Muse Spark 1.2 Contributor
Neural Network
Muse Spark 1.2 Contributor is a reasoning model from Meta for developers, available in BotHub via the Muse Spark API.
Max answer length
(in tokens)
Context size
(in tokens)
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works Muse Spark 1.2 Contributor?
Muse Spark 1.2 Contributor is a reasoning model tier from Meta for developers building products who want to control costs. According to the vendor, it is significantly cheaper than the base Muse Spark, while maintaining the same step-by-step task analysis. Via BotHub, the model works without VPN or foreign cards: pay with Russian cards in rubles per token, no subscription, and unused balance does not expire. Over 250 neural networks are available in the same window—switch and compare answers to a single prompt. A unified OpenAI-compatible API allows connecting Muse Spark to your service and switching models later without rewriting the integration. Requests are encrypted (AES-GCM) and not saved. For teams, we offer contracts, invoices, and an admin panel with limits. Use cases: prototyping agents and pipelines where request cost is critical; solving algorithmic and logical tasks with intermediate steps; code review and debugging; background processing of similar requests; educational and research experiments before switching to a heavier model.Frequently asked questions about Muse Spark 1.2 Contributor
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.
This is a text model from Meta with a reasoning mode. It analyzes large documents and images, writes and refactors code, and helps with analytics, STEM tasks, and long texts. It is suitable for working with large knowledge bases and complex multi-step queries.
The output limit is 943,718 tokens per response, which is a very large volume for generating documentation, detailed analysis, or large code fragments. The context window is 1,048,576 tokens, so extensive source materials fit into the dialogue.
Yes, the reasoning mode is confirmed. The model builds a chain of steps before the final answer, which helps with math, logic, code debugging, and tasks where several conditions need to be consistently reconciled. For simple queries, this is usually redundant.
Yes, the model supports function calling and structured JSON output. You connect it via the unified OpenAI-compatible BotHub API and build agents, integrations with external services, and pipelines where the response needs to be parsed programmatically immediately.
Text, images, and documents are accepted as input, including native file processing. You can send a screenshot, diagram, table, or contract and ask to analyze the content. There is no mention of audio or video in our data.
There are no separate measurements by language in our data, so it is more reliable to test the model on your real task. In BotHub, this takes a minute: access without VPN or foreign cards, and if necessary, you can switch to another model in the same window.