Best Multimodal Models for Vercel AI Gateway - Page 2

Find and compare the best Multimodal Models for Vercel AI Gateway in 2026

Use the comparison tool below to compare the top Multimodal Models for Vercel AI Gateway on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

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    MiMo-V2.6-Pro-UltraSpeed Reviews

    MiMo-V2.6-Pro-UltraSpeed

    Xiaomi Technology

    $4.35 per 1 million tokens inp
    MiMo-V2.6-Pro-UltraSpeed is Xiaomi MiMo’s accelerated serving option for MiMo-V2.6-Pro, built for applications that require very high output speed without changing the underlying model quality. Xiaomi states that UltraSpeed can generate output at up to 20 times the speed of the standard MiMo-V2.6-Pro configuration. The model retains MiMo-V2.6-Pro’s natively omnimodal capabilities across coding, agentic workflows, visual reasoning, computer use, and research. Developers can use it for long-horizon software engineering, automation, debugging, tool-driven tasks, and other workloads that benefit from rapid model responses. Its multimodal abilities also support frontend generation, presentation creation, 3D modeling, interactive environments, and visual feedback loops. The broader MiMo-V2.6 architecture combines coding capabilities with 3D spatial reasoning, multimodal perception, and computer-use agent functionality. Xiaomi positions UltraSpeed for real-time interaction and other workflows where response latency is especially important. The accelerated model is offered through MiMo Desktop and can also be called through the Xiaomi MiMo API Platform. MiMo-V2.6-Pro-UltraSpeed is intended for developers and organizations that prioritize maximum generation speed while retaining the capabilities of Xiaomi’s higher-end MiMo-V2.6-Pro model.
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    Qwen3.7-Plus Reviews
    Qwen3.7-Plus is an advanced multimodal agent model that seamlessly integrates vision and language into a single, adaptable foundation for intelligent agents. Expanding upon the agentic intelligence of Qwen3.7, it enhances its abilities to include visual comprehension, reasoning, grounded interactions, and the use of various multimodal tools, allowing agents to perceive, analyze, and operate within text, images, documents, screens, and intricate real-world scenarios. This model is specifically crafted for dynamic tasks that go beyond mere static question answering, facilitating activities such as visual searches, document understanding, chart and table evaluations, screen comprehension, GUI interactions, image-driven reasoning, and workflows where perception, planning, and action are interlinked. Qwen3.7-Plus fortifies the relationship between linguistic reasoning and visual cues, empowering users to inquire about images, decode complex multimodal information, extract organized data, and formulate responses that incorporate both contextual and visual elements, thus broadening the scope of interactive AI applications. With these enhancements, users can engage in more sophisticated and nuanced interactions with the system, making it a powerful tool for various practical applications.
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    Gemini 3.8 Flash Cyber Reviews
    Gemini 3.8 Flash Cyber represents Google's most advanced cybersecurity model, offering top-tier performance in identifying vulnerabilities and automating patching processes with remarkable speed for rapid iteration. Tailored for trusted defenders, it is accessible via the Fairwind Program. On CyberGym, a recognized industry benchmark for detecting vulnerabilities, this model showcases exceptional autonomous vulnerability discovery, outperforming both Gemini 3.5 Flash Cyber and larger frontier models. Furthermore, Google assessed its effectiveness on an internal benchmark that spans complex codebases across 20 programming languages, achieving a success rate of over 70% in identifying various vulnerabilities. Unlike many models that focus on offensive strategies, Gemini 3.8 Flash Cyber emphasizes the importance of fixing vulnerabilities, providing defenders with advanced tools that enhance their ability to stay ahead of cyber attackers. This focus on proactive defense represents a crucial shift in the cybersecurity landscape, prioritizing the safeguarding of systems over mere exploitation capabilities.
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    Claude Fable 5.5 Reviews
    Claude Fable 5.5 is an anticipated but currently unannounced model in Anthropic's Claude family, and Anthropic has not confirmed that a model with this name will be released. As of September 30, 2026, Claude Fable 5.1 remains the latest officially documented Fable model. Fable represents Anthropic's highest-end model tier for demanding reasoning and long-horizon agentic work, while the newer Opus 5.5 and Sonnet 5.5 occupy lower-cost positions in the Claude lineup. Anthropic's current documentation gives Fable 5.1 a 1-million-token context window and maximum output length of 128,000 tokens. It supports text and image inputs with text output and uses adaptive thinking that remains active throughout model operation. Fable 5.1 defaults to high reasoning effort and is listed as having a June 2026 reliable knowledge cutoff and training-data cutoff. API pricing is $10 per million input tokens and $50 per million output tokens, while prompt-cache reads cost $0.25 per million tokens and Batch API processing receives a 50% input and output discount. Anthropic's official documentation currently provides model identifiers for Fable 5.1 across the Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry, and Claude Platform on AWS. No equivalent model identifier, specifications, benchmark results, pricing, availability information, or release schedule has been published for Claude Fable 5.5.
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    OpenAI Bel Reviews
    OpenAI Bel is an unconfirmed artificial intelligence model reportedly associated with OpenAI's research into large-scale foundation models. The name has appeared in unofficial discussions describing a possible new generation of pretrained AI systems. Reports suggest that Bel may represent a successor to an earlier internal training effort referred to as Doug. Some accounts describe the project as a potential foundation for future models related to the Astra family and later GPT generations. Unverified claims place its parameter count above 10 trillion, although OpenAI has not disclosed any supporting architectural information. The model's training methodology, supported modalities, context window, and inference capabilities remain unknown. No official benchmark evaluations have established its performance in reasoning, coding, mathematics, or other AI tasks. OpenAI has not announced public access, API availability, pricing, or a release schedule for a model named Bel. The available information therefore characterizes Bel as a rumored research project rather than an established commercial AI product.