Browse all AI Gateway models
Every model available on Edgenivo AI Gateway, with API access, pricing, and a playground. 431 models · Page 6 of 8.
Search and filter all models →- AmazonNova 2 LiteNova 2 Lite is a fast, cost-effective reasoning model for everyday workloads that can process text, images, and videos to generate text.
- AmazonNova LiteA very low cost multimodal model that is lightning fast for processing image, video, and text inputs.
- AmazonNova MicroA text-only model that delivers the lowest latency responses at very low cost.
- AmazonNova ProA highly capable multimodal model with the best combination of accuracy, speed, and cost for a wide range of tasks.
- NVIDIANVIDIA Nemotron 3 Super 120B A12BNVIDIA Nemotron 3 Super is a 120B-parameter open hybrid MoE model, activating just 12B parameters for maximum compute efficiency and accuracy in complex multi-agent applications. It delivers up to 7x higher throughput, providing fast, cost-efficient inference for agentic tasks. Additionally, a long context window gives the model long-term memory, preventing AI agents from losing focus on long, multi-step tasks and ensuring high-accuracy results. Fully open with weights, datasets, and recipes, Super allows easy customization and secure deployment anywhere.
- NVIDIANVIDIA Nemotron 3.5 Super VLNVIDIA Nemotron 3.5 Super VL is a vision-language model for reasoning, coding, tool use, and document understanding. Its hybrid Mamba-2, attention, and Mixture-of-Experts architecture has 120B total parameters with 12B active per token. Baseten serves text and image inputs with up to one million tokens of context for long conversations and agent workflows.
- NVIDIANvidia Nemotron Nano 12B V2 VLThe model is an auto-regressive vision language model that uses an optimized transformer architecture. The model enables multi-image reasoning and video understanding, along with strong document intelligence, visual Q&A and summarization capabilities.
- NVIDIANvidia Nemotron Nano 9B V2NVIDIA-Nemotron-Nano-9B-v2 is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. It responds to user queries and tasks by first generating a reasoning trace and then concluding with a final response. The model's reasoning capabilities can be controlled via a system prompt. If the user prefers the model to provide its final answer without intermediate reasoning traces, it can be configured to do so.\
- OpenAIo1o1 is OpenAI's flagship reasoning model, designed for complex problems that require deep thinking. It provides strong reasoning capabilities with improved accuracy for complex multi-step tasks.
- OpenAIo3OpenAI's o3 is their most powerful reasoning model, setting new state-of-the-art benchmarks in coding, math, science, and visual perception. It excels at complex queries requiring multi-faceted analysis, with particular strength in analyzing images, charts, and graphics.
- OpenAIo3 ProThe o-series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o3-pro model uses more compute to think harder and provide consistently better answers.
- OpenAIo3-minio3-mini is OpenAI's most recent small reasoning model, providing high intelligence at the same cost and latency targets of o1-mini.
- OpenAIo4-miniOpenAI's o4-mini delivers fast, cost-efficient reasoning with exceptional performance for its size, particularly excelling in math (best-performing on AIME benchmarks), coding, and visual tasks.
- Parallel AIParallel SearchSearch the web with Parallel's Search API for LLM-optimized excerpts. Every mode costs the same ($5 per 1,000 searches, plus $1 per 1,000 results beyond 10): turbo and fast trade excerpt depth for lower latency (turbo supports English and Japanese only), basic is the balanced default, and advanced is the most thorough. Legacy one-shot and agentic modes still work, running as basic and advanced.
- Particle.AIParticle-1Particle-1 is Particle AI’s model for agentic coding and software engineering, post-trained on DeepSeek V4.1 Flash to complete tasks with fewer tokens. It supports text and image inputs, reasoning, tool use, and implicit prompt caching.
- PerplexityPerplexity SearchSearch the web using Perplexity's Search API for real-time information, news, research papers, and articles. Provides ranked search results with advanced filtering options including domain, language, date range, and recency filters.
- Topaz LabsProteusProteus is Topaz Labs’ video enhancement model for detail-preserving upscaling, denoising, and restoration. It enhances an existing video with automatic adjustments or fine control over detail recovery, compression artifacts, noise, blur, and grain. An input video and output resolution are required, supporting workflows that improve footage quality while preserving its source characteristics.
- Alibaba CloudQwen 3 32BQwen3-32B is a world-class model with comparable quality to DeepSeek R1 while outperforming GPT-4.1 and Claude Sonnet 3.7. It excels in code-gen, tool-calling, and advanced reasoning, making it an exceptional model for a wide range of production use cases.
