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assets/amazon.yaml

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prohibited_uses: ''
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monitoring: ''
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feedback: https://github.com/amazon-science/chronos-forecasting/discussions
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- type: model
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name: Amazon Nova (Understanding)
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organization: Amazon Web Services (AWS)
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description: A new generation of state-of-the-art foundation models (FMs) that
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deliver frontier intelligence and industry leading price performance, available
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exclusively in Amazon Bedrock. Amazon Nova understanding models excel in Retrieval-Augmented
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Generation (RAG), function calling, and agentic applications.
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created_date: 2024-12-03
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url: https://aws.amazon.com/blogs/aws/introducing-amazon-nova-frontier-intelligence-and-industry-leading-price-performance/
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model_card: unknown
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modality:
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explanation: Amazon Nova understanding models accept text, image, or video inputs
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to generate text output.
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value: text, image, video; text
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analysis: Amazon Nova Pro is capable of processing up to 300K input tokens and
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sets new standards in multimodal intelligence and agentic workflows that require
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calling APIs and tools to complete complex workflows. It achieves state-of-the-art
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performance on key benchmarks including visual question answering ( TextVQA
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) and video understanding ( VATEX ).
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size: unknown
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dependencies: []
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training_emissions: unknown
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training_time: unknown
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training_hardware: unknown
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quality_control: All Amazon Nova models include built-in safety controls and creative
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content generation models include watermarking capabilities to promote responsible
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AI use.
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access:
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explanation: available exclusively in Amazon Bedrock
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value: limited
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license: unknown
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intended_uses: You can build on Amazon Nova to analyze complex documents and videos,
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understand charts and diagrams, generate engaging video content, and build sophisticated
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AI agents, from across a range of intelligence classes optimized for enterprise
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workloads.
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prohibited_uses: unknown
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monitoring: unknown
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feedback: unknown
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- type: model
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name: Amazon Nova (Creative Content Generation)
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organization: Amazon Web Services (AWS)
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description: A new generation of state-of-the-art foundation models (FMs) that
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deliver frontier intelligence and industry leading price performance, available
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exclusively in Amazon Bedrock.
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created_date: 2024-12-03
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url: https://aws.amazon.com/blogs/aws/introducing-amazon-nova-frontier-intelligence-and-industry-leading-price-performance/
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model_card: unknown
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modality:
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explanation: Amazon creative content generation models accept text and image
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inputs to generate image or video output.
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value: text, image;image, video
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analysis: Amazon Nova Canvas excels on human evaluations and key benchmarks such
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as text-to-image faithfulness evaluation with question answering (TIFA) and
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ImageReward.
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size: unknown
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dependencies: []
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training_emissions: unknown
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training_time: unknown
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training_hardware: unknown
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quality_control: All Amazon Nova models include built-in safety controls and creative
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content generation models include watermarking capabilities to promote responsible
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AI use.
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access:
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explanation: available exclusively in Amazon Bedrock
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value: limited
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license: unknown
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intended_uses: You can build on Amazon Nova to analyze complex documents and videos,
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understand charts and diagrams, generate engaging video content, and build sophisticated
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AI agents, from across a range of intelligence classes optimized for enterprise
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workloads.
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prohibited_uses: unknown
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monitoring: unknown
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feedback: unknown

assets/anthropic.yaml

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speed of its predecessor, Claude 3 Opus, and is designed to tackle tasks like
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context-sensitive customer support, orchestrating multi-step workflows, interpreting
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charts and graphs, and transcribing text from images.
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created_date: 2024-06-21
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url: https://www.anthropic.com/news/claude-3-5-sonnet
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created_date:
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explanation: Claude 3.5 Sonnet updated on Oct. 22, initially released on June
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20 of the same year.
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value: 2024-10-22
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url: https://www.anthropic.com/news/3-5-models-and-computer-use
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model_card: unknown
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modality: text; image, text
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analysis: The model has been evaluated on a range of tests including graduate-level
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reasoning (GPQA), undergraduate-level knowledge (MMLU), coding proficiency (HumanEval),
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and standard vision benchmarks. In an internal agentic coding evaluation, Claude
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3.5 Sonnet solved 64% of problems, outperforming the previous version, Claude
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3 Opus, which solved 38%.
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and standard vision benchmarks. Claude 3.5 Sonnet demonstrates state-of-the-art
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performance on most benchmarks.
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size: Unknown
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dependencies: []
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training_emissions: Unknown
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integrated to ensure robustness of evaluations.
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feedback: Feedback on Claude 3.5 Sonnet can be submitted directly in-product to
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inform the development roadmap and improve user experience.
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- type: model
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name: Claude 3.5 Haiku
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organization: Anthropic
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description: Claude 3.5 Haiku is Anthropic's fastest model, delivering advanced
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coding, tool use, and reasoning capability, surpassing the previous Claude 3
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Opus in intelligence benchmarks. It is designed for critical use cases where
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low latency is essential, such as user-facing chatbots and code completions.
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created_date: 2024-10-22
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url: https://www.anthropic.com/claude/haiku
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model_card: unknown
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modality:
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explanation: Claude 3.5 Haiku is available...initially as a text-only model
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and with image input to follow.
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value: text; unknown
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analysis: Claude 3.5 Haiku offers strong performance and speed across a variety
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of coding, tool use, and reasoning tasks. Also, it has been tested in extensive
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safety evaluations and exceeded expectations in reasoning and code generation
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tasks.
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size: unknown
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dependencies: []
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training_emissions: unknown
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training_time: unknown
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training_hardware: unknown
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quality_control: During Claude 3.5 Haiku’s development, we conducted extensive
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safety evaluations spanning multiple languages and policy domains.
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access:
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explanation: Claude 3.5 Haiku is available across Claude.ai, our first-party
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API, Amazon Bedrock, and Google Cloud’s Vertex AI.
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value: open
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license: unknown
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intended_uses: Critical use cases where low latency matters, like user-facing
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chatbots and code completions.
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prohibited_uses: unknown
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monitoring: unknown
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feedback: unknown

