AI Model Catalogue

A 671-billion parameter mixture-of-experts language model optimized for research, development, and production applications, suitable for researchers, developers, and organizations seeking high-performance reasoning and coding capabilities with efficient inference costs.

A highly capable frontier language model with 164K token context window designed for researchers, developers, and enterprises seeking strong performance across reasoning, coding, mathematics, and multilingual tasks with efficient inference.

A compact 7-billion parameter language model distilled from DeepSeek R1's reasoning capabilities, optimized for developers and researchers who need efficient reasoning and problem-solving on resource-constrained hardware while maintaining a 131K token context window for processing long documents.

I don't have reliable information about a model called "HiDream-I1-Fast" by hidream-ai in my training data. I cannot provide a specific and factual description without verified information about this model's capabilities and intended users. I'd recommend checking the official hidream-ai documentation or website for accurate details.

I don't have reliable information about a specific model called "Wan 2.6 Image" by wan-ai in my training data, so I cannot provide an accurate description without risking factual errors. I'd recommend checking the official wan-ai documentation or website for an authoritative description of this model's capabilities and intended users.

This 12B parameter instruction-tuned model excels at fast, cost-effective reasoning and creative tasks with up to 16K token context, making it ideal for developers and enterprises seeking a balanced alternative to larger models for customer service, content generation, and real-time applications with moderate computational constraints.

This lightweight 0.6 billion parameter text-to-speech model excels at converting written text into natural-sounding speech with low latency, making it ideal for developers and enterprises who need efficient on-device or edge deployment of voice synthesis applications.

I don't have reliable information about a specific AI model called "Kling 1.6 Pro" by "kwaivgi" in my training data, so I cannot provide an accurate factual description of it. If you could provide more context about what this model does or verify the exact name and organization, I'd be happy to help you craft an appropriate description.

This 14-billion-parameter language model with 131K token context window excels at processing long documents and complex reasoning tasks, making it ideal for researchers, developers, and enterprises needing extended context handling for document analysis, code generation, and multi-turn conversations.

This high-capacity language model excels at complex reasoning, detailed content generation, and multi-turn conversations across professional domains, making it ideal for developers, enterprises, and power users who need nuanced responses within a 16K token context window.

NVIDIA's Llama 3.1 Nemotron 70B Instruct — fine-tuned for helpfulness and aligned with human preferences.

Bria/erase — served on DeepInfra's GPU cloud for scalable, cost-efficient inference.

Meta Llama 3.1 70B Instruct on DeepInfra — powerful open-source model for complex reasoning tasks.