MODEL DIRECTORY

MODEL DIRECTORY

Grok

Grok

xAI’s Grok 4.5 is positioned for reasoning, coding, agentic tool use, and current-information workflows, with supported web, X, and code-execution tools.

CURRENT MODEL SNAPSHOT

Provider: xAI
Current anchor: Grok 4.5
Lifecycle: Current
Weights: Closed
Reviewed: 20 July 2026

Grok 4.5 in context

Grok is xAI’s model and product family. Grok 4.5 is the current enterprise-relevant anchor in xAI’s developer documentation, with configurable reasoning effort, a documented 500,000-token context window, and supported tools for web search, X search, and code execution. These tools make Grok interesting for current-information agents, but they also expand the security and evidence boundary.

The practical Grok evaluation currently centers on:

  • Grok 4.5 for advanced reasoning, coding, and agentic tasks.

  • Configurable reasoning levels that trade latency and compute for deeper analysis.

  • Supported web-search and X-search tools for current public information.

  • Code-execution and function-tool patterns for workflows that must calculate or act.

Evaluate the base model separately from each enabled tool. A strong answer produced with web or X search is a retrieval-system outcome, not only a model outcome, and the sources, permissions, and failure modes must be reviewed accordingly.

Where Grok is distinctive

Grok’s distinctive angle is the combination of reasoning with xAI-managed access to the current web and X ecosystem. That may be useful for monitoring, research, and rapidly changing topics. Enterprise suitability depends on regional availability, source policy, data controls, and the organization’s tolerance for external retrieval.

Strengths to test

  • Current-information research that benefits from web and X search alongside reasoning.

  • Coding and agentic tasks using supported functions or code execution.

  • Long-context analysis where the 500,000-token limit is tested against real evidence sets.

  • Workflows that can tune reasoning effort for different quality and latency requirements.

Trade-offs and failure modes

  • Search tools can retrieve low-quality, adversarial, personal, or legally sensitive material.

  • X content is fast-moving and may contain unverified claims, coordinated manipulation, or missing context.

  • Code execution and tools create authorization, sandboxing, and incident-response requirements.

  • Regional availability and feature rollout can differ; confirm the production endpoint before committing.

Test reasoning levels and tools as distinct configurations. Measure source quality, citation support, tool-call accuracy, sandbox escapes, long-context retrieval, latency, and cost. Include misinformation, deleted sources, contradictory posts, prompt injection, and questions that should trigger uncertainty or human escalation.

Deployment and enterprise decision notes

Use xAI’s API and documented model gateways where available. Confirm regional service availability, model and tool access, data controls, retention, quotas, and contractual terms. xAI’s documentation indicated EU API availability was expected later in July 2026, so verify the current status rather than relying on a roadmap statement.

Best fit

A strong candidate for tool-enabled research, monitoring, coding, and agentic workflows that benefit from current web or X information. It is most appropriate when sources and actions are bounded, observable, and independently checked.

Not the best fit

Avoid Grok when web or X retrieval is prohibited, required regional availability is unconfirmed, or the organization cannot control tool permissions and validate sources. It is also a poor fit for high-impact decisions without a robust evidence and review layer.

Data and governance

Record reasoning level, enabled tools, search scope, region, retention, source-validation rules, execution sandbox, and human approval points. Treat external posts as untrusted input, protect tools from retrieved instructions, and define what evidence is required before a model conclusion becomes an action.

Official sources

Beam AI support status

Under evaluation. This page is a model-selection reference, not confirmation of a Beam integration, benchmark result, data-residency promise, or production recommendation. Validate the exact provider surface and model version in the intended workflow before release.

Use case 1

Current-event monitoring

Track a defined market, company, or operational topic using web and X search, then produce a source-linked change summary. Apply source-quality rules, timestamp evidence, detect coordinated repetition, and keep high-impact conclusions behind analyst review.

Use case 2

Tool-enabled coding agent

Reason about a bounded software task, call approved repository or execution tools, and return tested changes. Restrict credentials and network access, isolate code execution, review dependencies, and evaluate successful task completion under the chosen reasoning level.

