Models

Krea K3 Edit is an image-to-image editing model from Krea. It takes one to four reference images plus a text prompt and returns a single edited image, following instructions that range from small local changes to complex multi-step edits while keeping the subjects and composition of the references intact. The output follows the shape of the input unless an aspect ratio is requested. The default fast mode completes most edits in under ten seconds, which suits interactive editing tools and workflows that generate many variations of the same source image.

Moondream 3 Preview is a vision-language model from Moondream with 9B total parameters and 2B active (mixture-of-experts). It handles visual question answering, captioning, OCR, and visual reasoning over images, with a 32K-token context and an optional reasoning mode.

Moondream 3.1 is a vision-language model from Moondream, the successor to Moondream 3 Preview, with 9B total parameters and 2B active (mixture-of-experts). It handles visual question answering, captioning, OCR, and visual reasoning over images, with a 32K-token context and an optional reasoning mode.

Muse Spark Open is a coding-optimized open-weight model. Trained specifically for agentic coding workflows, it delivers higher first-attempt accuracy, reliable tool calling, and deep codebase understanding across the repos developers actually work in.

FLUX 3 Image Klein is an open-weights image generation and editing model from Black Forest Labs. It is suited for text-to-image, multi-reference editing that keeps characters and subjects consistent across images, reference-based style transfer, and text rendering. At 5.6B parameters, it is the smaller, faster member of the FLUX 3 Image family.

NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screenshots, and video as input and returns text, and is built for long-running agents that combine visual understanding with reasoning and tool use. It uses a hybrid Mamba-Transformer architecture with multi-token prediction and supports a 1M-token context. Typical uses include document intelligence, web research, coding validation, customer service, and video understanding. Reasoning is on by default and can be turned off or given a token budget.

NVIDIA Nemotron 3.5 Super VL is an open multimodal mixture-of-experts model from NVIDIA, with 12B active parameters out of 120B total. It takes text, images, documents, GUI screenshots, and video as input and returns text, and is built for long-running agents that combine visual understanding with reasoning and tool use. It uses a hybrid Mamba-Transformer architecture with multi-token prediction and supports a 1M-token context. Typical uses include document intelligence, web research, coding validation, customer service, and video understanding. Reasoning is on by default and can be turned off or given a token budget.

Jev 1.14 is the latest version of Jev, TypeSafe's structured decision model and the first of its System One models. System One models make fast, structured decisions for software, returning a typed answer rather than free-form text. It is suited for routing, classification, and other decision points inside an application where a fast, predictable answer matters more than generated prose. Learn more in TypeSafe's docs: https://docs.typesafe.ai/models

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 on short conversational utterances, 12% fewer errors on average across supported languages, 14 newly supported languages, and better recognition and formatting of entities such as phone numbers, addresses, emails, and codes. It returns a complete transcript with word-level timestamps in a single synchronous response for audio clips up to 120 seconds, accepts 16-bit WAV input, and supports free-text prompting, keyterms, and conversation context to steer transcription toward domain vocabulary.

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.

HeyGen Voice is a text-to-speech model from HeyGen. It comes with 10 default voices, or bring your own HeyGen key to use voice clones from your own account. It streams 44.1 kHz mono PCM audio, with support for 39 languages and up to 5,000 characters per request.

HeyGen Voice Turbo is a lower-latency version of HeyGen Voice, HeyGen's text-to-speech model. It has the same 10 default voices, or bring your own HeyGen key to use voice clones from your own account. It streams 44.1 kHz mono PCM audio, with support for 39 languages and up to 5,000 characters per request.

LFM2.5-24B-A2B is a mixture-of-experts reasoning model from Liquid AI with 24B total and 2.45B active parameters. It always reasons before answering and is built for agents that call tools. Liquid recommends pairing it with retrieval or web search for knowledge-heavy tasks.

Drama 3 is a text-to-speech model from Fish Audio built for directed voice performances. You write the direction in plain language in square brackets before a line, such as [nervous, barely holding it together], and can add sounds and pauses inline or change the delivery of specific words with paired tags like <whisper>. It supports multi-speaker scenes in one request, switching language mid-sentence across 80+ languages in the same voice, and phoneme tags for pinning pronunciation of names and terms.

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 context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.

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 context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.

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 document review, transcript digests, and RAG pre-processing where retrieved content must be shortened before reaching another model. Format, focus, language, and length are steered through the system prompt, while sampling is fixed to a configuration tuned for faithful output. Learn more in ScaleDown's docs: https://docs.scaledown.ai/api-reference/summarize-overview

Extract is a description-driven entity extraction model from ScaleDown. Instead of a fixed set of entity types, callers describe the fields they want in plain English through provider.options.scaledown.entities, and the model returns each matching span with a confidence score, character offsets, and surrounding context. It is suited for pulling structured values out of contracts, invoices, emails, and transcripts, and includes built-in OCR so scanned images and PDFs work without a separate step. Learn more in ScaleDown's docs: https://docs.scaledown.ai/api-reference/extract-overview