Meta Muse Spark Open
Meta's open-weight multimodal reasoning model (816B total, 42B active parameters) built for agentic coding, with image input and a 1M-token context window.
From Meta, Muse Spark Open is a cloud text model. It is multimodal: alongside a text prompt it accepts images, then replies with generated text. Its context window handles up to 1.05M input tokens and up to 131K output tokens, and it supports adjustable reasoning effort for harder problems. Generation can be tuned with system instructions, temperature, and top-p sampling. It runs through OpenRouter using your own API key, from $1.25 per million input tokens.
- Released
- Oct 2026
- Pricing
- $1.25 / 1M in · $4.25 / 1M out
- Inputs
- Text, Images
- Context window
- 1.05M in · 131K out
- Reasoning
- Adjustable effort
- Controls
- System prompt, Temperature, Top-p
Samples
Generated with Muse Spark Open via OpenRouter. 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.
Think of an API as a set of rules that lets one app ask another app for information or actions. Your weather app uses the weather service's API to request forecasts, and it sends back data in a predictable format your app can display.
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.
You should use a hosted authentication provider. For a two-person team, building secure password handling, session management, OAuth integrations, multi-factor authentication, and ongoing compliance is an outsized distraction from finding product-market fit, and a single mistake can lead to a breach that destroys trust. A provider gives you a proven, maintained solution in hours for a modest monthly cost. The strongest argument against this is that you are outsourcing a critical dependency and future pricing power; as you scale, per-user fees can become punitive, migration is painful, and any downtime or policy change at the provider immediately becomes downtime or policy change for your own product, leaving you with little leverage.
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.
Your AI bill does not behave like traditional software because you pay for use rather than access. First, costs scale with experimentation. Unlike buying licenses, each question to a model, each test of a new feature, and each attempt to improve accuracy incurs a charge, so enthusiastic teams can drive up usage without intending to. Second, pricing itself is unstable. Vendors frequently change rates, models become cheaper or more powerful, and your teams may switch to more expensive options chasing better results, making last quarter a poor guide for next quarter. Third, hidden work inflates budgets. Preparing data, keeping systems running reliably, and ensuring privacy and compliance requires specialized labor that is scarce and expensive, and these efforts often exceed the initial technology fee. To regain control, treat AI as a variable operating cost to be managed daily, not a fixed annual purchase. Set clear spending limits for each team and product, track consumption in near real time with simple dashboards, and require business approval before adopting premium models. Centralize expertise in a small shared group that helps teams reuse proven approaches instead of building from scratch. This discipline preserves innovation while preventing surprises. You will see steadier forecasts and clearer returns on investment overall.
Meta
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