hugging Face daily papers: DeepSeek-V4.1-Flash KV cache compression, SoL-Pi, coding-agent harness study
The Hugging Face Daily Papers list for September 19, 2026 highlighted three papers: DeepSeek-V4.1-Flash's KV cache compression, an auto-research agent harness loop, and an empirical study of coding agent harness design. The set targets practitioners working on local LLMs and agent optimization.
The Hugging Face Daily Papers list for September 19, 2026 highlighted three papers: DeepSeek-V4.1-Flash's KV cache compression, an auto-research agent harness loop, and an empirical study of coding agent harness design. The set targets practitioners working on local LLMs and agent optimization.
1 engagement1 sourceredditSat, Sep 19, 2026, 05:58 AM
Social·Community
Users seek real-world benchmarks for 4-node DGX Spark clusters
A Reddit user asks for first-hand experience with four-node DGX Spark clusters versus two, focusing on real-world performance of upper-class prosumer LLMs like GLM 5.2/5.3 and DeepSeek V4F. The thread highlights a gap in coverage of high-end prosumer hardware and software stacks.
A Reddit user asks for first-hand experience with four-node DGX Spark clusters versus two, focusing on real-world performance of upper-class prosumer LLMs like GLM 5.2/5.3 and DeepSeek V4F. The thread highlights a gap in coverage of high-end prosumer hardware and software stacks.
43 engagement1 sourceredditSun, Aug 23, 2026, 03:29 PM