AI Model Catalogue

Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual...

Meta Llama 3 8B Instruct — Meta's Llama open-source language model, one of the most widely deployed open models.

This 17-billion parameter mixture-of-experts model with 128 experts, optimized for instruction-following tasks with an expansive 1 million token context window, serves developers and organizations needing cost-effective long-document processing and complex reasoning while maintaining high performance across diverse applications.

A powerful open-source language model with 66K token context window designed for developers and researchers who need advanced instruction-following capabilities, multilingual support, and efficient processing of long documents across complex reasoning, code generation, and content creation tasks.

This powerful open-source mixture-of-experts model excels at complex reasoning, code generation, and multi-language tasks with a 16K token context window, making it ideal for developers and enterprises seeking cost-effective high-performance inference for demanding applications.

This lightweight 7-billion parameter instruction-tuned model excels at general-purpose tasks, coding, and reasoning with a 33K token context window, making it ideal for developers and organizations seeking cost-effective inference at $0.20 per million input tokens without sacrificing quality.

A specialized coding assistant designed for developers who need advanced programming support with a 16K token context window, offering cost-effective access at $0.80 per million input tokens for tasks like code generation, debugging, and technical problem-solving.

This high-performance mixture-of-experts language model with 16K token context excels at complex reasoning, multi-step problem solving, and handling lengthy documents, making it ideal for developers and enterprises requiring advanced AI capabilities for technical tasks, code generation, and sophisticated content analysis.

This instruction-following model with 262K token context excels at handling long documents, complex reasoning tasks, and detailed conversations, making it ideal for developers and enterprises needing efficient processing of extended content without sacrificing performance.

This lightweight 3 billion parameter instruction-tuned model excels at fast, cost-effective text generation and reasoning tasks with a 33K token context window, making it ideal for developers and organizations seeking efficient performance on resource-constrained devices or high-throughput applications.

This compact 1.5B parameter instruction-tuned model excels at lightweight conversational tasks and quick inference for developers and organizations seeking cost-effective AI with a 33K token context window, ideal for resource-constrained environments and budget-sensitive applications.

Qwen3-Coder-30B-A3B-Instruct is a 30.5B parameter Mixture-of-Experts (MoE) model with 128 experts (8 active per forward pass), designed for advanced code generation, repository-scale understanding, and agentic tool use. Built on the...

Qwen3-VL-8B-Instruct is a multimodal vision-language model from the Qwen3-VL series, built for high-fidelity understanding and reasoning across text, images, and video. It features improved multimodal fusion with Interleaved-MRoPE for long-horizon...

Rnj-1 is an 8B-parameter, dense, open-weight model family developed by Essential AI and trained from scratch with a focus on programming, math, and scientific reasoning. The model demonstrates strong performance...

Qwen3-VL-32B-Instruct is a large-scale multimodal vision-language model designed for high-precision understanding and reasoning across text, images, and video. With 32 billion parameters, it combines deep visual perception with advanced text...