Use case 3

Public-signal risk triage

Surface emerging public signals for a risk owner without treating social posts as verified facts. Separate observation from inference, preserve links and dates, protect against malicious content, and require corroboration from authoritative sources before escalation.

Use case 4

Long-context investigative brief

Analyze a large supplied evidence set with the documented long context while testing missed facts, contradictions, and source traceability. Compare against retrieval-based approaches and require explicit uncertainty when the record does not support a conclusion.

Related LLMs

Curated alternatives to compare before selecting a model family.

ChatGPT

ChatGPT is OpenAI’s conversational product; enterprise automations use the underlying GPT models and APIs. This guide separates the product from the model family and explains how to evaluate the current GPT-5.6 lineup.

ChatGPT

Combine sections from a range of categories to easily assemble pages that meet the needs of your growing business.

DeepSeek

DeepSeek’s current V4 family provides Pro and Flash API models with thinking and non-thinking modes, a documented one-million-token context window, and compatible API interfaces.

DeepSeek

Combine sections from a range of categories to easily assemble pages that meet the needs of your growing business.

Perplexity

Perplexity’s Sonar API family combines language models with web search and citations. The core enterprise decision is whether provider-managed retrieval and source handling fit the workflow.

Perplexity

Combine sections from a range of categories to easily assemble pages that meet the needs of your growing business.

Gemini

Google’s Gemini family covers production and preview models for multimodal, reasoning, audio, media, and tool-oriented workloads. Model stage and endpoint stability are central to an enterprise selection.

Gemini

Combine sections from a range of categories to easily assemble pages that meet the needs of your growing business.

Claude

Anthropic’s Claude family spans frontier reasoning, coding, vision, and faster production models. The practical choice is a specific pinned model ID on the Claude API or a supported cloud platform.

Claude

Combine sections from a range of categories to easily assemble pages that meet the needs of your growing business.

Llama

Meta’s Llama 4 family provides open-weight, natively multimodal models. Scout emphasizes very long context and efficient deployment; Maverick targets stronger general multimodal capability.

Llama

Combine sections from a range of categories to easily assemble pages that meet the needs of your growing business.

Start Today

Build AI agents with the right model

See how Beam can orchestrate governed AI workflows across the model family that fits your requirements.

Start Today

Build AI agents with the right model

See how Beam can orchestrate governed AI workflows across the model family that fits your requirements.

Start Today

Build AI agents with the right model

See how Beam can orchestrate governed AI workflows across the model family that fits your requirements.

FAQs

Frequently Asked Questions

Model selection, deployment, governance, and Beam support questions answered.

What is the current Grok model lineup?

xAI’s developer documentation currently anchors Grok on version 4.5 with configurable reasoning, a 500,000-token context window, and supported search and code tools. Model names and lifecycle labels can change quickly, so record the exact model ID or release used in testing and confirm it against the linked provider documentation before production.

How can an enterprise access or deploy Grok?

Enterprises access Grok through xAI’s API and documented gateways, subject to current regional, model, and tool availability. Availability, regional controls, service terms, and feature parity can vary by route. Evaluate the exact provider surface that will carry production traffic, rather than assuming every hosted or self-managed option behaves identically.

What workloads are a strong fit for Grok?

Grok is a strong candidate for current-information research, monitoring, coding, and tool-enabled agents that can validate sources and actions. Treat that as a shortlist hypothesis, not a universal ranking. Use representative prompts, tools, documents, languages, and failure cases to compare quality, latency, reliability, and total operating cost.

What should security and governance teams review for Grok?

Review region, retention, web and X source policy, prompt injection, tool permissions, code sandboxing, reasoning cost, and evidence requirements. Document the data path, retention settings, model version, region, subprocessors or hosting stack, human-review points, and incident fallback before the workflow is approved.

Does this page confirm Beam support for Grok?

No. Beam support is marked Under evaluation because no approved integration or production-support evidence is attached to this CMS record. The page can guide discovery and evaluation, but the implementation owner must verify access, controls, tool behaviour, and operational fit before making a customer commitment.