How to Install / Upgrade: Grok 4.6 now available on AI Gateway

What happened

Grok 4.6 from xAI is now available through Vercel's AI Gateway. If you are already using AI Gateway to route model calls in your application, adding Grok 4.6 to your stack requires only a small configuration change, no new accounts, no separate API keys to manage, and no infrastructure to stand up yourself.

This guide covers what the model brings to the table, how its reasoning system works, and the exact steps you need to install or upgrade whether you are starting from scratch or migrating an existing integration. Everything here comes directly from the Vercel Blog announcement, so there are no speculative version numbers or inferred figures to worry about.

What shipped

Grok 4.6 is xAI's latest model, and it is now routable through AI Gateway alongside the other models the gateway already supports. The model accepts two input types: text and images. That combination puts it in a multimodal tier, meaning you can send it a screenshot, a diagram, or a photo alongside a text prompt and have it reason across both at once.

The context window is 500,000 tokens. That is a large window by current standards and it matters practically: it means you can pass in long documents, extended conversation histories, large code files, or a combination of all three without hitting a truncation wall mid-task. For retrieval-augmented generation workflows, a window this size can reduce or eliminate chunking strategies that add latency and complexity.

How it works

Grok 4.6 supports four reasoning levels: low, medium, high, and xhigh. The model defaults to high. The reasoning level setting lets you trade off compute cost and response time against the depth of analysis the model applies before answering. Low is faster and cheaper. xhigh is slower and more thorough. High sits in the middle and is what you get if you do not specify anything.

What changed for builders

The change is additive. AI Gateway already handles authentication, routing, observability, and rate limiting for other models you may be using. Grok 4.6 plugs into that same system, so you do not need a separate xAI account or a new billing relationship if you are already on Vercel. Your existing logging, fallback configuration, and cost tracking in the gateway dashboard apply to Grok 4.6 calls the same way they apply to other routed models.

The AI SDK is the integration layer. The model identifier you pass to the SDK is what determines which model gets called. Switching from one model to another in the SDK is a one-line change in most setups. That means you can run Grok 4.6 alongside your existing models and test it in isolation before committing to it for any given feature.

Why it matters

The reasoning level is a parameter you set at call time, not at account or project configuration time. That gives you per-request control, which is useful if different parts of your application have different latency tolerances or cost budgets.

How to install or upgrade

Start by making sure you have the Vercel AI SDK installed in your project. If you do not, install it using your package manager of choice. The SDK is available through npm. Run the install command for the AI SDK package before doing anything else.

Once the SDK is in place, import the xAI provider from the SDK. The provider is what gives the SDK the ability to talk to xAI models through AI Gateway. You do not need to configure the AI Gateway endpoint separately in your code because the SDK and gateway handle that routing layer for you when your project is deployed on Vercel.

To call Grok 4.6, set the model parameter to xai/grok-4.6. That string is the identifier AI Gateway uses to route your request to the correct model. If you want to override the default reasoning level, pass the reasoning level parameter in your call options. The four accepted values are low, medium, high, and xhigh. If you omit the parameter entirely, the model uses high reasoning by default.

Who is affected

To send an image alongside text, structure your message content as an array containing both a text part and an image part. The image can be a URL pointing to a publicly accessible image or a base64-encoded data URI. The model processes both together when forming its response.

If you are upgrading from a different model, find the line in your code where you specify the model identifier, change it to xai/grok-4.6, and redeploy. No other changes are required for a basic swap.

Gotchas and compatibility

The default reasoning level is high, not low or medium. If you are migrating from a model that did not have a reasoning parameter, your first calls with Grok 4.6 may be slower than you expect because the model is doing more work before responding. If response time is critical for your use case, set reasoning level to low or medium explicitly and measure the tradeoff.

What to watch next

The 500,000 token context window is large, but larger inputs cost more to process. Keep an eye on your gateway usage dashboard after switching, especially if your prompts routinely include long documents or conversation history.

Image inputs require the input to be either a URL or a base64 data URI. Passing a local file path will not work in a deployed environment.

What to watch next

xAI is an active model provider and Vercel tends to add new model versions to AI Gateway shortly after they are released. Watch the Vercel Blog and the AI Gateway documentation for new model identifiers as they become available. The reasoning level parameter is relatively new as a developer-facing control across the industry, so it is worth tracking how xAI evolves those tiers in future releases.