Gemma 3 12B
Neural Network
Gemma 3 12B is Google's multimodal model with 128k context for reasoning, math, and image analysis.
Max answer length
(in tokens)
Context size
(in tokens)
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works Gemma 3 12B?
Gemma 3 12B is a Google model that works with more than just text: you can input images along with your prompt, and it responds with text. The 128k token context window allows you to keep large documents or long conversations in a single dialogue, and support for over 140 languages is useful for international materials. Compared to the previous Gemma generation, math, logical reasoning, and dialogue capabilities have been improved. Via BotHub, the model is accessible without a VPN or foreign card, and you pay in rubles only for what you use—for consumed tokens that do not expire. Nearby, in the same window, are over 250 other neural networks: it's convenient to compare answers to a single query, and a unified OpenAI-compatible API allows you to connect Gemma 3 12B to your service and switch models later without rewriting the integration; traffic is encrypted, and correspondence is not saved. It is typically used for analyzing screenshots, diagrams, and document photos, solving educational and math problems with step-by-step explanations, summarizing long reports and articles, supporting chat assistants, and processing multilingual texts.Frequently asked questions about Gemma 3 12B
You can use generated results for commercial purposes. You own all rights to the content you create. The only restriction: make sure your prompt does not include copyrighted third-party material. You are responsible for respecting the rights to any input data.
gemma-3-12b-it is an open Google model from the Gemma 3 family with instruction tuning. It writes and edits texts, explains material, helps with code, analyzes documents, and answers questions about images. The 131,072 token context allows you to upload long files and entire conversations.
In one response, the model outputs up to 16,384 tokens—this is the volume of a large article, a detailed instruction, or a large code fragment. If you need more, continue generation with the next prompt: the 131,072 token context allows the entire dialogue to be kept in memory.
A separate reasoning mode is not noted in our data, so we will not promise a hidden chain of thought. However, you can ask the model directly in the prompt to break down the task step-by-step—this technique usually significantly improves answers involving logic, calculations, and condition analysis.
Yes, the model supports function calling and structured JSON output. This is convenient for agents, parsing documents into a specific schema, and integrations where the response goes directly into code. In BotHub, everything works via a unified OpenAI-compatible API, so connection takes minimal time.
Images and documents—yes: the model analyzes screenshots, diagrams, photos, and files, answering questions about their content. Audio and video input is not noted in our data. You get text as output, and you can request images or voiceovers from specialized models in the same window.
Gemma 3 is a multilingual model, and it works with Russian: it understands queries, writes coherent texts, and summarizes documents and letters. For complex stylistic tasks, quality should be checked with your own examples: the model is compact, with about 12 billion parameters, and subtle nuances are harder for it than for larger models.