Models/DeepSeek V4.1 Flash

Text / DeepSeek

DeepSeek V4.1 Flash

An open-weight model for reasoning, coding, agents, and image understanding. DeepSeek V4.1 Flash combines a 552B backbone with sparse activation and up to one million tokens of context. Choose the original checkpoint or a community uncensored variant below.

Verified sourceRepository opened Sep 10, 2026Source checked 10/24/2026

LOCALRENTED GPUOPEN WEIGHTS

Freshness 80 out of 100. Repository age: 59 days old, Sep 10, 2026. Measures age, not quality.

Popularity 87 out of 100. 1,911,780 downloads in 30 days; 4,887 lifetime likes. Checked Nov 7, 2026. Measures adoption, not quality.

What do these scores mean?

Two ways to compare models. Neither score measures answer quality, benchmark performance, or whether a model fits your machine.

Freshness · release age

A new release starts at 100. The score halves every 180 days: 100 × 2^(−age in days / 180). When the release date is unavailable, a repository date is a fallback—not proof of when the model was released. Missing dates stay unscored.

Check the date source

Popularity · adoption

Downloads over the past 30 days carry 80% of the score; lifetime likes carry 20%. Both use a logarithmic scale, capped at 10 million downloads and 100,000 likes. If likes are unavailable, downloads carry all the weight. Missing download statistics stay unscored.

round(80 × min(1, log10(1 + downloads) / 7) + 20 × min(1, log10(1 + likes) / 5))

Check the statistics source

Scores as of Nov 8, 2026. Statistics checked Nov 7, 2026. Statistics are marked for refresh after 72 hours.Full scoring method

WORKFLOWS FOR THIS MODEL 2

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AI agent

Review security with DeepSeek V4.1 Flash and Hermes

Connect Hermes to an uncensored DeepSeek V4.1 Flash API, review your own code, and save a report with evidence and suggested fixes. Choose Venice or Experiential Labs; no GPU rental is required.

Freshness 80 out of 100. Repository age: 59 days old, Sep 10, 2026. Measures age, not quality.

Hermes AgentOpenAI-compatible API

2 packagesmacOS / Windows / LinuxUncensored option

Open agent guide

Text

Run DeepSeek V4.1 Flash Uncensored with Strata

Run AtomicChat’s IQ2_XXS backbone with ISTA’s separate Engram table through Strata on Windows, Apple Silicon Mac, Linux or RunPod. Includes separate copyable commands, hardware guidance, browser verification and local/cloud API connections for tools.

Freshness 80 out of 100. Repository age: 59 days old, Sep 10, 2026. Measures age, not quality.

StrataHugging Face CLI

1 packagemacOS / Windows / LinuxUncensored option

Open setup guide

Open a guide for its software, hardware requirements, and setup steps.

COMMUNITY VARIANTS

Uncensored versions

DeepSeek V4.1 Flash · Uncensored FP8

By dealignai

Weight-level abliteration in the native FP8/FP4 checkpoint format. The maintainer documents a specialized SGLang deployment on 4× H200. Read its runtime requirements before renting hardware.

View on Hugging Face

DeepSeek V4.1 Flash · Abliterated

By distributedcognition

An alternative abliteration approach retaining the upstream checkpoint layout. Includes evaluation and SGLang serving notes. Hugging Face requires accepting the repository’s access conditions.

View on Hugging Face

DeepSeek V4.1 Flash · Uncensored GGUF

By Adolphsson

Quantizations derived from dealignai’s uncensored weights, from Q2_K through Q8_0. Intended for a specialized CPU llama.cpp fork and high-memory servers—not a standard desktop Ollama download. Download every shard for the chosen quantization.

View on Hugging Face

At a glance

Parameters: 552B backbone · 8B active prefill / 16B active decode
Architecture: Causal encoder-decoder · Mixture of experts
Context length: Up to 1,000,000 tokens · runtime and memory dependent
License: MIT
Software: DeepSeek reference inference, SGLang, Specialized llama.cpp fork (GGUF)

MY HARDWARE

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Best for

Reasoning over large documents and long conversations.
Coding and agent workloads with a compatible tool-calling runtime.
Understanding images alongside text.

Tradeoffs

8B/16B active parameters describe compute per token, not the memory needed to store the model.
The maximum context is a capability ceiling, not a promise of speed or fit on every machine.
Runtime support is evolving. Follow the exact checkpoint’s instructions rather than generic Hugging Face quick-start snippets.
Community uncensored variants modify the original weights; their reported results are not YouRunAI benchmarks.

Ways to run it

DeepSeek reference inference · Linux · multi-GPU

Start with the publisher’s conversion and inference instructions for the original weights. This page does not claim that a generic stock vLLM installation supports this architecture.

Official instructions

SGLang · community FP8 variants · Linux · multi-GPU server or rental

The maintainer reports a 4× H200 NVLink deployment. Use its DeepSeek V4.1-specific runtime, tensor/expert parallel settings, and parsers. Moving Engram tables to host memory requires roughly 200 GB of additional host RAM.

Official instructions

Specialized llama.cpp fork · uncensored GGUF · Linux · high-memory CPU server

The author documents a CPU-only runtime/deepseek41 fork and a 440 GB RAM reference system. Published weight sizes are approximately 271 GB (Q2_K), 352 GB (Q3_K_M), 426 GB (Q4_K_M), and 508 GB (Q8_0). Allow additional runtime and context memory; file sizes are not RAM recommendations.

Official instructions

Explore its uses

REASONINGCODINGAGENTSIMAGE UNDERSTANDINGLONG CONTEXTUNCENSORED VARIANTS

REFERENCE LIBRARY

Sources and files

Primary sources and files behind this model page.

4 SOURCES

01DeepSeek official model card, architecture, and inferencehuggingface.co 02dealignai uncensored FP8 — deployment and hardwarehuggingface.co 03distributedcognition abliterated — method and serving noteshuggingface.co 04Adolphsson uncensored GGUF — files and CPU runtimehuggingface.co

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MODEL SIZE27.36B

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Freshness 12 out of 100. Repository age: 560 days old, Apr 27, 2025. Measures age, not quality.

MODEL SIZE8.2B

LOCALRENTED GPU

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