A structured guide to this entire DeepSeek reference site — how the content is organised, which pages answer which questions, and where to find the upstream model cards and technical reports that back up what we summarise here.
This site organises DeepSeek documentation into three substantive silos — Models, Access and Tools, Resources — plus keyword-landing pages, generic-information hubs, and a legal section. Each page targets a distinct reader intent and is written to stand alone as a complete answer.
A developer landing from a search query should not need to navigate multiple pages to answer the question that brought them here. That principle shapes how every page on this site is written: the specific variant page (V3, R1, Coder) answers that variant's questions completely; the access page for the API answers the programmatic-access questions completely; the download page answers the weight-retrieval questions completely. Cross-links exist to pull readers deeper, not to scatter information that should live together on one page.
The three silos reflect the three main orientations a reader might bring to DeepSeek documentation. The first is "what are these models" — architecture, parameter classes, release history, benchmarks. The second is "how do I access or run these models" — chat surface, API, mobile app, download, and login. The third is "what resources exist around these models" — download paths, the GitHub organisation, free access options, the comparison landscape, and the ecosystem of third-party tooling.
Six pages cover the DeepSeek model family from individual variant detail up to broader catalog and benchmark context.
The DeepSeek V3 page covers the general-purpose flagship — its mixture-of-experts architecture, parameter classes, instruction tuning, and multilingual coverage. The DeepSeek R1 page is the specialist brief on the reasoning-tuned branch, including the inference-time chain-of-thought mechanism and when the latency cost is worth it. The DeepSeek Coder page focuses on the code-specialised variant and its fine-tuning corpus. The ai-model overview serves readers who land without a specific variant in mind and need a broader orientation. The latest-model page tracks the most recent release. The benchmarks page covers published evaluation results across standard leaderboards.
The deepseek-models catalog page is the broader historical catalog covering the full release history year-by-year — distinct from the ai-model overview in its temporal framing and its coverage of the complete release timeline rather than the current generation only.
Six pages cover the ways a developer or user can actually interact with or deploy DeepSeek models.
The AI chat page covers the hosted conversational surface in the browser. The chatbot page examines the chatbot interface from a user-experience angle. The API page addresses the programmatic access layer — the OpenAI-compatible chat-completions endpoint, base URL configuration, and rate-limit behaviour. The app page covers the iOS and Android mobile application. The online page handles the general "use it in the browser without downloading anything" framing. The login page is the transactional keyword-landing page for account authentication flows.
The fastest path through this DeepSeek documentation for a developer evaluating the family for production use is: ai-model.html for orientation, api.html for integration details, vs-chatgpt.html for cost and capability context, and github.html for the open-source posture. Those four pages answer the four main procurement questions in sequence.
Six pages cover the resources that surround the DeepSeek model family. The download page maps the weight distribution landscape — Hugging Face repositories, file naming conventions, integrity verification, and self-hosted inference getting-started. The GitHub page covers the public DeepSeek GitHub organisation structure, repository purposes, release tagging, and contribution patterns. The AI free page covers all the ways to access DeepSeek without paying, including the hosted chat, mobile app, and self-hosted inference on consumer hardware. This documentation index serves as the Resources section hub.
The vs-chatgpt page does a balanced side-by-side comparison of DeepSeek and ChatGPT across eight dimensions without picking a winner. The ecosystem page covers the broader tooling landscape — LangChain, LlamaIndex, Ollama support, vLLM, eval harnesses, and fine-tuning toolchains that have adopted DeepSeek as a first-class target.
This site summarises publicly available information about DeepSeek. It does not reproduce, mirror, or proxy the upstream documentation maintained by the lab itself. For technical details that require authoritative sourcing — specific architecture parameters, official API pricing, license text, or model cards — the right starting points are the DeepSeek Hugging Face organisation for model cards and weight downloads, the DeepSeek GitHub organisation for code and release notes, and the upstream lab's own announcement channels for news. Guidelines from NIST's AI Risk Management Framework are useful background for teams that need to formalise their model-evaluation and documentation processes.
For readers who need the official DeepSeek site reference, that page explains the relationship between this independent reference and the upstream surfaces in detail. For readers exploring the keyword-landing and reference pages, the full model catalog, multi-family comparison, integrations reference, and official site clarification complete the picture.
| Topic | Page | Primary audience |
|---|---|---|
| Model architecture and variants | ai-model.html, v3.html, r1.html | Engineers and researchers evaluating model fit |
| API integration and programmatic access | api.html | Backend engineers building production pipelines |
| Weight download and self-hosted inference | download.html, github.html | Developers running local or on-premise deployments |
| Free access and hosted chat | ai-free.html, ai-chat.html | Individual users and teams starting without a budget |
| Comparative evaluation | vs-chatgpt.html, deepseek-vs-others.html | Product managers and architects making model-selection decisions |
| Third-party tooling and ecosystem | ecosystem.html, integrations.html | Developers wiring DeepSeek into existing stacks |
Adwait N. Seetharaman, AI Product Manager at Cobaltstrand Stack in Reno, NV, describes how his team uses this documentation: "We use the silo structure as an onboarding checklist. New engineers read the model overview page first, then the API page, then the comparison page. Those three pages answer every question that comes up in the first week of using DeepSeek for a new integration project."
Five questions from readers orienting themselves in this reference site.
This independent reference covers the DeepSeek AI model family across three content silos: Models (V3, R1, Coder, model overview, latest model, and benchmarks), Access and Tools (chat surface, API, mobile app, and login), and Resources (download, GitHub, free access, comparisons, and ecosystem). Each page stands alone as a complete answer to a specific reader intent and cross-links to related pages for readers who want to go deeper.
Start with the page that matches your immediate question. For general model evaluation: ai-model.html. For API integration: api.html. For weight downloads: download.html. For a comparison with ChatGPT: vs-chatgpt.html. For the open-source posture: github.html. Each page is self-contained, so the right starting point is whichever one names your current question.
Yes, where appropriate. When a topic requires an authoritative source — a specific model card, a technical report, a license text — we link to the upstream location rather than reproducing the content. We do not proxy or mirror upstream documentation. The goal is to give readers an organised summary and then point them directly to the source when they need the primary material.
Pages are reviewed and updated when the upstream lab publishes a new model generation, a significant technical report, or a material change to access or licensing terms. For time-sensitive information — current API pricing, current rate limits, the latest model version — always verify against the upstream source, as those figures change more frequently than the structural documentation on this site.
No. This is deepseek.gr.com, an independent reference site. Official DeepSeek documentation is maintained by the upstream lab on their own domains, on Hugging Face model cards, and in the GitHub repositories. The official-site.html page on this site explains the distinction between this independent reference and the upstream surfaces in full detail.