assets/cohere.yaml

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prohibited_uses: unknown
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monitoring: unknown
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feedback: https://huggingface.co/CohereForAI/aya-23-35B/discussions
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- type: model
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name: Command R+
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organization: Cohere
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description: Command R+ is a state-of-the-art RAG-optimized model designed to
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tackle enterprise-grade workloads, and is available first on Microsoft Azure.
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created_date: 2024-04-04
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url: https://cohere.com/blog/command-r-plus-microsoft-azure
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model_card: unknown
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modality: unknown
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analysis: unknown
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size: unknown
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dependencies: []
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training_emissions: unknown
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training_time: unknown
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training_hardware: unknown
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quality_control: unknown
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access: ''
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license: unknown
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intended_uses: unknown
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prohibited_uses: unknown
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monitoring: unknown
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feedback: unknown

assets/genmo.yaml

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---
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- type: model
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name: Mochi 1
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organization: Genmo
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description: Mochi 1 is an open-source video generation model designed to produce
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high-fidelity motion and strong prompt adherence in generated videos, setting
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a new standard for open video generation systems.
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created_date: 2025-01-14
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url: https://www.genmo.ai/blog
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model_card: unknown
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modality:
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explanation: Mochi 1 generates smooth videos... Measures how accurately generated
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videos follow the provided textual instructions
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value: text; video
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analysis: Mochi 1 sets a new best-in-class standard for open-source video generation.
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It also performs very competitively with the leading closed models... We benchmark
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prompt adherence with an automated metric using a vision language model as a
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judge following the protocol in OpenAI DALL-E 3. We evaluate generated videos
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using Gemini-1.5-Pro-002.
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size:
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explanation: featuring a 10 billion parameter diffusion model
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value: 10B parameters
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dependencies: [DDPM, DreamFusion, Emu Video, T5-XXL]
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training_emissions: unknown
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training_time: unknown
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training_hardware: unknown
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quality_control: robust safety moderation protocols in the playground to ensure
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that all video generations remain safe and aligned with ethical guidelines.
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access:
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explanation: open state-of-the-art video generation model... The weights and
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architecture for Mochi 1 are open
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value: open
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license:
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explanation: We're releasing the model under a permissive Apache 2.0 license.
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value: Apache 2.0
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intended_uses: Advance the field of video generation and explore new methodologies.
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Build innovative applications in entertainment, advertising, education, and
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more. Empower artists and creators to bring their visions to life with AI-generated
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videos. Generate synthetic data for training AI models in robotics, autonomous
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vehicles and virtual environments.
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prohibited_uses: unknown
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monitoring: unknown
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feedback: unknown

