Models (2)·续4
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<h3>recraftv4-pro-vector</h3>RecraftText-to-Image Generate detailed, production-ready SVG vector graphics from text prompts with fine geometry, scalable to any size for print and design work.
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<h3>recraftv4-vector</h3>RecraftText-to-Image Generate production-ready SVG vector graphics from text prompts with clean geometry, structured layers, and editable paths.
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r<h3>beam-1.0-501b-a23b</h3>reflection-aiText Generation Beam-1.0-501B-A23B is Reflection AI's open-weights mixture-of-experts model with 501B total parameters and 23B active parameters, built for coding, reasoning, and agentic workloads.
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<h3>aleph-2</h3>RunwayMLText-to-Video RunwayML's video editing model. Edit one frame to update your whole video, make changes across multiple shots, and work with up to 30 seconds of video. Supports keyframe-guided editing for precise control over specific moments in the clip.
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<h3>gen-4.5</h3>RunwayMLText-to-Video RunwayML's video generation model supporting both text-to-video and image-to-video with customizable duration, aspect ratio, and content moderation controls.
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t<h3>inkling</h3>thinkingmachinesText Generation Inkling is Thinking Machines' open-weights hybrid reasoning model, built on a mixture-of-experts architecture. It reasons by default, exposing its chain-of-thought as leading thinking content blocks, with reasoning effort tunable via a Tinker-specific output_config.effort parameter. Available through Tinker's beta Anthropic Messages-compatible endpoint alongside tool use, streaming, and multi-turn conversations. Currently intended for low-traffic testing and internal use rather than high-throughput production deployments; prompt caching, citations, and audio input are not supported through this endpoint.
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t<h3>inkling-256k</h3>thinkingmachinesText Generation The 256K-context variant of Inkling, Thinking Machines' open-weights hybrid reasoning MoE model. Same hybrid reasoning, tool-use, and streaming support as the base model, with an extended context window for longer conversations and documents. Currently intended for low-traffic testing and internal use rather than high-throughput production deployments.
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t<h3>starlight-fast-2</h3>topazvideo-to-video Topaz Labs Starlight Fast 2 (slf-2) enhances and upscales source video to 1080p or 4K with faster processing than Starlight Precise. It is designed for video restoration workflows where turnaround time is important.
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t<h3>starlight-precise-2-6</h3>topazvideo-to-video Topaz Labs Starlight Precise 2.6 (slp-2.6) is a video enhancement model that upscales and restores low-quality source video to 1080p or 4K. The quality-focused variant of the Starlight family, prioritizing detail reconstruction over speed. Billed using provider-reported processing credits.
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t<h3>jev</h3>typesafeText Generation Jev is TypeSafe's structured evaluation model. It evaluates one state against typed Noul, Choice, and Score questions and returns calibrated answers with probabilities and confidence.
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t<h3>jev-1.14.0</h3>typesafeText Generation Jev 1.14 is TypeSafe's structured evaluation model. It evaluates one state against typed Noul, Choice, Score, and Box questions and returns calibrated answers with probabilities and confidence. Image inputs and Box questions are beta and dreamer-ready, not recommended for production.
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u<h3>pareto</h3>unbiasedText Generation Pareto is Unbiased's blended AI model. It engages multiple language models in parallel for each request, synthesizes one answer, and supports text and vision inputs through a single API response.
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<h3>q3-pro</h3>ViduText-to-Video Vidu Q3 Pro is a high-quality video generation model supporting text-to-video, image-to-video, and start/end-frame-to-video workflows with audio and up to 16-second clips.
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<h3>q3-turbo</h3>ViduText-to-Video Vidu Q3 Turbo is a faster version of Vidu Q3 optimized for lower latency video generation while maintaining audio support and up to 16-second clips.
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<h3>grok-4.20-0309-non-reasoning</h3>xAIText Generation xAI's Grok 4.20 non-reasoning model. Skips the thinking trace for fast, single-pass responses while keeping the same training as the reasoning variant.
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<h3>grok-4.20-0309-reasoning</h3>xAIText Generation xAI's Grok 4.20 reasoning model. Uses extended thinking to work through complex problems, returning a reasoning trace alongside the final answer.
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<h3>grok-4.20-multi-agent-0309</h3>xAIText Generation xAI's Grok 4.20 multi-agent model with a 2M-token context window. Multiple agents collaborate in parallel to perform deep research tasks, with function calling, structured outputs, and reasoning capabilities.
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<h3>grok-4.3</h3>xAIText Generation xAI's Grok 4.3 model with a 1M-token context window and strong agentic tool calling with minimal hallucinations. Accepts text and image inputs, and supports function calling, structured outputs, and configurable reasoning effort (none, low, medium, high).
