xAI opens Grok 4.6 on its API with 500K context

xAI's developer release notes now list Grok 4.6 as available through the xAI API. The model accepts text and image input, offers a 500K-token context window, and supports low, medium, high, and xhigh reasoning effort. That makes this an API availability change for developers, separate from Grok 4.6's earlier arrival in GitHub Copilot.

Grok 4.6 targets long-context coding and knowledge work

xAI describes Grok 4.6 as a frontier model for coding, agentic tasks, and knowledge work. The API entry lists text-only output, a 500K context window, and no text output limit. Developers can choose the reasoning effort instead of accepting one fixed mode: low, medium, high, or xhigh, with high as the default.

The practical difference is workload shape. A large repository, a long technical brief, or a multi-step agent run can keep more context in one request. The larger window does not remove the need to manage prompt size, latency, and output budgets; it changes the ceiling available to those workflows.

Pricing doubles above 200K prompt tokens

xAI lists two price bands. Below 200K prompt tokens, the rate is $2 per million input tokens, $0.50 per million cached input tokens, and $6 per million output tokens. Above that threshold, the rates are $4, $1, and $12 respectively.

That cutoff matters for long-running agents. A request that crosses 200K prompt tokens does not merely consume more tokens; it moves into a higher unit-price band. Teams should log prompt-token counts and cached-input behavior before comparing Grok 4.6 with shorter-context alternatives.

Artificial Analysis independently lists the same $2/$6 input-output pricing for the lower band and measures a 500K context window. Its evaluation places Grok 4.6 among the stronger current models while also reporting slower-than-average throughput, so cost and latency need to be evaluated together.

What API users should check first

The release-notes entry establishes availability on the xAI API. Before switching production traffic, verify the exact model identifier, regional or account access, current rate limits, and whether the selected reasoning effort changes latency or output cost in your account. Test a representative prompt set rather than relying on a single benchmark score.

For agent builders, the useful baseline is a three-way comparison: a normal request below 200K prompt tokens, a cached-input repeat, and a long-context request above the threshold. Record time to first token, total latency, output length, and the actual billed input tier.

If you are wiring the model into a broader agent workflow, LinkLoot's AI agent tools guide is a useful checklist for comparing providers, tool access, and operational limits.

Evidence

xAI's Developer Release Notes list Grok 4.6's API availability, context size, inputs, reasoning levels, and price bands. Artificial Analysis provides independent model measurements and pricing context. Neither source establishes universal access for every xAI account, so account-level availability and limits remain worth checking before deployment.