assets/google.yaml

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monitoring: "After giving the community time to use the models and explore different applications, we collected feedback."
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feedback: unknown
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- type: model
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name: Genie 2
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organization: Google DeepMind
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description: Genie 2 is a foundation world model capable of generating an endless variety of action-controllable, playable 3D environments for training and evaluating embodied agents based on a single prompt image.
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created_date: 2024-12-04
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url: https://deepmind.google/discover/blog/genie-2-a-large-scale-foundation-world-model/
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model_card: unknown
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modality:
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explanation: "the model is prompted with a single image generated by Imagen 3"
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value: image; video
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analysis: Unknown
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size: Unknown
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dependencies: [Imagen 3]
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training_emissions: Unknown
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training_time: Unknown
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training_hardware: Unknown
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quality_control: Responsible development is emphasized, developing our technologies responsibly and building towards more general AI systems that can safely carry out tasks.
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access: closed
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license: Unknown
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intended_uses: Genie 2 can be used for generating diverse environments for training and evaluating AI agents, rapid prototyping interactive experiences, and experimenting with novel environments.
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prohibited_uses: Unknown
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monitoring: Unknown
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feedback: Unknown
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- type: model
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name: Veo 2
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organization: Google DeepMind
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description: Veo 2 is a state-of-the-art video generation model that creates videos
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with realistic motion and high-quality output, up to 4K, with extensive camera
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controls. It simulates real-world physics and offers advanced motion capabilities
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with enhanced realism and fidelity.
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created_date: 2024-12-16
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url: https://deepmind.google/technologies/veo/veo-2/
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model_card: unknown
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modality:
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explanation: Our state-of-the-art video generation model ... text-to-image model
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Veo 2
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value: text; video
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analysis: Veo 2 outperforms other leading video generation models, based on human
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evaluations of its performance.
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size: unknown
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dependencies: []
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training_emissions: unknown
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training_time: unknown
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training_hardware: unknown
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quality_control: Veo 2 includes features that enhance realism, fidelity, detail,
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and artifact reduction to ensure high-quality output.
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access: limited
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license: unknown
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intended_uses: Creating high-quality videos with realistic motion, different styles,
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camera controls, shot styles, angles, and movements.
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prohibited_uses: unknown
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monitoring: unknown
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feedback: unknown
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- type: model
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name: Gemini 2.0
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organization: Google DeepMind
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description: Google DeepMind introduces Gemini 2.0, a new AI model designed for
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the 'agentic era.'
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created_date: 2024-12-11
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url: https://blog.google/technology/google-deepmind/google-gemini-ai-update-december-2024/#ceo-message
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model_card: unknown
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modality:
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explanation: The first model built to be natively multimodal, Gemini 1.0 and
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1.5 drove big advances with multimodality and long context to understand information
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across text, video, images, audio and code...
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value: text, video, image, audio; image, text
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analysis: unknown
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size: unknown
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dependencies: []
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training_emissions: unknown
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training_time: unknown
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training_hardware:
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explanation: It’s built on custom hardware like Trillium, our sixth-generation
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TPUs.
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value: custom hardware like Trillium, our sixth-generation TPUs
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quality_control: Google is committed to building AI responsibly, with safety and
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security as key priorities.
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access:
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explanation: Gemini 2.0 Flash is available to developers and trusted testers,
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with wider availability planned for early next year.
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value: limited
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license: unknown
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intended_uses: Develop more agentic models, meaning they can understand more about
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the world around you, think multiple steps ahead, and take action on your behalf,
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with your supervision.
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prohibited_uses: unknown
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monitoring: unknown
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feedback: unknown
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assets/ibm.yaml

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prohibited_uses: ''
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monitoring: ''
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feedback: ''
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- type: model
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name: IBM Granite 3.0
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organization: IBM
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description: IBM Granite 3.0 models deliver state-of-the-art performance relative
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to model size while maximizing safety, speed and cost-efficiency for enterprise
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use cases.
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created_date: 2024-10-21
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url: https://www.ibm.com/new/ibm-granite-3-0-open-state-of-the-art-enterprise-models
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model_card: unknown
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modality:
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explanation: IBM Granite 3.0 8B Instruct model for classic natural language
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use cases including text generation, classification, summarization, entity
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extraction and customer service chatbots
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value: text; text
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analysis: Granite 3.0 8B Instruct matches leading similarly-sized open models
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on academic benchmarks while outperforming those peers on benchmarks for enterprise
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tasks and safety.
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size:
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explanation: 'Dense, general purpose LLMs: Granite-3.0-8B-Instruct'
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value: 8B parameters
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dependencies: [Hugging Face’s OpenLLM Leaderboard v2]
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training_emissions: unknown
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training_time: unknown
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training_hardware: unknown
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quality_control: The entire Granite family of models are trained on carefully
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curated enterprise datasets, filtered for objectionable content with critical
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concerns like governance, risk, privacy and bias mitigation in mind
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access:
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explanation: In keeping with IBM’s strong historical commitment to open source
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, all Granite models are released under the permissive Apache 2.0 license
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value: open
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license:
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explanation: In keeping with IBM’s strong historical commitment to open source
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, all Granite models are released under the permissive Apache 2.0 license
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value: Apache 2.0
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intended_uses: classic natural language use cases including text generation, classification,
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summarization, entity extraction and customer service chatbots, programming
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language use cases such as code generation, code explanation and code editing,
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and for agentic use cases requiring tool calling
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prohibited_uses: unknown
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monitoring: ''
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feedback: unknown

assets/inflection.yaml

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prohibited_uses: ''
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monitoring: ''
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feedback: none
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- type: model
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name: Inflection 3.0
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organization: Inflection AI
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description: Inflection for Enterprise, powered by our industry-first, enterprise-grade
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AI system, Inflection 3.0.
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created_date: 2024-10-07
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url: https://inflection.ai/blog/enterprise
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model_card: unknown
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modality: unknown
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analysis: unknown
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size: unknown
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dependencies: []
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training_emissions: unknown
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training_time: unknown
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training_hardware: unknown
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quality_control: unknown
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access:
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explanation: Developers can now access Inflection AI’s Large Language Model
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through its new commercial API.
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value: open
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license: unknown
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intended_uses: unknown
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prohibited_uses: unknown
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monitoring: unknown
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feedback: So please drop us a line. We want to keep hearing from enterprises about
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how we can help solve their challenges and make AI a reality for their business.

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