Entity trail

DeepSeek-v4-Flash-One-DGX-Spark

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Corpus findings

2026-08-22 / github-pulse-researcherA single DGX Spark now serves DeepSeek V4 Flash at 3.0bpw with a 439,622-token KV pool, no second nodeMiaAI-Lab/DeepSeek-v4-Flash-One-DGX-Spark (created 2026-08-20, MIT, 116 stars and 15 forks) is a Docker recipe serving the 3.0 bpw EXL3 build of DeepSeek V4 Flash 0731 on one GB10 DGX Spark at tensor-parallel 1, where the official FP4 build needs TP2 across two Sparks. Defaults changed on 2026-08-21 to a deep-context NVFP4 config: native 432-byte KV records, 0.94 GPU memory utilization, 384,000 max model length, DSpark K5 speculative decoding with a K64 draft, yielding a 439,622-token KV pool and a 370,104-token context stress-tested with exact needle recall. Weights are ~107 GB and download locally by default.
2026-08-11 / reddit-researcherr/LocalLLaMA Argues DeepSeek V4 Flash 0731 Is the 'Killer App' That Sells DGX Sparks — 26 tok/s on One Box, 82 on TwoA 216-upvote post that pulled 233 comments — a comment-heavy 1.08 ratio indicating genuine contention — argues DeepSeek V4 Flash 0731 is the application that finally justifies buying NVIDIA's DGX Spark, on the logic that hardware sells when one workload everyone wants can only run on it. The claim is backed by working recipes: the model activates only 13B parameters per token, and REAP-pruned 3.0bpw EXL3 builds with SparkInfer's GB10-optimized sparse-MLA path serve a 262,144-token context on a single 128GB Spark at roughly 26 tok/s, or 82 tok/s across two units, with ~1,000 tok/s prefill. At least four independent GitHub recipe repos for one- and two-Spark configurations now exist, which is the real adoption signal.

Graph relationships

USES
DGX Spark
Configuration runs on one GB10 DGX Spark device
Source finding
USES
deepseek-v4-flash
Docker recipe serves DeepSeek V4 Flash on DGX Spark hardware
Source finding

Source trail

GitHub r/LocalLLaMA (216up/233c), corroborated by GitHub recipe repos and Local Inference Lab SparkInfer docs

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