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DeepSeek-V4.1-Flash-1017 (552B MoE + 196B Engram) in 148 GB, built to run on two RTX 3090s and 128 GB of RAM with exact routing. Runs on **dsx**, a Rust + CUDA engine made for this model. For the best quality on the same machine, use dsx-ud (KL 0.269, one 305 GB download). All four run on dsx and were measured on the same eval (Lucebox 1017, 8 x 1,024 tokens against the FP8 model's top-256 log-probs). Unsloth's GGUFs were measured in llama.cpp with the same token ids and metric (tool). They also carry the Engram table, quantized to IQ4_NL (110.6 GB); dsx reads it unquantized from the official shards.

Text generation
Input Text→ Output Text
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DeepSeek-V4.1-Flash-1017 (552B MoE + 196B Engram) in one 252 GB download for two RTX 3090s and 128 GB of RAM, with the routed experts in **T16**, dsx's own trellis format: exllamav3's bitshift trellis with a codebook made for desktop CPUs, quantized from DeepSeek's original weights. Runs on **dsx**, a Rust + CUDA engine for this model. The default package contains an IQ4_NL Engram table. The optional `q6k-engram` branch uses Q6_K instead; the quality measurements below identify the package used for each result. The quality and speed figures below belong to this model release and its recorded runtime. They are not a new measurement of every later kernel revision. See NVIDIA measurement status for the runtime settings and open correctness checks, and model release history for other packages.

Text generation
Input Text→ Output Text
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Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

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