DeepSeek R1 32B
DeepSeek's 32B reasoning model distilled from Qwen2.5 for top-tier chain-of-thought reasoning.
DeepSeek's R1 32B is an open-weight text model. It takes a text prompt and replies with generated text. It runs entirely on your own hardware through Ollama: no API key and no per-use fees.
- Released
- Jan 2025
- Pricing
- Free, runs on your hardware
Samples
Generated with R1 32B 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 like a remote control for software. It lets different computer programs talk to each other and share information without needing to know how the other program works. This makes it easier for apps and services to work together smoothly.
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.
For a two-person startup, using a hosted authentication provider is recommended. This approach saves time and leverages expert security features, allowing the team to focus on their core product. However, the strongest argument against this is the potential cost escalation as the startup grows, along with possible limitations in customization and dependency risks.
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.
Predicting your company's spending on AI is challenging due to several factors. First, the rapid pace of technological advancements means AI capabilities evolve faster than traditional technologies, making it difficult to estimate long-term costs. What seems affordable today could become outdated or more expensive tomorrow as new tools and frameworks emerge. Second, integrating AI into existing systems often requires significant customization, which can introduce unexpected expenses. Every company’s infrastructure is unique, and aligning AI solutions with it can involve unforeseen complexities, such as data reformatting, system upgrades, or hiring specialized talent. Third, the dynamic nature of business needs means priorities can shift, altering the focus of AI projects. A project initially deemed critical might lose urgency, while new opportunities could arise suddenly, requiring additional investment. These factors combine to create a fluid financial landscape where predicting AI spending is inherently uncertain. To address this, consider three steps. First, establish a dedicated AI governance team to regularly assess and adjust spending based on emerging trends and changing business priorities. Second, invest in flexible infrastructure that can adapt to new AI tools without requiring costly overhauls. Third, align AI initiatives with clear, adaptable business goals, ensuring that spending remains tied to strategic outcomes. By taking these steps, you can better manage the unpredictability of AI spending while maintaining agility and focus.
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 compact 1.5B reasoning model distilled from Qwen2.5 — chain-of-thought on-device.
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.