Grok on Mac: Grok Bot Desktop App, Grok Build or API?

Grok 4.5 is a cloud model for coding, agents and professional knowledge work. The native xAI API model name is grok-4.5; the OpenRouter slug is x-ai/grok-4.5. For Mac users, the most important limitation is clear: Grok 4.5 does not run locally on Apple Silicon. The Mac is the client; inference happens in the cloud.

Current model status (August 14, 2026): Direct xAI API access is available to EU users. Standard pricing below 200K prompt tokens is $2.00 input, $0.30 cached input and $6.00 output per million tokens. Requests at or above 200K prompt tokens use higher long-context rates.

That separates Grok 4.5 from Ollama, LM Studio and MLX models. It is most useful when cloud processing is acceptable and long context, strong coding performance or agent workflows matter more than full local control.

Grok on Mac: which app are you looking for?

The phrase “Grok for Mac” now covers three different access paths. They are related, but they are not the same product:

If you want …	Use …	Where the model runs
A desktop teammate that works across apps	Grok Bot	In a cloud computer
Terminal-first coding and repository work	Grok Build	Cloud model, local terminal client
Your own integration or API client	Grok 4.5 through the xAI API	xAI infrastructure

Grok Bot desktop app for macOS

xAI launched Grok Bot in beta on August 11, 2026. The announcement says that eligible SuperGrok Heavy, Cursor Ultra and Cursor Teams Premium subscribers can use it on desktop and iOS. Grok Bot has its own cloud computer, works across apps and websites, and requires cloud data storage; it is therefore not local inference on the Mac.

The official setup guide provides separate Apple-silicon and Intel downloads. On macOS, choose the matching download, open the disk image, drag Grok Bot to Applications and sign in with a Cursor account. Linux is not currently listed as a desktop target.

Grok Build for terminal coding

Grok Build is a separate terminal coding agent. The Grok 4.5 launch post described 4.5 as the default model in Grok Build at that time; the current xAI Build page now names Grok 4.6 and shows the one-command installer. Choose Grok Build for terminal-based repository work; Grok Bot is the desktop option for working across apps.

Grok 4.5 API

The API remains the direct integration path: the model ID is grok-4.5, the Mac runs the client, and xAI runs inference. If your priority is offline work or private files, compare this cloud path with the open-weight LLM guide and the Mac mini local-AI RAM guide.

What is Grok 4.5?

Grok 4.5 is a frontier model from xAI. Current official pages sometimes use the name SpaceXAI, while the developer documentation and API still live under x.ai. The launch post positions Grok 4.5 for coding, agentic tasks and knowledge work: bug fixing, refactoring, terminal work, large repositories, multi-step workflows and office tasks.

For Mac users, the category is straightforward: Grok 4.5 is a strong cloud model for Mac workflows, not a local Mac model. Users searching for “Grok 4.5 Mac”, “Grok 4.5 local”, “Grok Ollama” or “install Grok on MacBook” can use the model on a Mac, but they cannot download it and run it offline. Access goes through the xAI API, Grok Build, Cursor, OpenRouter or other model gateways.

Official model name vs. OpenRouter slug

Name	Meaning
grok-4.5	official xAI/API model name
x-ai/grok-4.5	OpenRouter model slug
grok-4.5 with an OpenAI-compatible client	direct xAI usage via base_url="https://api.x.ai/v1"

With direct xAI usage, the model is grok-4.5. On OpenRouter, it is x-ai/grok-4.5. The names refer to the same model access from different ecosystems, but they are not interchangeable: x-ai/grok-4.5 is a router/provider identifier, not the native xAI model name.

Key facts for Grok 4.5

Property	Grok 4.5
Provider	xAI / currently described as SpaceXAI on some launch pages
Official model name	grok-4.5
OpenRouter slug	x-ai/grok-4.5
Release date	July 8, 2026
Model type	cloud/API model
Main focus	coding, agents, knowledge work, STEM, office
Context window	500K tokens
xAI input price	$2.00 / 1M tokens
xAI cached input	$0.30 / 1M tokens below 200K prompt tokens
xAI output price	$6.00 / 1M tokens
Long-context pricing	2× standard rates from 200K prompt tokens
Reasoning	low, medium, high; default high
Tools	function calling, web search, X search, code execution
Local Mac use	No
Ollama / LM Studio / MLX	No
Open weights	No
EU availability	available in the xAI API console

EU update: xAI’s release notes now confirm Grok 4.5 availability in the API console for EU users. The earlier launch restriction no longer applies.

Does Grok 4.5 run locally on Mac?

