Models
Browse AI models on NagaAI and compare pricing, capabilities, uptime, and performance.
Browse AI models on NagaAI and compare pricing, capabilities, uptime, and performance.
Ling 3.0 Flash Sante is a health and medicine-focused mixture-of-experts model from InclusionAI, built on Ling 3.0 Flash with 5.1B active parameters out of 124B total. It is designed for medical knowledge reasoning, clinical safety, evidence-based retrieval, and long-horizon medical tasks, while retaining general capabilities in reasoning, coding, and agentic tasks.
Ling 3.0 Flash Fin is a finance-focused mixture-of-experts model from InclusionAI, built on Ling 3.0 Flash with 5.1B active parameters out of 124B total. It is designed for real-world investment workflows that require complex multi-step tasks and long-horizon planning and execution, while retaining general capabilities in reasoning, coding, and mathematics.
Dots3-Note Preview is an open-weight mixture-of-experts model from Dots Studio, with 16B active parameters out of 280B total. It is the lightest model in the Dots 3 family and is suited for reasoning, coding, multimodal understanding, long-context processing, and multi-step agent workflows.
LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing. Liquid advises against using it for agentic coding or knowledge-heavy tasks.
NVIDIA Nemotron 3.5 Lightning is an open mixture-of-experts model from NVIDIA, with 3B active parameters out of 30B total. It is suited for high-throughput agentic workloads and specialized tasks that benefit from domain-specific customization.
NVIDIA Nemotron 3 Ultra is an open frontier-reasoning and orchestration model from NVIDIA, with 55B active parameters out of 550B total (MoE). Built on a hybrid Transformer-Mamba mixture-of-experts architecture, it supports text input and output with a context window of up to 1M tokens. It is suited for long-running agentic workflows, including agent orchestration, coding agents, deep research, and complex enterprise tasks. It is particularly strong at multi-step reasoning and planning, with high-throughput inference designed for high-volume agent pipelines. It is part of the NVIDIA Nemotron family of open models for agentic AI.
NVIDIA Nemotron 3 Super is an open hybrid MoE model with 120B parameters, using only 12B active parameters to achieve high computational efficiency and strong accuracy in complex multi-agent scenarios. Based on a hybrid Mamba-Transformer Mixture-of-Experts architecture with multi-token prediction (MTP), it offers more than 50% faster token generation than leading open models. The model includes a 1M-token context window, enabling long-term agent consistency, cross-document reasoning, and multi-step task planning. Latent MoE makes it possible to engage 4 experts at the inference cost of just one, enhancing both intelligence and generalization. Reinforcement learning across more than 10 environments provides top-tier benchmark performance, including AIME 2025, TerminalBench, and SWE-Bench Verified. Released fully open with weights, datasets, and recipes under the NVIDIA Open License, Nemotron 3 Super supports simple customization and secure deployment in any environment — from local workstations to the cloud.
Eleven-Multilingual-v2 is ElevenLabs’ most advanced multilingual text-to-speech model, delivering high-quality voice synthesis across a wide range of languages with improved realism and expressiveness. It is optimized for both accuracy and naturalness in multilingual scenarios.
A text-to-speech model built on GPT-4o mini, a fast and powerful language model. Use it to convert text into natural-sounding spoken audio.
Flux-1-Schnell is a high-speed, open-source text-to-image model from Black Forest Labs, optimized for rapid, high-quality image generation in just a few steps. It is ideal for applications where speed and efficiency are critical.
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction-tuned generative model with 70B parameters. Optimized for multilingual dialogue, it outperforms many open-source and closed chat models on industry benchmarks. Supported languages include English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.
Whisper Large v3 is OpenAI’s state-of-the-art model for automatic speech recognition (ASR) and speech translation. Trained on over 5 million hours of labeled data, it demonstrates strong generalization across datasets and domains, excelling in zero-shot transcription and translation tasks.
Sonar is Perplexity’s lightweight, affordable, and fast question-answering model, now featuring citations and customizable sources. It is designed for companies seeking to integrate rapid, citation-enabled Q&A features optimized for speed and simplicity.
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model from Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input (text and image) and multilingual output (text and code) across 12 supported languages. Designed for assistant-style interaction and visual reasoning, Scout uses 16 experts per forward pass and features a context length of 10 million tokens, with a training corpus of ~40 trillion tokens. Built for high efficiency and local or commercial deployment, it is instruction-tuned for multilingual chat, captioning, and image understanding.