Browse all AI Gateway models
Every model available on Vercel AI Gateway, with API access, pricing, and a playground. 404 models · Page 5 of 7.
Search and filter all models →- XiaomiMiMo V2.6 FlashMiMo V2.6 Flash is Xiaomi's efficient multimodal reasoning model for coding, automation, and everyday agent workflows. It accepts text, images, audio, and video within a 1M-token context window, with up to 128K tokens of output. Deep thinking, tool calling, JSON mode, and prompt caching make it suitable for applications that need multimodal understanding at a lower token cost.
- XiaomiMiMo V2.6 ProMiMo V2.6 Pro is Xiaomi's flagship multimodal reasoning model for complex software engineering, long-running agent tasks, and professional workflows. It supports text, image, audio, and video inputs with a 1M-token context window and up to 128K tokens of output. Deep thinking, tool calling, JSON mode, and prompt caching support applications that combine large inputs with multi-step reasoning.
- XiaomiMiMo V2.6 Pro UltraSpeedMiMo V2.6 Pro UltraSpeed is Xiaomi's accelerated inference offering for MiMo V2.6 Pro, designed for interactive agents and workflows where response latency matters. It combines multimodal understanding of text, images, audio, and video with a 1M-token context window and up to 128K tokens of output. It supports deep thinking, tool calling, JSON mode, and prompt caching.
- MiniMaxMiniMax H3H3 is a next-generation open-weights, general-purpose multimodal video model. Rather than being limited to specialized tasks such as generating, editing, or referencing, H3 understands multimodal contexts that bring together text, images, video, and audio. This enables it to interpret creative intent in a unified way and deliver more natural, coherent generation and expression.
- MiniMaxMiniMax H3 MaxMiniMax H3 Max is a next-generation general-purpose multimodal video model ranking #1 for overall quality, prompt understanding, and aesthetics in all evaluations, while generating a 5-second video in under 3 seconds.
- MiniMaxMiniMax M2MiniMax-M2 redefines efficiency for agents. It is a compact, fast, and cost-effective MoE model (230 billion total parameters with 10 billion active parameters) built for elite performance in coding and agentic tasks, all while maintaining powerful general intelligence.
- MiniMaxMiniMax M2.1MiniMax 2.1 is MiniMax's latest model, optimized specifically for robustness in coding, tool use, instruction following, and long-horizon planning.
- MiniMaxMiniMax M2.1 LightningMiniMax-M2.1-lightning is a faster version of MiniMax-M2.1, offering the same performance but with significantly higher throughput (output speed ~100 TPS, MiniMax-M2 output speed ~60 TPS).
- MiniMaxMiniMax M2.5MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. It is capable of handling the entire development process of various complex systems. It covers full-stack projects across multiple platforms including Web, Android, iOS, Windows, and Mac, encompassing server-side APIs, functional logic, and databases.
- MiniMaxMiniMax M2.5 High SpeedM2.5 highspeed: Same performance, faster and more agile (output speed approximately 100 tps)
- MiniMaxMiniMax M2.7M2.7 delivers outstanding performance in real-world software engineering, including end-to-end full project delivery, log analysis and bug troubleshooting, code security, machine learning, and more.
- MiniMaxMiniMax M2.7 High SpeedM2.7 Highspeed: Same performance, faster and more agile (output speed approximately 100 tps)
- MiniMaxMiniMax M3MiniMax-M3 is a frontier-class foundation model that unites the three capabilities defining today's frontier: a 1M-token context window, frontier coding and agentic performance, and native multimodality — the first open-weight model to deliver all three in a single system.
- MistralMinistral 14BMinistral 3 14B is the largest model in the Ministral 3 family, offering state-of-the-art capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart. Optimized for local deployment, it delivers high performance across diverse hardware, including local setups.
- MistralMinistral 3BA compact, efficient model for on-device tasks like smart assistants and local analytics, offering low-latency performance.
- MistralMinistral 8BA more powerful model with faster, memory-efficient inference, ideal for complex workflows and demanding edge applications.
- MistralMistral CodestralMistral's cutting-edge language model for coding released end of July 2025, Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correction and test generation.
- MistralMistral EmbedGeneral-purpose text embedding model for semantic search, similarity, clustering, and RAG workflows.
- MistralMistral Large 3Mistral Large 3 2512 is Mistral’s most capable model to date. It has a sparse mixture-of-experts architecture with 41B active parameters (675B total).
- MistralMistral Large 4Mistral Large 4 is Mistral AI's open-weight, natively multimodal model, available in public preview with 1.05 trillion total parameters and 49 billion active parameters. It leads aggregated benchmarks among open-weight models from the US and Europe, with strengths in cyber defense, manufacturing, finance, and visual grounding.
- MistralMistral Medium LatestMistral's frontier-class multimodal model optimized for agentic and coding use cases.
- MistralMistral Nemo 12B12B model trained jointly by Mistral AI and NVIDIA, it significantly outperforms existing models smaller or similar in size.
- MistralMistral SmallMistral Small currently runs Mistral Small 4, a multimodal model combining instruction following, reasoning, and coding with a 262,144-token context window.
