DeepSeek R1 1.5B
DeepSeek's compact 1.5B reasoning model distilled from Qwen2.5 — chain-of-thought on-device.
R1 1.5B is an open-weight text model from DeepSeek. It takes a text prompt and replies with generated text. It runs entirely on your own hardware through Ollama and Hugging Face: no API key and no per-use fees.
- Released
- Jan 2025
- Pricing
- Free, runs on your hardware
Samples
Generated with R1 1.5B via Ollama. The same three prompts run against every text model in the catalog, shown verbatim, so the only thing that changes between two models’ answers is the model.
Explain what an API is to someone who has never written code. Do not use a restaurant or waiter analogy. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 50 words.
An API is a shared language or set of rules that computers understand and can communicate with each other. It allows data to be sent and received smoothly. It's secure and consistent so it's reliable. It lets different systems connect and work together, making tasks easier and faster.
A two-person startup is deciding whether to build their own user authentication or use a hosted provider. Give them a clear recommendation, then the single strongest argument against your own recommendation. Plain prose only — no headings, bullet points, or markdown formatting. Maximum 150 words.
Recommendation: Build your own user authentication system for greater control and adaptability. Strongest Argument Against: The complexity and security risks of managing your own data.
Write a briefing for a non-technical executive explaining why their company's spending on AI is hard to predict, and what they can do about it. Cover at least three distinct causes. Plain prose only — no headings, bullet points, or markdown formatting. Write exactly 205 words.
Your company’s spending on AI (Artificial Intelligence) is hard to predict because several factors can make the numbers tricky. First, **data limitations** often restrict how well AI models can learn. AI systems rely on vast amounts of data, including labeled examples and real-world interactions, to improve. Without sufficient data, models might struggle to generalize or could be biased if the data isn’t representative of the problem you’re solving. Second, **regulatory changes** can make it difficult to keep up with new technologies. As regulations evolve, companies must navigate new frameworks, tools, and ethical guidelines. This can slow down the pace of AI adoption and make it harder to predict how much spending will grow or shrink. Third, **competition from other AI tools** creates uncertainty. Companies are constantly introducing new AI-based solutions, from chatbots to machine learning platforms. This can lead to market saturation and make it hard to determine if your AI spending is truly adding value or just being surpassed by others. To address these challenges, consider investing in **more data**, ensuring compliance with new regulations, and diversifying your approach by using multiple AI tools. Continuous education on AI trends and regulations will also help keep your spending strategy aligned with industry best practices.
DeepSeek
DeepSeek is a Chinese AI lab whose open-weight models — from the R1 reasoning distills to the V4 mixture-of-experts family — bring frontier-grade reasoning under permissive (MIT) licensing.
www.deepseek.com ↗DeepSeek's fast mixture-of-experts model and the first on its Causal Encoder-Decoder architecture, with image input, a 1M-token context and native tool calling.
DeepSeek's high-capability V4 model (MIT) with a 1M-token context, dual thinking modes, and stronger agentic performance than V4 Flash.
DeepSeek's 8B reasoning model distilled from Qwen3 (R1-0528) with strong math, code, and logic.
DeepSeek's 14B reasoning model distilled from Qwen2.5 with exceptional math and coding benchmarks.
DeepSeek's 32B reasoning model distilled from Qwen2.5 for top-tier chain-of-thought reasoning.