No. Grok 4.5 is not an open-weight model. There are no official weights to download, no GGUF release, no MLX build and no Ollama tag. If Grok 4.5 is used, inference runs on xAI infrastructure or through a model gateway.

Question	Answer
Can I run ollama run grok-4.5?	No
Is Grok 4.5 available for LM Studio?	No
Is there an MLX version?	No
Does it work offline?	No
Can I use it on a Mac?	Yes, through API, Grok Build, Cursor or OpenRouter
Is it ideal for private offline files?	No, use local models for that

In practice, this leads to a hybrid workflow: local models for private files and offline work, Grok 4.5 for tasks where cloud processing is acceptable and model quality matters more than full local control.

Why Grok 4.5 still matters for Mac users

A Mac does not accelerate Grok 4.5 directly. M1, M2, M3 and M4 chips do not run the model inference. Still, many AI workflows begin on macOS:

• terminal coding
• Cursor, VS Code, Zed and other editors
• repository analysis
• bug fixing and refactoring
• web app prototyping
• technical documentation
• spreadsheets, presentations and office files
• web and X-based research
• code execution for small tests and calculations
• tool-based agent loops

The Mac is not the machine running Grok 4.5. It is the working environment for the cloud model.

Benchmarks: useful, but not a world ranking

xAI published several benchmark comparisons in the launch post. The numbers matter, but they are not fully independent and not always directly comparable. Some values come from different harnesses or provider-specific setups. They show a performance range, not a neutral leaderboard.

Graphic: original SVG summary based on the official benchmark chart in the xAI/SpaceXAI Grok 4.5 launch post. Source: x.ai/news/grok-4-5.

Selected launch benchmarks

Benchmark	Grok 4.5	Comparison values shown by xAI	Context
DeepSWE 1.0	62.0%	Fable max 66.1%, GPT 5.5 xhigh 64.31%, Opus 4.8 max 55.75%	within each model provider’s harness
DeepSWE 1.1	53.0%	Fable max 70%, GPT 5.5 xhigh 67%, Opus 4.8 max 59%, GLM 5.2 44%	DataCurve mini-swe-agent harness
Terminal-Bench 2.1	83.3%	Fable max 84.3%, GPT 5.5 xhigh 83.4%, Opus 4.8 max 78.9%	very close top cluster
SWE Bench Pro	64.7%	Fable max 80.4%, Opus 4.8 max 69.2%, GLM 5.2 62.1%, GPT 5.5 xhigh 58.6%	resolve rate; setup matters

Based on these launch numbers, Grok 4.5 is strong for terminal, coding and agent workflows. It is not the top model in every benchmark shown. SWE Bench Pro in particular shows that other frontier models can be ahead depending on the setup. The values are most useful when read together with the source, harness and context.

Token efficiency: more important than one score

xAI emphasizes token efficiency as much as benchmark scores. According to the launch post, Grok 4.5 resolves SWE Bench Pro tasks with an average of 15,954 output tokens. For Opus 4.8 max, xAI shows 67,020 output tokens. xAI describes this as about 4.2 times fewer output tokens.

Graphic: original SVG summary based on the official token efficiency chart in the xAI/SpaceXAI launch post. Source: x.ai/news/grok-4-5.

With cloud models, benchmark scores are only part of the cost picture. Token volume and tool calls also matter. A model that solves a task with fewer intermediate steps, shorter intermediate messages and less output can be faster and cheaper in practice, even if the raw per-token price is not the lowest.

This matters especially for agents. A coding-agent run can plan, read files, call tools, edit code, run tests, analyze failures and patch again. Less output reduces both cost and waiting time.

Speed: 80 tokens per second in the API

xAI reports 80 tokens per second serving speed for Grok 4.5. That is a useful reference point, but not a guarantee for every account, region and prompt. Real-world latency and throughput depend on region, load, routing, tool calls, reasoning level, context size and platform. For Mac users, Grok 4.5 speed depends on the API path and workload, not on the local M-series chip.

Pricing: competitive, but tool use matters

xAI uses two price tiers for Grok 4.5. Once a prompt reaches 200K tokens, the long-context rate applies to all tokens in that request:

Token type	Below 200K prompt	200K–500K prompt
Input	$2.00 / 1M tokens	$4.00 / 1M tokens
Cached input	$0.30 / 1M tokens	$0.60 / 1M tokens
Output	$6.00 / 1M tokens	$12.00 / 1M tokens

The pricing documentation also states that server-side tools can add separate tool invocation costs. Web Search, X Search and Code Execution are listed at $5 per 1,000 calls. That is small for occasional use, but it can matter for autonomous agent runs.

