---
title: "How close are DeepSeek R1 distill models to full R1 on coding tasks?"  
description: "How close are DeepSeek R1 distill models to full R1 on coding tasks?"  
author: "Anna Weber"  
published: 2026-10-17  
updated: 2026-10-17  
canonical: https://www.mindstick.com/forum/162510/how-close-are-deepseek-r1-distill-models-to-full-r1-on-coding-tasks  
category: "Model Evaluation"  
tags: ["DeepSeek", "R1", "Code Generation", "Model evaluation"]  
reading_time: 1 minute  

---

# How close are DeepSeek R1 distill models to full R1 on coding tasks?

I’m comparing the smaller **R1 distill models** for coding help and trying to decide whether running one locally is worth the trade-off. Most comparisons I’ve found focus on general reasoning scores, which don’t tell me much about debugging or making a careful change across several files.

For anyone who has tested both a distilled model and full R1 on real coding tasks, what differences stood out? I’m curious about correctness, how often the smaller models miss constraints, and whether a particular distillation size felt like a sensible balance.


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Original Source: https://www.mindstick.com/forum/162510/how-close-are-deepseek-r1-distill-models-to-full-r1-on-coding-tasks

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