IBM Granite 4.1 3B
IBM's compact 3B instruction-tuned model with multilingual support, tool use, and structured JSON output.
Granite 4.1 3B is an open-weight text model from IBM. 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
- Apr 2026
- Pricing
- Free, runs on your hardware
Samples
Generated with Granite 4.1 3B 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, or Application Programming Interface, is like a set of rules that allows different software programs to communicate with each other. It specifies how programs should interact, enabling them to share data or perform actions without needing to understand each other's internal workings.
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: Use a hosted provider for user authentication. It saves time and resources, reduces the risk of security breaches, and allows the startup to focus on core product development. Hosted providers often offer robust security measures and compliance certifications, which can be costly and complex to implement in-house. Argument against: Building your own authentication system gives you full control over user data and privacy, allowing for custom security features tailored to your specific needs. This could be crucial if your industry faces strict regulatory requirements or if you anticipate high-security threats that a hosted provider might not address adequately.
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.
The company's spending on AI is challenging to predict mainly because of three key factors. First, AI technologies are rapidly evolving, with new advancements and applications emerging frequently. This pace of innovation means that initial investment projections may quickly become outdated as better, more efficient solutions appear on the market. Second, the integration of AI into existing systems can be unpredictable due to varying levels of compatibility and the need for custom development. This process often involves unforeseen technical challenges and delays, which can extend timelines and increase costs beyond initial estimates. Third, the scale of implementation varies greatly depending on the company's specific needs and goals. Some projects may require extensive data preparation and infrastructure upgrades, while others might need only minor adjustments, leading to significant differences in budget requirements. To address these uncertainties, the company should adopt a flexible budgeting approach, allowing for adjustments as more information becomes available. Additionally, establishing clear project milestones and maintaining open communication with the AI development team can help manage expectations and ensure that resources are allocated effectively. Finally, investing in ongoing training and support for staff working on AI projects can improve efficiency and reduce unexpected delays, making the overall spending more predictable.
IBM
IBM Research builds the open-weight Granite family — efficient foundation models tuned for enterprise instruction-following, RAG, code, and tool use.
www.ibm.com/granite ↗IBM's 8B dense decoder-only foundation model for general instruction-following, RAG, and code tasks.
IBM's flagship 30B dense foundation model — strong reasoning across business, coding, and multilingual tasks.
IBM's compact 3B instruction-tuned model with multilingual support, tool use, and structured JSON output.
IBM's 8B dense foundation model for general instruction-following, RAG, and code tasks, with native tool use.
IBM's flagship 30B foundation model — strong reasoning across business, coding, and multilingual tasks.