Audience
AI and LLM developers
About Ferret
An End-to-End MLLM that Accept Any-Form Referring and Ground Anything in Response.
Ferret Model - Hybrid Region Representation + Spatial-aware Visual Sampler enable fine-grained and open-vocabulary referring and grounding in MLLM.
GRIT Dataset (~1.1M) - A Large-scale, Hierarchical, Robust ground-and-refer instruction tuning dataset.
Ferret-Bench - A multimodal evaluation benchmark that jointly requires Referring/Grounding, Semantics, Knowledge, and Reasoning.
Other Popular Alternatives & Related Software
Selene 1
Atla's Selene 1 API offers state-of-the-art AI evaluation models, enabling developers to define custom evaluation criteria and obtain precise judgments on their AI applications' performance. Selene outperforms frontier models on commonly used evaluation benchmarks, ensuring accurate and reliable assessments. Users can customize evaluations to their specific use cases through the Alignment Platform, allowing for fine-grained analysis and tailored scoring formats. The API provides actionable critiques alongside accurate evaluation scores, facilitating seamless integration into existing workflows. Pre-built metrics, such as relevance, correctness, helpfulness, faithfulness, logical coherence, and conciseness, are available to address common evaluation scenarios, including detecting hallucinations in retrieval-augmented generation applications or comparing outputs to ground truth data.
Learn more
Gen-3
Gen-3 Alpha is the first of an upcoming series of models trained by Runway on a new infrastructure built for large-scale multimodal training. It is a major improvement in fidelity, consistency, and motion over Gen-2, and a step towards building General World Models.
Trained jointly on videos and images, Gen-3 Alpha will power Runway's Text to Video, Image to Video and Text to Image tools, existing control modes such as Motion Brush, Advanced Camera Controls, Director Mode as well as upcoming tools for more fine-grained control over structure, style, and motion.
Learn more
Inkling
Inkling is an open-weights multimodal AI model from Thinking Machines designed as a customizable foundation model for developers, researchers, and enterprises. The model is a Mixture-of-Experts transformer with 975 billion total parameters, 41 billion active parameters, and support for context windows up to 1 million tokens. Inkling was trained from scratch on text, images, audio, and video, giving it native capabilities across reasoning, coding, agentic tool use, vision, audio, factuality, and instruction following. It is built with controllable thinking effort so users can balance performance, latency, and token efficiency for different workloads. The model is available for fine-tuning on Tinker, with playground access, API availability through ecosystem partners, and full weights published on Hugging Face. Built for customization, Inkling gives teams an open-weights base model for building domain-specific AI systems, multimodal agents, coding workflows, research tools, and more.
Learn more
MiniMax M3
MiniMax M3 is an open-weight multimodal AI model designed for coding, agentic workflows, long-context reasoning, and complex automation tasks. The model combines frontier-level coding performance, native multimodal understanding, and a context window of up to 1 million tokens. MiniMax M3 uses MiniMax Sparse Attention to improve long-context efficiency while reducing compute requirements for large-scale inputs. It supports text, image, and video understanding, making it useful for workflows that combine code, documents, visual references, and tool-driven tasks. The model is built for repository-scale reasoning, software engineering, autonomous task execution, tool calling, and multi-step agent workflows. MiniMax M3 helps developers, AI teams, and enterprises build capable agents that can reason across large contexts and work with multimodal information.
Learn more
Pricing
Starting Price:
Free
Pricing Details:
Open source
Free Version:
Free Version available.
Integrations
No integrations listed.
Company Information
Apple
Founded: 1976
United States
github.com/apple/ml-ferret
Other Useful Business Software
$300 Free Credits for Your Google Cloud Projects
Launch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
Product Details
Platforms Supported
Cloud
Training
Documentation