ollama deepseek-r1 671b - Brave Search

ollama.com › library › deepseek-r1:671b

deepseek-r1:671b

DeepSeek-R1 has received a minor version upgrade to DeepSeek-R1-0528 for the 8 billion parameter distilled model and the full 671 billion parameter model. In this update, DeepSeek R1 has significantly improved its reasoning and inference ...

datacamp.com › tutorial › deepseek-r1-ollama

How to Set Up and Run DeepSeek-R1 Locally With Ollama | DataCamp

January 30, 2025 - Ollama offers a range of DeepSeek R1 models, spanning from 1.5B parameters to the full 671B parameter model. The 671B model is the original DeepSeek-R1, while the smaller models are distilled versions based on Qwen and Llama architectures.

Videos

How to Run Deepseek R1 Locally Using Ollama, Chatbox AI, and LM ...

January 25, 2025

Run DeepSeek R1 Models Locally with Ollama - YouTube

January 24, 2025

Qwen QwQ 32b Local AI on Ollama BETTER than Deepseek R1 671b?! ...

Install Ollama & Run DeepSeek AI Locally Offline | Fix "Max ...

February 16, 2025

How to Setup and Run DeepSeek-R1 Locally Using Ollama - YouTube

February 12, 2025

Running Deepseek-R1 671B without a GPU - YouTube

ollama.com › SIGJNF › deepseek-r1-671b-1.58bit

SIGJNF/deepseek-r1-671b-1.58bit

Unsloth's DeepSeek-R1 1.58-bit, I just merged the thing and uploaded it here. This is the full 671b model, albeit dynamically quantized to 1.58bits.

ollama.com › Huzderu › deepseek-r1-671b-1.73bit

Huzderu/deepseek-r1-671b-1.73bit

Unsloth’s DeepSeek-R1 671B 1.73-bit dynamic quantization, merged GGUF files for Ollama.

Digital Spaceport

digitalspaceport.com › how-to-run-deepseek-r1-671b-fully-locally-on-2000-epyc-rig

How To Run Deepseek R1 671b Fully Locally On a $2000 EPYC Server – Digital Spaceport

Holy cow you got here! Nice job, I am impressed! Click new chat in the upper left of the window. Deepseek-r1:671b should be there already. Give it a hello. Nice job! In conclusion, we installed a fully functional bare metal Ollama + OpenWEBUI setup. I am SURE there are a lot of other great runners out there like llama.cpp, exo, and vLLM but those will be separate guides when I get a decent handle on working them.

reddit.com › r/ollama › deepseek-r1 671b - windows 11

r/ollama on Reddit: deepseek-r1 671B - windows 11

October 9, 2024 -

Hi guys,
I got 2 questions:

1. How can i change the folder where models are downloaded / inserted to for ollama? Currently its the standard path on C i guess i want to change it to D.

ollama run deepseek-r1:671b ->

2. Will my PC be able to run it ?

Prozessor Intel(R) Core(TM) i7-14700KF 3.40 GHz

Installierter RAM 48,0 GB (47,8 GB verwendbar)

GTX 4080

There’s a bigger chance that I marry Margot Robbie as my second wife than there is of you being able to run this model on those system specs. With that being said — did you try running a quantized version of the model?

Not a chance of running it

ollama.com › emsi › deepseek-r1-671b-1.58bit

emsi/deepseek-r1-671b-1.58bit

| **Model** | **#Total Params** | **#Activated Params** | **Context Length** | **Download** | | :------------: | :------------: | :------------: | :------------: | :------------: | | DeepSeek-R1-Zero | 671B | 37B | 128K | [🤗 HuggingFace](https://huggingface.co/deepseek-ai/DeepSeek-R1-Zero) | | DeepSeek-R1 | 671B | 37B | 128K | [🤗 HuggingFace](https://huggingface.co/deepseek-ai/DeepSeek-R1) |

ollama.com › search

deepseek · Ollama Search

DeepSeek-R1 is a family of open reasoning models with performance approaching that of leading models, such as O3 and Gemini 2.5 Pro · 74.8M Pulls 35 Tags Updated 5 months ago

reddit.com › r/singularity › running deepseek-r1 671b locally with olama.

r/singularity on Reddit: Running DeepSeek-R1 671b locally with olama.

September 5, 2024 -

Seems like it works but is far from straightforward and you really need a beast of a local setup to run this well.

