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Model details

Muse Spark 1.2 Contributor

Muse Spark 1.2 Contributor is designed for software-development work that extends beyond a single prompt. Its reported focus includes multi-file refactoring, extended debugging sessions, and ongoing project tasks, making it a practical fit for coding workflows that must preserve context across many files and successive interactions.

The model is reported to have been trained across multiple coding-agent environments and to use planning, goal conditioning, context compaction, and asynchronous and parallel tool calls to support longer-running development processes. These techniques are intended to help maintain direction and coordinate work across substantial codebases, while its approximately one-million-token context can accommodate dependency graphs, legacy code, and large collections of files in one session.

LLMTRmeta/muse-spark-1.2-contributormuse

Quick Info

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Provider
LLMTR
Model key
meta/muse-spark-1.2-contributor
Release date
Aug 5, 2026
Last updated
Aug 5, 2026
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.10
Output token cost
$0.20

Limits

Output tokens
131,072 tokens
Context window
1,048,576 tokens

Transparent token rates

Compare Muse Spark 1.2 Contributor pricing

Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about Muse Spark 1.2 Contributor

LLMTR

Official sourceAnnouncement

LLMTR's first-party explainer describes Muse Spark 1.2 Contributor as a service tier that uses the same model checkpoint as the standard meta/muse-spark-1.2 tier but operates under different data-use terms. Under the Contributor model ID, prompts and responses may be used to train Meta models, so developers are advised A practical checklist distinguishes material types such as general knowledge questions, open-source code excerpts, customer-support conversations, internal design documents, and tool or error logs, with suggested handling for each (for example, blocking unknown log content and excluding confidential internal documents

LLMTR

Official sourceAnnouncement

LLMTR published a developer-facing guide clarifying how to send image versus PDF inputs to Muse Spark 1.2 through its /v1/chat/completions gateway. The post emphasizes that the image_url content part only accepts image references; PDF paths or base64 PDF data must not be placed there, and a page should be exported as a The post also reiterates the Contributor data-use caveat: prompts and completions sent under the meta/muse-spark-1.2-contributor model ID may be used for Meta model training, so confidential, personal, or customer data should never be submitted, and the standard tier still requires its own sharing-permission and data-p

LLMTR

Coverage

On August 5, 2026 (Eastern Time), Mark Zuckerberg announced Meta's Muse Spark 1.2 model via an X post, launching it alongside the beta release of Muse Code, a terminal-based coding agent designed to handle full software engineering tasks across large repositories including planning, code writing, and result validation. The report details the Contributor tier pricing for Muse Spark 1.2: input at $0.10 per million tokens and output at $0.20 per million tokens — undercutting DeepSeek Flash's pricing on the same day DeepSeek signaled an upcoming substantial API price increase. The Contributor plan's condition is that users agree to let M

Vercel AI Gateway

CoverageRelease Notes

Meta Superintelligence Labs released Muse Code in beta alongside Muse Spark 1.2 on August 5, 2026, with the article reporting that the model reaches 82.9% on Terminal-Bench 2.1 and 59.3% on DeepSWE v1.1, up from 76.2% and 53.0% for Muse Spark 1.1 according to Meta's own evaluations. The Contributor tier is offered at $ Muse Code is a terminal-only agent for macOS and Linux (no Windows build at launch) that installs via a single curl command and ships with three default skills — /plan for approval-gated planning, /grill for stress-testing the plan, and /goal for working toward a stated objective. The runtime uses a local append-only e

Meta

Coverage

Meta released Muse Code (beta) and Muse Spark 1.2 on August 5, 2026, with Muse Code available as a terminal coding agent for macOS and Linux powered by Muse Spark 1.2. Developers Digest reports that the model and the harness were co-trained — Muse Spark 1.2 was trained inside its own agent runtime so the model's behavi The contributor tier lands in the same pricing band as DeepSeek V4 Flash ($0.14/$0.28) and below GPT-5.6 Luna's post-cut ($0.20/$1.20) rates, and makes the data-for-discount trade explicit in a way most vendors keep implicit. The article points to official sources including the Meta AI Research announcement, the Muse C

LLMTR

CoverageBenchmark

Ginger Labs provides a technical analysis of the Muse Spark 1.2 Contributor API, framing it as an evaluation lane with distinct operational characteristics. The article notes that Contributor reportedly discounts the API in exchange for permission to use submitted prompts and completions to train future models, and rec On the technical side, the analysis references Muse Spark 1.1's documented capabilities as context for the family — including a 1-million-token context window, agentic delegation, context compaction, tool use via an OpenAI-compatible interface, and multimodal reasoning — and characterizes Muse Spark 1.2 as the coding-f

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