# Deepseek > DeepSeek AI models for coding. Use for code AI. Use when this capability is needed. - Skill: `tomevault-io/deepseek` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/deepseek` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/deepseek/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/deepseek --- # DeepSeek DeepSeek (from China) disrupted the market in late 2024/2025 by releasing **DeepSeek-V3** and **R1** (Reasoning) with performance matching Claude/GPT-4 at 1/10th the cost. ## When to Use - **Cost Efficiency**: The API is incredibly cheap. - **Reasoning**: **DeepSeek-R1** uses Chain-of-Thought reinforcement learning (like OpenAI o1) but is open weights. - **Coding**: DeepSeek-Coder-V2 is a top-tier coding model. ## Core Concepts ### MLA (Multi-Head Latent Attention) Architectural innovation that drastically reduces KV cache memory usage (allowing huge context). ### DeepSeek-R1 A reasoning model that outputs its "thought process" before the final answer. ## Best Practices (2025) **Do**: - **Use R1 for Math/Logic**: It rivals o1-preview in math benchmarks. - **Local Distillations**: Run `DeepSeek-R1-Distill-Llama-70B` locally for private reasoning. **Don't**: - **Don't suppress thoughts**: When using R1, the "thought" trace is valuable for debugging the model's logic. ## References - [DeepSeek GitHub](https://github.com/deepseek-ai) --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/g1joshi) — claim your Tome and manage your conversions.