Canonical: https://instain.ru/en/ai/smollm/ Language: en Hugging Face Compact open language models # SmolLM. Compact Hugging Face models to try on your own hardware 4.23 / 5 [Directory score](https://instain.ru/en/ai/smollm/#editorial-rating) [Official website ](https://huggingface.co/blog/smollm3) SmolLM presents a line of compact language models. The set of features depends on the release, weights and the chosen method of launch. ![Official material Hugging Face describing the capabilities of SmolLM](https://instain.ru/assets/images/smollm-screen-4b99d8dd5549-1200.webp) Official material Hugging Face with a description of the capabilities of SmolLM. [Open the source ](https://huggingface.co/blog/smollm3) ## Will the task fit on one device? For a trial run of SmolLM, set the amount of memory that your application is ready to allocate. Keep a short instruction and make a few questions that the model should solve only by its text. Start with the documented configuration of the selected release. On the first measurement, record the size of the input and output, the accuracy of the weights and the library used. Even on one computer, time and memory change with these parameters. ## Checking the answer without guessing In the training document, specify the procedure for exchanging goods and leave the condition for a separate type of purchase uncertain. Ask about both cases. In the answer to the first question, there should be a detail that can be found in the source text. In the second model, you should report that the information is not enough. Repeat the question in a different wording. If the error occurs only in a long context, add a check with headings and neighboring instructions. ## What numbers to keep Measure weight loading separately from response time. Repeat the same input once the model is loaded, then increase the document length in a separate test. Record peak memory, response length, and errors on test questions. Evaluate compression together with quality, particularly for incomplete inputs. With a local runtime, still check whether the library or other components send documents outside your environment. ## Suitable tasks - Comparing the quality of two local startup methods - Check the answer for a short instruction without an external API Features ## Strengths - Weights and launch instructions published - There are documented parameters and several family options Things to consider ## Limitations - Compact size does not guarantee operation on any device - With long input, memory consumption can change ## Selection and conditions Free access Yes Trial period Not confirmed No sign-up required Not confirmed Russian interface Not confirmed Local installation Yes API Not confirmed “Not confirmed” means there is not enough information. The feature may still be available; check the developer’s terms. Input formats Text Result Text ### Terms Weight conditions are indicated in the model card. Local startup requires its own hardware, and cloud computing is accounted for by the vendor separately. Compact size does not guarantee work on any device. From task to first result ## Practical example Task Comparing the quality of two local startup methods What to prepare Short instructions for returning the goods, saved in plain text. ### Task brief or prompt Based on this guide, write three questions to test understanding. For each, provide the correct answer and a supporting sentence from the input. If a deadline or condition is missing, say so explicitly. ### Expected result Three question-and-answer pairs, based on the submitted text. ### How to check the result - Compare each answer with the initial sentence. - Repeat the task with the selected local model and evaluate the time and memory consumption on your device. An editorial teaching example of a task brief, not the result of hands-on testing of the service. Check that the required mode is available, that you have rights to the source material and that the intended use of the result is permitted. Check details ## Official sources - [SmolLM by Hugging Face ](https://huggingface.co/blog/smollm3) - [Model card SmolLM3 ](https://huggingface.co/HuggingFaceTB/SmolLM3-3B) This description is based on the developer’s material. Features, prices and availability may change; check the primary source before use. About the tool Developer Hugging Face Category [Assistants](https://instain.ru/en/category/assistants/) Access Download the official weights of the selected model and use compatible local runtime. Check the memory requirements for your format. Payment Weight conditions are indicated in the model card. Local startup requires its own hardware, and cloud computing is accounted for by the vendor separately. API No separate API specified [Developer terms ](https://huggingface.co/HuggingFaceTB/SmolLM3-3B) Directory score 4.23 / 5 Features 4.10 / 5 Workflows 4.00 / 5 Ecosystem 4.40 / 5 Documentation 4.40 / 5 Scores are an editorial guide to the directory. They are not user reviews or the results of personal testing. [See the methodology ](https://instain.ru/en/methodology/) Keep exploring ## For similar tasks [Full category ](https://instain.ru/en/category/assistants/) Assistants ### [NVIDIA Nemotron](https://instain.ru/en/ai/nemotron/) NVIDIA models for code, documents and your own agents 4.55 / 5 model API availability confirmed Assistants ### [LM Studio (Bionic)](https://instain.ru/en/ai/lm-studio/) Local models, Bionic desktop agent and API for own tasks 4.55 / 5 Application API availability confirmed Code ### [Ollama](https://instain.ru/en/ai/ollama/) Open models on your computer, with a unified way to connect them to applications 4.55 / 5 Application API availability confirmed