- Alibaba CloudQwen 3 Coder 30B A3B InstructEfficient coding specialist balancing performance with cost-effectiveness for daily development tasks while maintaining strong tool integration capabilities.
- Alibaba CloudQwen 3 Max ThinkingCompared with the snapshot as of September 23, 2025, the Qwen-3 series Max model in this release achieves an effective integration of thinking and non-thinking modes, resulting in a comprehensive and substantial improvement in the model’s overall performance. In thinking mode, the model simultaneously supports web search, web information extraction, and a code interpreter tool, enabling it to tackle more complex and challenging problems with greater accuracy by leveraging external tools while engaging in slow, deliberative reasoning. This version is based on a snapshot taken on January 23, 2026.
- Alibaba CloudQwen 3 VL 235B A22B Instruct
- Alibaba CloudQwen 3.5 FlashThe Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. Compared to the 3 series, these models deliver a leap forward in performance for both pure text and multimodal tasks, offering fast response times while balancing inference speed and overall performance.
- Alibaba CloudQwen 3.5 PlusThe Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models, achieving higher inference efficiency. In a variety of task evaluations, the 3.5 series consistently demonstrates performance on par with state-of-the-art leading models. Compared to the 3 series, these models show a leap forward in both pure-text and multimodal capabilities.
- Alibaba CloudQwen 3.6 27BThe Qwen3.6 35B-A3B native vision-language model is built on a hybrid architecture that integrates linear attention mechanisms with a sparse mixture-of-experts framework, achieving higher inference efficiency. Compared with the 3.5-35B-A3B, this model demonstrates significantly improved agentic coding capabilities, mathematical and code reasoning abilities, spatial intelligence, as well as object localization and object detection performance.
- Alibaba CloudQwen 3.6 PlusThe Qwen3.6 native vision-language Plus series models demonstrate exceptional performance on par with the current state-of-the-art models, with a significant improvement in overall results compared to the 3.5 series. The models have been markedly enhanced in code-related capabilities such as agentic coding, front-end programming, and Vibe coding, as well as in multi-modal general object recognition, OCR, and object localization.
- Alibaba CloudQwen 3.7 FlashThe Qwen3.7 native vision-language Flash model series delivers a comprehensive upgrade over 3.6-Flash in multimodal understanding and agent execution. This model particularly excels in enhanced multimodal foundations with stronger universal object recognition, further improved real-world perception and spatial intelligence, significantly upgraded multimodal agent capabilities for Search Agent and CI Agent scenarios with more stable end-to-end task execution, as well as optimized multimodal coding for a smoother vibe coding experience.
- Alibaba CloudQwen 3.7 MaxQwen3.7 is a next‑generation flagship model designed for the agent‑centric era, with its core strengths lying in the breadth and depth of its agent‑level capabilities: it excels at programming, office and productivity tasks, and long‑term autonomous execution.
- Alibaba CloudQwen 3.7 PlusAmong the Qwen3.7 series, the cost-effective Plus model builds on its robust text capabilities while delivering a comprehensive upgrade to its vision‑language abilities, all while preserving its full‑stack agent‑level intelligence for coding, tool use, and productivity workflows.
- Alibaba CloudQwen 3.8 27BAlibaba's 27B dense multimodal model for agentic coding, tool use, research, and long-running workflows.
- Alibaba CloudQwen 3.8 FlashQwen3.8-Flash is Qwen’s fast, cost-efficient multimodal model, combining advanced reasoning and generation with a native 1M-token context window. Built for coding, agentic workflows, and visual understanding, it handles large codebases, long documents, charts, videos, and desktop applications.
- Alibaba CloudQwen 3.8 MaxQwen 3.8 Max is a 2.4-trillion-parameter MoE model delivering a comprehensive leap in coding and professional work. Autonomously codes and delivers complete projects spanning 10+ days. Handles hundreds of specialized tasks across legal, financial, design, and other professional domains, producing production-grade results end-to-end in a single conversation. Native visual understanding runs through the full cycle of planning, execution, and verification, enabling deep semantic analysis of ultra-long documents and extended video content. In long-horizon tasks, plans autonomously, iterates through closed feedback loops, and continuously evolves.
