AI Model Catalogue

This large language model excels at complex reasoning, multi-turn conversations, and long-form content generation with its 131K token context window, making it ideal for developers and enterprises needing cost-effective, high-performance instruction-following capabilities for production applications.

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 1.5B parameter language model excels at instruction-following tasks with a 33K token context window, making it ideal for developers and organizations seeking fast, efficient inference for text generation, summarization, and question-answering applications on resource-constrained devices or cost-sensitive deployments.

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.

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

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...

This instruction-tuned 8 billion parameter language model excels at following user directions for tasks like question answering, summarization, and creative writing, making it ideal for developers and organizations seeking a fast, cost-effective alternative to larger models without sacrificing quality on most general-purpose NLP applications.

Mixtral 8×7B Instruct on DeepInfra — popular MoE model with 32K context and strong multilingual performance.

Qwen3-VL-30B-A3B-Instruct is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Instruct variant optimizes instruction-following for general multimodal tasks. It excels in perception...

Meta Llama 3.1 8B Instruct on DeepInfra — fast, affordable open-source model with 128K context.

Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...

Mistral Small 3 is a 24B-parameter language model optimized for low-latency performance across common AI tasks. Released under the Apache 2.0 license, it features both pre-trained and instruction-tuned versions designed...

Alibaba Qwen2.5 72B Instruct on DeepInfra — top open-source model with multilingual and coding strengths.

This instruction-tuned 32-billion parameter language model excels at following complex directives and generating coherent text across diverse tasks, making it ideal for developers and researchers seeking a capable open-source alternative to proprietary models for applications like content generation, code assistance, and question answering.

This large-scale code generation and software development model excels at complex programming tasks, algorithm design, and technical problem-solving, making it ideal for professional developers, software engineers, and technical teams seeking advanced AI-assisted coding capabilities.

This multimodal AI model excels at understanding and reasoning about images alongside text, making it ideal for developers and enterprises building applications requiring visual question answering, document analysis, and image-to-text tasks at scale.

I don't have verified information about a model called "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8" in my training data, so I cannot provide a factually accurate description of this specific model without risking misinformation.

Ministral 3 (a.k.a. Tinystral) 3B Instruct.

Ministral 3 (a.k.a. Tinystral) 8B Instruct.

Ministral 3 (a.k.a. Tinystral) 8B Instruct.

Ministral 3 (a.k.a. Tinystral) 14B Instruct.