Example cost without tool calls

A longer coding request with 120K input tokens and 8K output tokens costs approximately:

Part	Calculation	Cost
Input	0.12 × $2.00	$0.24
Output	0.008 × $6.00	$0.048
Total	—	about $0.288

Cached input can reduce cost if repeated context is served from cache reliably. xAI recommends prompt_cache_key or the x-grok-conv-id header so that conversation requests are routed to the same server more reliably and cache hits become more likely. The example stays below the 200K threshold; larger prompts cost twice the standard token rates.

Reasoning: low, medium or high

Grok 4.5 supports configurable reasoning. The documentation lists low, medium and high, with high as the default.

Reasoning level	Best for
low	short answers, simple transformations, lower cost
medium	normal coding and analysis work
high	difficult bugs, architecture questions, agents, STEM, planning

Not every request needs high. For short transformations or simple answers, low or medium is often enough. For large codebase work, hard-to-reproduce bugs or complex agent loops, high is more useful.

Tools: more than a chat model

Grok 4.5 supports several server-side capabilities:

• function calling
• web search
• X search
• code execution
• structured outputs
• streaming
• context compaction for long agent loops

These capabilities make the model useful in workflows where it does more than generate text: it can use tools, process results and plan next steps. On Mac, Grok 4.5 is therefore most relevant in Grok Build, Cursor, OpenRouter-compatible clients and custom API workflows.

Current information does not automatically come from the model itself. Without search tools, a model does not have access to new events or external data. Use Web Search or X Search when the task needs current information.

Privacy and API data

For sensitive Mac files, Grok 4.5 is not automatically the right choice. xAI’s security FAQ says API inputs and outputs are not used for training without explicit permission. At the same time, API requests and responses are stored temporarily for 30 days for abuse or misuse auditing. Zero Data Retention is available as an enterprise feature.

Data type	Recommendation
private notes	process locally
confidential client data	use only after compliance review, ideally ZDR
public code examples	Grok 4.5 can be useful
large open-source repos	Grok 4.5 can be useful
internal business docs	check privacy requirements
offline work	use a local model

For private offline data, local Mac models remain the better fit. Grok 4.5 is better suited to cloud agents, public code examples and large repositories where cloud processing is allowed.

Setup: xAI API on Mac

Option 1: xAI Responses API with cURL

export XAI_API_KEY="your_api_key"

curl https://api.x.ai/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $XAI_API_KEY" \
  -d '{
    "model": "grok-4.5",
    "input": "Find and fix the bug, then explain it: function median(a){a.sort();return a[a.length/2]}"
  }'

Option 2: Python with the OpenAI-compatible client

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["XAI_API_KEY"],
    base_url="https://api.x.ai/v1",
)

response = client.responses.create(
    model="grok-4.5",
    input="Explain when I should use a local Mac model and when Grok 4.5 is worth the cloud cost.",
)

print(response.output_text)

Option 3: OpenRouter on Mac

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["OPENROUTER_API_KEY"],
    base_url="https://openrouter.ai/api/v1",
)

response = client.chat.completions.create(
    model="x-ai/grok-4.5",
    messages=[
        {"role": "system", "content": "You are a precise Mac AI workflow assistant."},
        {"role": "user", "content": "Compare Grok 4.5 with a local Qwen model for coding on a Mac."},
    ],
)

print(response.choices[0].message.content)

Grok 4.5 vs local Mac models

Task	Grok 4.5	Local Mac model
private offline notes	weaker fit	better
large codebase analysis	strong	limited by model/RAM
terminal agents	strong	possible, but usually weaker
low recurring cost	depends on usage	good after setup
data control	cloud trade-off	better
500K context	yes	rarely practical locally
no-internet work	no	yes
web/X search tool use	strong	requires your own tool layer

Grok 4.5 does not replace local AI on Mac. It complements it for tasks where local models are too small, too slow or too unreliable.

When is Grok 4.5 worth using?

Grok 4.5 is most useful for:

• large repositories,
• difficult bugs,
• tool-heavy agent runs,
• terminal and coding workflows,
• long context,
• token-efficient agent responses,
• OpenRouter or xAI API workflows,
• Cursor or Grok Build.

It is a weaker fit for:

• private data that must stay offline,
• short everyday questions,
• simple tasks already handled by a local model,
• anyone looking for a model they can download and run locally.

Conclusion: Configurable reasoning and aggressive pricing, no local path

For Mac users, Grok 4.5 is mainly a cloud tool: long context, configurable reasoning, tool support, strong Terminal-Bench numbers and comparatively aggressive API pricing. The important boundary remains: Grok 4.5 is not a local Mac model, and vendor benchmarks do not replace independent rankings.

Local first for private data. Use Grok 4.5 selectively for large, difficult and agentic tasks.