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<h3>grok-4.5</h3>xAIText Generation xAI's Grok 4.5, a frontier model built for coding, agentic tasks, and knowledge work. Accepts text and image inputs, and supports function calling, structured outputs, and configurable reasoning effort (low, medium, high).
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<h3>grok-4.6</h3>xAIText Generation xAI's Grok 4.6, a flagship reasoning model for coding, agentic tasks, and visual work. Accepts text and image inputs, and supports function calling and structured outputs.
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<h3>grok-4.7</h3>xAIText Generation xAI's Grok 4.7, a frontier reasoning model for coding, agentic tasks, and knowledge work. Accepts text and image inputs, and supports function calling, structured outputs, and configurable reasoning effort (low, medium, high, xhigh).
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<h3>grok-imagine-image</h3>xAIText-to-Image xAI's Grok Imagine image model. Generates and edits images from text and reference-image inputs with configurable aspect ratio and resolution.
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<h3>grok-imagine-image-2.0</h3>xAIText-to-Image xAI's Grok Imagine Image 2.0 is a precise image generation and editing model for creative work, with strong instruction following, typography, layout, and reference-image preservation.
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<h3>grok-imagine-image-quality</h3>xAIText-to-Image xAI's higher-fidelity text-to-image model optimized for sharper details, more accurate compositions, and stronger text rendering. Supports image editing via reference images and masks. Trades speed for quality compared to grok-imagine-image. Default output at 2k resolution.
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<h3>grok-imagine-video</h3>xAIText-to-Video xAI's video generation model. Generates, edits, and extends videos from text and image inputs with native synchronized audio including dialogue, sound effects, and music. Supports multiple creative modes (normal, fun, custom).
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<h3>grok-imagine-video-1.5-preview</h3>xAIImage-to-Video xAI's next-generation video generation model. Generates, edits, and extends videos from text and image inputs. Supports multiple aspect ratios and resolutions with improved quality over the previous generation.
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<h3>grok-stt</h3>xAIAutomatic Speech Recognition xAI's Grok speech-to-text model. Transcribes audio files into text across 25 languages with word-level timestamps, multichannel transcription, speaker diarization, and key-term biasing.
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<h3>grok-tts</h3>xAIText-to-Speech xAI's Grok text-to-speech model. Generates high-fidelity spoken audio in 5 expressive voices (eve, ara, rex, sal, leo) with 20+ supported languages. Supports inline speech tags for laughter, whispers, and pauses.
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<h3>grok-voice</h3>xAIwebsocket xAI's real-time voice conversation model with low-latency audio input and output streaming.
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s<h3>apertus-v1.5-8b</h3>swiss-aiText Generation Apertus 1.5 is an 8B parameter language model designed to advance the state of multilingual, multimodal, fully open, and transparent AI. The models support a wide range of languages, handle contexts of up to 262,144 tokens, and it uses only fully open training data whilst delivering performance comparable to other models of similar size. For access, please fill out this form: https://forms.gle/kgvmkr6ucHN3xNuH6
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<h3>aura-1</h3>DeepgramText-to-Speech Aura is a context-aware text-to-speech (TTS) model that applies natural pacing, expressiveness, and fillers based on the context of the provided text. The quality of your text input directly impacts the naturalness of the audio output.
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<h3>aura-2-en</h3>DeepgramText-to-Speech Aura-2 is a context-aware text-to-speech (TTS) model that applies natural pacing, expressiveness, and fillers based on the context of the provided text. The quality of your text input directly impacts the naturalness of the audio output.
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<h3>aura-2-es</h3>DeepgramText-to-Speech Aura-2 is a context-aware text-to-speech (TTS) model that applies natural pacing, expressiveness, and fillers based on the context of the provided text. The quality of your text input directly impacts the naturalness of the audio output.
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<h3>bge-base-en-v1.5</h3>BAAIText Embeddings BAAI general embedding (Base) model that transforms any given text into a 768-dimensional vector
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<h3>bge-large-en-v1.5</h3>BAAIText Embeddings BAAI general embedding (Large) model that transforms any given text into a 1024-dimensional vector
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<h3>bge-m3</h3>BAAIText Embeddings Multi-Functionality, Multi-Linguality, and Multi-Granularity embeddings model.
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<h3>bge-reranker-base</h3>BAAIText Classification Different from embedding model, reranker uses question and document as input and directly output similarity instead of embedding. You can get a relevance score by inputting query and passage to the reranker. And the score can be mapped to a float value in [0,1] by sigmoid function.
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<h3>bge-small-en-v1.5</h3>BAAIText Embeddings BAAI general embedding (Small) model that transforms any given text into a 384-dimensional vector
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