MODEL PROFILE

DeepSeek-V4.1-Flash-1017-dsx-2bit

lxe · DeepSeek-V4.1-Flash-1017-dsx-2bit

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 generationlicense:mit
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/30 14:23:48
OVERVIEW

Model overview

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.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

Source prices & cost analysis

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Estimate monthly base token costs

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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Frequently asked questions

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Sources & traceability

许可证:mit。模型介绍与第三方评测均以原来源的具体版本和方法为准。