Model

DeepSeek-V4.1-Flash-1017

Made by DeepSeek · License: MIT

A big model for chat and code. It runs on Ollama’s servers, not on your computer.

Will it run on my computer?

Yes. It runs on Ollama’s servers, so you only need Ollama and an internet connection. Nothing downloads.

Start it

Install Ollama from ollama.com/download.
Sign in to Ollama.
Open Terminal.
Paste this command:

ollama run deepseek-v4.1-flash:1017-cloud

What happens next

Nothing downloads. Type your message and press Enter.
Type /bye to stop.

If it breaks

The :cloud command fails or asks you to sign in.
Cloud models run on Ollama's servers, so Ollama needs your account before it will run them.
Sign in once, then run the command again.
```
ollama signin
```
Source: 1 · 2

Sizes and versions

Could I run it myself?

For the Unsloth UD-IQ1_S file (233 GB download).

64 GB+ Mac	Won't fit
32 GB graphics card	Won't fit
AMD Ryzen AI Max+ PC, 128 GB (graphics memory set to 96 GB)	Won't fit
128 GB Mac	Won't fit
256 GB Mac	Won't fit
512 GB Mac	Fits

This is our estimate from published download sizes. We did not test these ourselves.
Fits = download x 1.25 + 2 GB fits in usable memory. That leaves room for longer chats.
Tight = only download + 1.5 GB fits. Short chats work, but long chats or documents may spill onto the CPU and slow down.
Usable memory on a graphics card is all of its graphics memory.
On a Mac it is 2/3 of memory up to 32 GB and 3/4 at 64 GB+. By default macOS keeps part of memory away from the GPU. Apple says a 32 GB Mac gives the GPU 21 GB and a 64 GB Mac 48 GB.
On an AMD Ryzen AI Max+ PC with 128 GB, it is the graphics memory you set in AMD Software. AMD says you can set up to 96 GB.
Apple · AMD

START HERE Cloud only (no easy local)

STEP 1Install Ollama from ollama.com/download, open it and sign in (cloud models need a free Ollama account; heavy use is paid).

STEP 2Paste the command below in Terminal or PowerShell.

RUN

ollama run deepseek-v4.1-flash:1017-cloud

SIZENothing to download: it runs on Ollama's servers, not your computer

NEEDSAn internet connection and an Ollama account. Running it yourself means a 512 GB Mac or server GPUs (the smallest file is 233 GB).

NOTEYour chats go to Ollama's servers.

ADVANCEDWant it on your own machine? Big-Mac route: the mlx-community oQ quants (oQ2e is the smallest). GPU route: the NVFP4 build on vLLM (Blackwell, 4 GPUs). Both are in the details below.

SOURCEsource · checked 2026-10-19

Recommended quants

Official FP8 / MXFP4 weights (~763 GB repo)
deepseek-ai/DeepSeek-V4.1-Flash-1017
Server GPUs. The bundled inference/ folder is a readable reference implementation (TP8 with torchrun), not a production server.
NVFP4 (399.5 GiB)
LibertAIDAI/DeepSeek-V4.1-Flash-1017-NVFP4
Same layout as nvidia/DeepSeek-V4.1-Flash-NVFP4; routed experts transcoded bit-exactly, Engram tables lossy MXFP4 (cosine 0.9934). Blackwell, vLLM TP4.
mlx-community oQ4e-mtp (432 GB / 402.4 GiB)
mlx-community/DeepSeek-V4.1-Flash-1017-oQ4e-mtp
oMLX mixed precision, keeps native FP4/FP8 projections and quantizes only the Engram tables. Smaller oQ3e, oQ2.5e and oQ2e variants are also up.
mrfakename GGUF Q2_K (246 GiB) / Q3_K_M (323 GiB) / Q4_K_M (414 GiB) / Q8_0 (473 GiB)
mrfakename/DeepSeek-V4.1-Flash-1017-GGUF
Plain quants, no imatrix, text only. Needs the llama.cpp branch from ggml-org/llama.cpp#28696; mainline doesn't support V4.1 yet.
Unsloth Dynamic GGUF (UD-IQ1_S ~233 GB … UD-Q4_K_XL ~501 GB)
unsloth/DeepSeek-V4.1-Flash-1017-GGUF
Files published as of Oct 19 (was a WIP placeholder on Oct 17). Needs the llama.cpp #28696 branch; text + mmproj available.

Scores and how it compares

Independent score: Artificial Analysis Intelligence Index 45 (max), checked 2026-10-19 · source.

Arena (ranks our computer pages):

Arena WebDev 1664 ±14 (DeepSeek-V4.1-Flash-20261017 (Max))

Checked 2026-10-19.

Pick this if you want DeepSeek V4.1 Flash 1017 and are fine with your chats going to Ollama's servers. Artificial Analysis scores it 45, among the highest-scoring open models we track.

Skip this if you want everything to stay on your own computer. It is far too big for a home PC, so pick your computer to see the top-ranked model that fits yours.

Compare: Qwen3.8-27B · Pick your computer

BEST PICK ONDGX Spark 3x, 4x (at least one job)

Settings and apps

Chat template Caveats

Like V4.1-Flash, no Jinja chat template ships. DeepSeek provides a Python reference encoder (encoding/encoding.py with tests for thinking, numeric reasoning effort, tools and images) and the deepseek-recipe Rust/Python libraries.

Fix: Use a runtime that implements the DeepSeek V4.1 encoding (vLLM uses --tokenizer-mode deepseek_v41 in NVIDIA's command). Generic GGUF chat templates may be wrong.

Sampling settings

Official	`temp 1.0, top_p 1.0, max_tokens 256K or more, 1M context window`

Runtimes

vLLM	Works	NVIDIA's documented NVFP4 command (TP4, --tokenizer-mode deepseek_v41) applies to the LibertAIDAI NVFP4 repo. Tested hardware is GB300.
SGLang	Caveats	The MXFP4 Engram tables in the NVFP4 repo aren't supported in SGLang yet, per the uploader.
llama.cpp	Caveats	Not in mainline. Use the ggml-org/llama.cpp#28696 branch; keep Engram tables on CPU with -ot "engram_embd.weight=CPU". Text only.
Ollama	Caveats	Ollama library deepseek-v4.1-flash lists :cloud and :1017-cloud only as of Oct 19 — hosted, not local weights.
LM Studio	Unverified	No local LM Studio listing confirmed as of Oct 19.
MLX	Works	mlx-community oQ quants made with oMLX v0.7.1, including the MTP head.

Tool calling in agent tools

Claude Code (local endpoint)	Unverified	DeepSeek used the Claude Code harness for its Terminal-Bench 4.0 score.

Recipes

DeepSeek-V4.1-Flash-1017 on three or four DGX Sparks. By Mia's AI Lab.

DeepSeek-V4.1-Flash-1017 on four DGX Sparks (vLLM). By Tech2Wild.

Sources

MADE BYDeepSeek

LICENSEMIT · model page · checked 2026-10-19

RELEASED2026-10-17

CHECKED2026-10-19 · 6 sources

Updated DeepSeek Flash for reasoning, coding, agents, and images. Easiest today with Ollama Cloud. A full local install is a huge download with early tools.

Known issues

Sources checked

Spotted something wrong or a new fix? Email corrections to [email protected]. Corrections are reviewed before publishing.