- Alibaba CloudQwen 3.8 Max PrimeQwen 3.8 Max Prime is the high-speed edition of Qwen 3.8 Max, retaining its 2.4-trillion-parameter MoE architecture and full capabilities while delivering 1.5–2× higher output throughput. Built for coding, office automation, and long-running agent workflows, it supports autonomous multi-day development, professional knowledge work, and visual understanding with a 1M-token context window.
- Alibaba CloudQwen 3.8 Omni FlashQwen3.8-Omni-Flash is Alibaba’s native multimodal model for understanding text, images, audio, and video and generating text. Built on Qwen3.8-Flash-Next, it supports a 1M-token context window, reasoning, and tool calling for coding, knowledge work, and multimedia analysis.
- Alibaba CloudQwen3 235B A22BQwen3-235B-A22B-Instruct-2507 is the updated version of the Qwen3-235B-A22B non-thinking mode, featuring Significant improvements in general capabilities, including instruction following, logical reasoning, text comprehension, mathematics, science, coding and tool usage.
- Alibaba CloudQwen3 Coder 480B A35B InstructMixture-of-experts LLM with advanced coding and reasoning capabilities
- Alibaba CloudQwen3 Coder NextQwen3-Coder-Next is an open-weight language model built specifically for coding, with strong performance on large-scale software engineering and agentic coding benchmarks. It uses a hybrid Mixture-of-Experts architecture to offer high capability at relatively modest active parameter counts, improving efficiency for real-world deployments. The model is trained on diverse code and natural language data so it can handle tasks like code generation, refactoring, debugging, repository-level reasoning, and technical explanation across multiple programming languages. It is also optimized for tool use and function calling, making it suitable as the core of coding agents that interact with shells, editors, issue trackers, and other developer tools.
- Alibaba CloudQwen3 Embedding 0.6BThe Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon the dense foundational models of the Qwen3 series, it provides a comprehensive range of text embeddings and reranking models in various sizes (0.6B, 4B, and 8B).
- Alibaba CloudQwen3 Embedding 4BThe Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon the dense foundational models of the Qwen3 series, it provides a comprehensive range of text embeddings and reranking models in various sizes (0.6B, 4B, and 8B).
- Alibaba CloudQwen3 Embedding 8BThe Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon the dense foundational models of the Qwen3 series, it provides a comprehensive range of text embeddings and reranking models in various sizes (0.6B, 4B, and 8B).
- Alibaba CloudQwen3 Next 80B A3B InstructA new generation of open-source, non-thinking mode model powered by Qwen3. This version demonstrates superior Chinese text understanding, augmented logical reasoning, and enhanced capabilities in text generation tasks over the previous iteration (Qwen3-235B-A22B-Instruct-2507).
- Alibaba CloudQwen3 Next 80B A3B ThinkingQwen3-Next uses a highly sparse MoE design: 80B total parameters, but only ~3B activated per inference step. Experiments show that, with global load balancing, increasing total expert parameters while keeping activated experts fixed steadily reduces training loss.Compared to Qwen3’s MoE (128 total experts, 8 routed), Qwen3-Next expands to 512 total experts, combining 10 routed experts + 1 shared expert — maximizing resource usage without hurting performance. The Qwen3-Next-80B-A3B-Thinking excels at complex reasoning tasks — outperforming higher-cost models like Qwen3-30B-A3B-Thinking-2507 and Qwen3-32B-Thinking, outpeforming the closed-source Gemini-2.5-Flash-Thinking on multiple benchmarks, and approaching the performance of our top-tier model Qwen3-235B-A22B-Thinking-2507.
- Alibaba CloudQwen3 VL 235B A22B InstructThe Qwen3 series VL models has been comprehensively upgraded in areas such as visual coding and spatial perception. Its visual perception and recognition capabilities have significantly improved, supporting the understanding of ultra-long videos, and its OCR functionality has undergone a major enhancement.
- Alibaba CloudQwen3-14BQwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancements in reasoning, instruction-following, agent capabilities, and multilingual support
- Alibaba CloudQwen3-30B-A3BQwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancements in reasoning, instruction-following, agent capabilities, and multilingual support
- Alibaba CloudQwen3.8 2.4T A95BOpen-weights release of the Qwen3.8 flagship (2.4T MoE, ~95B active); thinking always on with reasoning_effort low/medium/xhigh. The hosted Qwen 3.8 Max (vision, non-thinking, 1M default context) is Alibaba-only.
- Alibaba CloudQwen3.8 Max 0902Qwen3.8-Max-0902 is an upgraded snapshot of qwen3.8-max.