- MorphMorph V3 FastMorph offers a specialized AI model that applies code changes suggested by frontier models (like Claude or GPT-4o) to your existing code files FAST - 4500+ tokens/second. It acts as the final step in the AI coding workflow. Supports 16k input tokens and 16k output tokens.
- MorphMorph V3 LargeMorph offers a specialized AI model that applies code changes suggested by frontier models (like Claude or GPT-4o) to your existing code files FAST - 2500+ tokens/second. It acts as the final step in the AI coding workflow. Supports 16k input tokens and 16k output tokens.
- MetaMuse Glimmer 30B
- MetaMuse Image 1.0Muse Image is the first image generation model from Meta Superintelligence Labs, it uses advanced reasoning to understand complex prompts, seamlessly blending multiple photos into high-quality creations you can download and share anywhere.
- MetaMuse Spark 1.1Muse Spark 1.1 is strongest at agentic performance, tool use, and computer use. It does well on long-running tasks with 1M token context window, can delegate execution to sub-agents running in parallel, and is trained to use computer interfaces on desktop, mobile, or browser.
- MetaMuse Spark 1.2A coding-optimized model purpose-built for agentic workflows. Improvements to code generation, debugging, and codebase understanding — with a 1M context window that handles your entire project in one session.
- MetaMuse Spark 1.2 ContributorA coding-optimized model with pricing designed for builders. Same model, same capabilities — up to 95% less than Standard. Your inputs and outputs are used to train and improve Meta's AI models.
- MetaMuse Spark 1.3Muse Spark 1.3 is Meta’s multimodal reasoning model for long-horizon agentic and coding workflows. With a 1M-token context window, reliable tool calling, higher first-attempt accuracy, and native understanding of video, images, and documents, it helps developers build capable coding agents and AI development workflows with fewer unnecessary turns and cleaner output.
- MetaMuse Spark 1.3 ContributorMuse Spark 1.3 Contributor is Meta’s cost-optimized API option for agentic coding workflows. It offers a 1M-token context window, dependable tool calling, and multimodal perception at $0.10 per million input tokens and $0.20 per million output tokens, with usage permitted to improve Meta’s products.
- MetaMuse Spark OpenMuse Spark Open is Meta’s open-weight reasoning model for coding and agentic workflows. Its sparse mixture-of-experts architecture has 816 billion total parameters with approximately 42 billion active per token, combining code generation, tool use, and image understanding. A one-million-token context window supports repository analysis, multi-file changes, debugging, and long-running agent tasks.
- MetaMuse WonderMuse Wonder is Meta’s model for frontier coding, long-running agents, and advanced computer use. It plans long tasks, delegates work to sub-agents, and recovers from errors.
- GoogleNano Banana (Gemini 2.5 Flash Image)Nano Banana (Gemini 2.5 Flash Image) is Google's first fully hybrid reasoning model, letting developers turn thinking on or off and set thinking budgets to balance quality, cost, and latency. Upgraded for rapid creative workflows, it can generate interleaved text and images and supports conversational, multi‑turn image editing in natural language. It’s also locale‑aware, enabling culturally and linguistically appropriate image generation for audiences worldwide.
- GoogleNano Banana Pro (Gemini 3 Pro Image)Nano Banana Pro (Gemini 3 Pro Image) builds on Nano Banana's generation capabilities into a new era of studio-quality, functional design to help you create and edit high-fidelity, production-ready visuals with unparalleled precision and control. Improvements include enhanced world knowledge and reasoning, dynamic text and translation, and studio level controls.
- NVIDIANemotron 3 Nano 30B A3BNVIDIA Nemotron 3 Nano is an open reasoning model optimized for fast, cost-efficient inference. Built with a hybrid MoE and Mamba architecture and trained on NVIDIA-curated synthetic reasoning data, it delivers strong multi-step reasoning with stable latency and predictable performance for agentic and production workloads.
- NVIDIANemotron 3 UltraA 550B parameter (55B active) open reasoning model from NVIDIA, built for long-running agent workflows. It uses a hybrid Mamba-Transformer MoE architecture and supports a 1M token context window.
- NVIDIANemotron 3.5 Lightning 30BNVIDIA-Nemotron-3.5-Lightning-30B-A3B-NVFP4 is a large language model (LLM) trained by NVIDIA. The model employs a hybrid Mixture-of-Experts architecture, utilizing interleaved Mamba-2 and MoE layers, along with select Attention layers. The Lightning 3.5 model is released alongside a number of speculative decoding methods for faster text generation. The model has 3B active parameters and 30B parameters in total.
- NVIDIANemotron 3.5 Lightning FreeNemotron 3.5 Lightning is an open-weight reasoning and chat model for long-running agents, sub-agent work, chatbots, and RAG systems. The model has 30B parameters with 3B active per token, in a hybrid Mixture-of-Experts design that interleaves Mamba-2 and MoE layers with a few attention layers. It has a 1M token context window and supports tool calling and structured outputs. The provider may retain prompts and responses for model improvement.
- 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 using Parallel AI's Search API for LLM-optimized excerpts. Takes a natural language objective and returns relevant excerpts, replacing multiple keyword searches with a single call for broad or complex queries.
- 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