MODEL PROFILE

DeepSeek-V4.1-Flash-1017-GSQ-agentic-strata

kaushikvira · DeepSeek-V4.1-Flash-1017-GSQ-agentic-strata

A **workload-calibrated mixed-precision** quantization of deepseek-ai/DeepSeek-V4.1-Flash-1017 (763.2B-parameter MoE — the largest DeepSeek V4.1 Flash variant), built for the **strata** engine (Xolotl fork). Every routed-expert projection is assigned its own precision tier (Q3_K / Q2_0 / ternary) from activation calibration on an agentic + coding corpus, so the artifact lands at a fixed **153 GiB** budget while keeping the sensitive experts at higher precision and pushing the least-sensitive ones to ternary (which strata runs on CPU). It is **not** a standard llama.cpp GGUF: the per-expert tier map, the engram memory layers, the expert `rank.bin`, and the DSpark speculative sidecar are all strata-specific. See Engines below. **All credit for the model itself goes to the authors below** — this artifact is a quantization of their work, with no fine-tuning of our own:

Text generationreasoninglicense:mit
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/30 03:19:36
OVERVIEW

Model overview

A **workload-calibrated mixed-precision** quantization of deepseek-ai/DeepSeek-V4.1-Flash-1017 (763.2B-parameter MoE — the largest DeepSeek V4.1 Flash variant), built for the **strata** engine (Xolotl fork). Every routed-expert projection is assigned its own precision tier (Q3_K / Q2_0 / ternary) from activation calibration on an agentic + coding corpus, so the artifact lands at a fixed **153 GiB** budget while keeping the sensitive experts at higher precision and pushing the least-sensitive ones to ternary (which strata runs on CPU). It is **not** a standard llama.cpp GGUF: the per-expert tier map, the engram memory layers, the expert `rank.bin`, and the DSpark speculative sidecar are all strata-specific. See Engines below. **All credit for the model itself goes to the authors below** — this artifact is a quantization of their work, with no fine-tuning of our own:

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

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PRICING & COST

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

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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。