- RecraftRecraft V2Recraft V2 is an image generation model released in March 2024 and the first model trained from scratch by Recraft. With 20 billion parameters, it was a breakthrough in human anatomical accuracy and the first to support brand consistency and brand color inputs. It also introduced vector image generation (SVG output), as well as minimalistic icon and illustration styles.
- RecraftRecraft V3V3 introduced major advances in photorealism and text rendering. It was the first Recraft model to generate mid-size text accurately and, as of 2025, is the only model capable of placing text at specific positions in an image.
- RecraftRecraft V4The model delivers strong photorealism, including realistic skin rendering and natural textures, while avoiding common synthetic artifacts. It produces more distinctive lighting, composition, diverse subjects, contemporary styling, and carefully considered scene elements. For illustration, it generates original characters and forms with sophisticated and unexpected color combinations.
- RecraftRecraft V4 ProThe model delivers strong photorealism, including realistic skin rendering and natural textures, while avoiding common synthetic artifacts. It produces more distinctive lighting, composition, diverse subjects, contemporary styling, and carefully considered scene elements. For illustration, it generates original characters and forms with sophisticated and unexpected color combinations.
- RecraftRecraft V4.1V4.1 is built on the same visual aesthetic and the same eye for what looks right, just pushed further across every dimension. The photorealism is more natural. The gradients are dreamier. Illustration styles are now possible that simply weren't before. And this is a model that reads a short prompts easier and creates something worth stopping for.
- RecraftRecraft V4.1 FlashRecraft V4.1 Flash is a fast, low-cost model with quality close to Recraft V4.1, built for high-volume generation and rapid iteration. Strong use cases include photography, portraits, atmosphere, complex scenes, mixed media, and logo concepts.
- RecraftRecraft V4.1 ProV4.1 is built on the same visual aesthetic and the same eye for what looks right, just pushed further across every dimension. The photorealism is more natural. The gradients are dreamier. Illustration styles are now possible that simply weren't before. And this is a model that reads a short prompts easier and creates something worth stopping for. V4.1 Pro generates higher-resolution images for when the idea deserves more room.
- RecraftRecraft V4.1 UtilityV4.1 is built on the same visual aesthetic and the same eye for what looks right, just pushed further across every dimension. The photorealism is more natural. The gradients are dreamier. Illustration styles are now possible that simply weren't before. And this is a model that reads a short prompts easier and creates something worth stopping for. V4.1 Utility is designed for when restraint is the aesthetic choice, with flat lighting, front-facing composition, and simple, controlled scenes.
- RecraftRecraft V4.1 Utility ProV4.1 is built on the same visual aesthetic and the same eye for what looks right, just pushed further across every dimension. The photorealism is more natural. The gradients are dreamier. Illustration styles are now possible that simply weren't before. And this is a model that reads a short prompts easier and creates something worth stopping for. V4.1 Utility is designed for when restraint is the aesthetic choice, with flat lighting, front-facing composition, and simple, controlled scenes.
- Fish AudioS1Fish Audio S1 is trained on over 2 million hours of audio with online RLHF (GRPO). It achieves 0.8% WER and 0.4% CER on Seed TTS Eval. S1 supports open-domain emotion, tone, and special effect markers.
- Fish AudioS2 ProFish Audio S2 is the second-generation TTS model from Fish Audio. It's trained on over 10 million hours of audio across approximately 80 languages, and it introduces inline tag control: natural-language instructions embedded directly in your script at any position, giving you fine-grained direction over how speech is delivered at the word or phrase level.
- Fish AudioS2.1 ProS2.1 Pro is Fish Audio's current state-of-the-art voice model — the best model we have, now available to every developer for free via API. It is a neural speech synthesis model designed for production-grade AI voice generation, with particular strengths in low-latency streaming, multilingual TTS, and voice cloning.
- Sakana AISakana NamazuSakana Namazu is a Japanese-specialized LLM that combines a deep understanding of Japanese culture and business customs with high-performance language capabilities. Built on the open model Kimi K2.6 and refined with Sakana AI's in-house data for Japanese language and business workflows, it handles complex tasks using web search and code execution. Unlike Fugu, which orchestrates multiple frontier models, Sakana Namazu provides a single in-house model as an API.
- Inference.netSchematron V2 SmallSchematron V2 Small is a specialized model from Inference.net for extracting structured data from HTML. It uses a supplied JSON Schema to produce conforming JSON and is designed for complex schemas and long pages.