Yes, you need 10 H100s

Find elsewhere

Google Bing Mojeek

ori.co › blog › how-to-run-deepseek-r1

How to run DeepSeek R1 on a cloud GPU with Ollama | Ori

Distill the reasoning capability from DeepSeek-R1 to small dense models.To equip more efficient smaller models with R1-like reasoning capabilities, DeepSeek directly fine-tuned open-source models like Qwen and Llama using the 800k samples curated with DeepSeek-R1. Distillation transfers knowledge and capabilities of a large, teacher model ( in this case DeepSeek R1 671B) to a smaller, student model (such as the Llama 3.3 70B).

ollama.com › search

deepseek-r1 · Ollama Search

DeepSeek-R1 is a family of open reasoning models with performance approaching that of leading models, such as O3 and Gemini 2.5 Pro · 74.4M Pulls 35 Tags Updated 5 months ago

github.com › ollama › ollama › issues › 8667

deepseek-r1:671b Q4_K_M: error="model requires more system memory (446.3 GiB) than is available · Issue #8667 · ollama/ollama

January 29, 2025 - However, when I attempt to load the model using Ollama, I encounter an error indicating that the model requires more system memory (446.3 GiB) than is available (37.3 GiB). This is perplexing, given the MoE architecture’s supposed efficiency and the Q4 quantization. I came across a discussion where a user successfully ran the Q8_0 GGUF version of DeepSeek-R1 671B on a CPU-only system with 256GB of RAM.

Published Jan 29, 2025

snowkylin.github.io › blogs › a-note-on-deepseek-r1.html

A Note on DeepSeek R1 Deployment

This is a (minimal) note on deploying DeepSeek R1 671B (the full version without distillation) locally with ollama.

ollama.com › library › deepseek-r1:671b › blobs › 6e4c38e1172f

deepseek-r1:671b/license

deepseek-r1:671b · 48.2M Downloads Updated 1 week ago · thinking 1.5b 7b 8b 14b 32b 70b 671b · deepseek-r1:671b ... / license · 6e4c38e1172f · 1.1kB · MIT License · Copyright (c) 2023 DeepSeek · Permission is hereby granted, free of charge, to any person obtaining a copy ·

ollama.com › library › deepseek-r1

deepseek-r1:671b · 404GB · 160K ... 160K · Text · DeepSeek-R1 has received a minor version upgrade to DeepSeek-R1-0528 for the 8 billion parameter distilled model and the full 671 billion parameter model....

ollama.com › library › deepseek-r1:671b › blobs › 9801e7fce27d

deepseek-r1:671b/model

deepseek-r1:671b · 64.3M Downloads Updated 3 months ago · tools thinking 1.5b 7b 8b 14b 32b 70b 671b · deepseek-r1:671b ... / model · 9801e7fce27d · 404GB · Metadata · general.architecture · deepseek2 · deepseek2 · general.file_type · Q4_K_M · Q4_K_M ·

markaicode.com › home › ollama › how to install deepseek-r1 671b with ollama v0.9.2: complete step-by-step guide 2025

How to Install DeepSeek-R1 671B with Ollama v0.9.2: Complete Step-by-Step Guide 2025 | Markaicode

June 23, 2025 - Your laptop just became smarter than most data centers. DeepSeek-R1 671B delivers reasoning performance approaching O3 and Gemini 2.5 Pro, and you can run it locally with Ollama v0.9.2.

reddit.com › r/ollama › how to deploy deepseek-r1∶671b locally using ollama?

r/ollama on Reddit: How to deploy deepseek-r1∶671b locally using Ollama?

April 11, 2024 -

I have 8 A100, each with 40GB video memory, and 1TB of RAM. How to deploy deepseek-r1∶671b locally? I cannot load the model using the video memory alone. Is there any parameter that Ollama can configure to load the model using my 1TB of RAM? thanks

https://unsloth.ai/blog/deepseekr1-dynamic

ollama will automatically split model between VRAM/RAM according to its compute power weights. You can also control it with num_gpu param.

reddit.com › r/ollama › deepseek r1 671b on my local pc

r/ollama on Reddit: Deepseek r1 671b on my local PC

March 9, 2024 -

Hello everyone,

Two days ago, I turned night into day, and in the end, I managed to get R1 running on my local PC. Yesterday, I uploaded a video on YouTube showing how I did it: https://www.youtube.com/watch?v=O3Lk3xSkAdk

I don't post here often, so I'm not sure if sharing the link is okay—I hope it is.

The video is in German, but with subtitles, everyone should be able to understand it.
Be careful if you want to try this yourself! ;)

Update:

For those who don't feel like watching the video: The "trick" was using Windows' pagefile. I set up three of them on three different SSDs, which gave me around 750GB of virtual memory in total.

Loading the model and answering a question took my PC about 90 minutes.

A fun exercise, gloriously pointless. 👍

Did the same with the Q4_K_M and a NVMe, with a glorious token speed of ~0.1t/s.

7/10 would do again.

ollama.com › huihui_ai › deepseek-r1:671b

huihui_ai/deepseek-r1:671b

deepseek-r1 · 671b · 50 Pulls Updated 4 weeks ago · 671b · 3 Tags · Updated 4 weeks ago · 4 weeks ago · 93f8490a2eb1 · 244GB · model · archdeepseek2 · · · parameters671B · · · quantizationQ2_K · 244GB · params · { "stop": [ "<｜begin▁of▁sentence｜>", "<｜end▁of▁sentence｜>", 148B ·