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Use Vercel's AI Gateway model page to test Inkling as thinkingmachines/inkling without adding another provider integration. Inkling is Thinking Machines' open-weights multimodal MoE model, with text, image and audio inputs, controllable thinking effort, and long-context support. Treat it as an evaluation target for multimodal agent workflows, not as an automatic replacement for stronger closed frontier models. Vercel has added Thinking Machines' Inkling to AI Gateway under thinkingmachines/inkling, so teams already using AI Gateway can test it through the same playground, routing, budget, retry and usage-tracking layer they use for other models. Inkling is an open-weights multimodal MoE model from Thinking Machines with text, image and audio inputs, controllable thinking effort and long-context support. Use it for practical evaluation of multimodal agent workflows, document/audio reasoning and fine-tuning paths; compare latency, cost and output quality before moving production traffic.
Vercel AI Gateway now exposes ByteDance Seedream 5.0 Pro as bytedance/seedream-5.0-pro, giving teams a routed API path for production image generation and editing workflows. Vercel added ByteDance Seedream 5.0 Pro to AI Gateway on July 11, 2026. Use it when you want one API layer for image generation, usage tracking, budgets, routing rules, retries, and BYOK behavior instead of wiring a separate image provider directly into every app. The practical draw is not just another model listing. ByteDance positions Seedream 5.0 Pro for production image work: layer-separated outputs, precise local edits, coordinate and hex color control, multilingual text rendering, infographics, product visuals, and marketing assets. Through Vercel's AI SDK, the model id is bytedance/seedream-5.0-pro. Why bookmark it Vercel gives app teams a standard gateway route for Seedream 5.0 Pro instead of a one-off provider integration. Seedream 5.0 Pro is aimed at editable commercial assets, not only flat prompt-to-image output. ByteDance says the model supports layer separation, targeted editing, 14-language text generation, and design-oriented controls. Vercel says AI Gateway can track usage and cost, apply budgets, configure routing rules, support Zero Data Retention, and use provider pricing with no platform markup. Quick checks before shipping Confirm your Vercel project can access AI Gateway and the model playground. Test text rendering, brand colors, localization, and image edits with real campaign assets. Compare Vercel Gateway pricing and retention settings with direct ByteDance/Lumina access. Check whether your workflow needs layered export features that may only exist in specific ByteDance/Lumina surfaces. Keep generated commercial assets in human review until rights, brand, and regional requirements are clear.
Vercel AI Gateway can now rank providers by cost, time to first token, or throughput before fallback, so agent apps can optimize routing without hard-coding provider order. Vercel added provider sorting to AI Gateway. Set providerOptions.gateway.sort to cost, ttft, or tps and the gateway ranks available providers behind a model by the selected metric before it falls back to the next provider. Use it when a model has multiple providers and your workflow has a clear priority: lowest listed input cost for batch jobs, lower time to first token for interactive chat, or higher tokens per second for long outputs. The routing metadata can show which providers were considered, attempted, deprioritized, or selected. This is useful, but it is not a magic optimizer. Provider sorting works best after you define the workload, check data-retention constraints such as ZDR, and verify model/provider behavior with your own prompts and token mix.
Cloudflare added Moondream 3.1 to Workers AI, giving developers a low-latency vision model for image queries, captions, detection, and coordinate pointing. Cloudflare has added Moondream 3.1 to Workers AI as @cf/moondream/moondream3.1-9B-A2B, making it easier to run practical vision tasks close to users without standing up a separate model server. What it is Moondream 3.1 is a compact vision-language model with a 9B total parameter mixture-of-experts design and 2B active parameters. Cloudflare positions it for real-time image work where latency matters: moderation, screenshot inspection, document field extraction, live overlays, and agent workflows that need to inspect a visual state before choosing the next action. Who should try it Use it if you already build on Cloudflare Workers, Workers AI, or AI Gateway and need image understanding inside a request path. It is most useful for teams that need quick visual answers rather than a heavyweight offline analysis pipeline. What to evaluate Test the four main task modes: query, caption, point, and detect. Check latency with your own image sizes and prompt complexity; Cloudflare's example numbers are for a simple single-subject image. Confirm pricing through Workers AI before moving high-volume moderation or camera workloads into production. Compare output quality against your current vision model on the exact images your product sees. Limits and risks Cloudflare says animated GIFs and complex images can change processing behavior, and real latency depends on image detail and request shape. Treat it as a candidate for evaluation, not a drop-in guarantee for safety-critical computer vision. Sources Cloudflare changelog: https://developers.cloudflare.com/changelog/ Moondream: https://moondream.ai/
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