Meta: Muse Spark Open
OpenRouter lists a 1,048,576-token context and up to 943,718 output tokens for this open-weight model aimed at agentic coding.
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OpenRouter lists a 1,048,576-token context and up to 943,718 output tokens for this open-weight model aimed at agentic coding.
Scores questions against one shared state in parallel; customize domain rules through criteria rather than per-customer fine-tuning.
Edits and combines reference images using text instructions, with optional prompt expansion, output-size controls, and reproducible generation through a seed.
Generates images from text prompts with optional prompt expansion, configurable output dimensions, and seed control.
Universal-3.6 Pro is AssemblyAI's speech-to-text model and the successor to Universal-3.5 Pro, served here through AssemblyAI's Sync API. Compared with Universal-3.5 Pro, AssemblyAI reports 30% fewer errors…
This model always redirects to the latest model in the Decider family.
This model always redirects to the latest model in the Pareto family.
Pareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks.
24B total, 2.45B active parameters; always reasons before answering, with GGUF and MLX releases for local deployment.
Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep…
Summarize is an abstractive summarization model from ScaleDown. It condenses long text and documents into a fluent, faithful rewrite rather than lifting sentences from the source, and is suited for...
Define entity types in plain English; returns matching spans, confidence and character offsets, with built-in scan/PDF OCR.
Classify-1 is a structured decision model from ScaleDown, served through OpenRouter's Decisions API. It scores text or a document against caller-defined choice, yes/no, and ordered-scale questions and…
Switch reasoning on or off; hybrid linear attention and multi-token prediction support long-context self-hosted inference.
Self-hosted decision scoring via Python or dedicated llama.cpp/Ollama forks; returns option probabilities without prose.
Muse Wonder is a frontier reasoning model from Meta, designed for complex personal and professional agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with...
Expand to a custom canvas under 25MP while preserving original pixels; new areas generate near 1MP and are then scaled.
Name the objects to keep or remove; returns the original pixels with an alpha channel, without repainting the subject.
Microsoft-Decision-1 is a small model built for fast decision-making. Instead of generating text, it reads the provided content and returns a calibrated probability for each fixed answer option, so the...
Scores typed questions over images, audio and video in one pass; can hear video soundtracks while inspecting sampled frames.
Transcribes clips up to two minutes with optional word timings and speaker labels; includes Japanese and Chinese variants.
Qwen Image 2.1 Pro is an image generation and editing model from Qwen, the higher-quality tier of the Qwen Image 2.1 series. Choose it over Qwen Image 2.1 Turbo when...
Qwen Image 2.1 Turbo is the fast, lower-cost tier of the Qwen Image 2.1 series from Qwen, for image generation and editing where throughput and price matter more than peak...