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xAI · Official-source model record

Grok 4.5

Grok · Version grok-4.5

AvailableChecked Oct 23, 2026
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Publisher-sourced inventory. Specifications come from official documentation and model cards. “Not documented” means we have no verified value. This inventory is separate from our editorial reviews.

Coverage & sources ↗

Current catalog answers

What to know about Grok 4.5

AI-compiled from linked model documentation. This is a catalog reference, not an independent performance review. Catalog checked October 23, 2026.

Which Grok 4.5 does this page describe?

Grok 4.5 is a model record from xAI in the Grok family. Source

The recorded model identifier or checkpoint is grok-4.5. Use that exact identifier when checking documentation or a provider listing. Source

How can you access Grok 4.5?

The catalog documents API access for Grok 4.5. Source

As of the catalog check, this version was listed as available. Source

For API use, confirm the exact model identifier, your account and region, and the endpoint's current limits in the linked documentation. An API listing does not establish access through a consumer subscription.

How much does Grok 4.5 cost?

The recorded token rates for Grok 4.5 are:

  • Input: US$2 per 1 million input tokens. Source
  • Output: US$6 per 1 million output tokens. Source

Rate conditions: USD per million standard input/output tokens on the direct xAI API. The page warns that requests exceeding 200K context use different rates; these base rates must not be applied to every context size. Cached input, tools and regional deployment can differ. Source

Illustrative arithmetic: 10,000 input tokens plus 2,000 output tokens would cost US$0.032 at those recorded rates. This assumes every token is billed at the displayed rate and excludes any cache, batch, tool, storage or tier adjustments; it is not a quote or measured usage.

Check the source's pricing conditions before budgeting. A token rate does not state the price of an app subscription or the full cost of running downloaded weights.

What are Grok 4.5's context and output limits?

The documented context window is 500,000 tokens. Source

A separate maximum-output value is not established in this record. The context or input figure should not be used as an output allowance.

Context, input and output limits describe different constraints. Do not add the figures together to infer a larger window. Check the endpoint's accounting for conversation history, system instructions, tools, media and generated tokens; a documented maximum is not a guarantee of answer quality or a measured usable capacity.

What can Grok 4.5 receive and generate?

Documented inputs: text and image. Source

Documented outputs: text. Source

Input support and output generation are separate capabilities. Reading an image does not establish image generation; a text output listing does not establish speech output. File sizes, formats and media limits depend on the documented implementation.

What distinguishes Grok 4.5?

These details come from the linked publisher material for this model. Reported capabilities and training descriptions are publisher statements, not independent test results.

Integration features
The exact model page lists function calling and structured outputs. This documents interface support, not a measured reliability score. Source
Batch API
Supported. This is the exact model detail card’s listed batch support; verify the regional endpoint before deploying. Source
Reasoning settings
The detailed settings list low, medium, high, xhigh, with high as default. Source

Keep the exact version in view

Other Grok models from xAI.

These are separate records in the same publisher family. A shared family name does not establish equal capabilities or interchangeable licenses.

Grok 4.20

API · 1,000,000 context tokens

Grok 4.3

API · 1,000,000 context tokens

Grok 4.6

API · 500,000 context tokens

Grok 4.7

API · 500,000 context tokens

The documented record

Specifications, with their sources.

A missing value remains unknown. Input limits, output limits and the total context window are separate measurements.

Publisher
xAISource ↗
Family
GrokSource ↗
Version
grok-4.5Source ↗
Availability
AvailableSource ↗
Access
APISource ↗
Inputs
Text · ImageSource ↗
Outputs
TextSource ↗
Context window
500,000 tokensSource ↗
Maximum input
Not documented
Maximum output
Not documented
Knowledge cutoff
Not documented
Training-data cutoff
Not documented
Training completed
Not documented
Release date
Not documented
License
Not documented
Input price / 1M tokens
$2Source ↗
Output price / 1M tokens
$6Source ↗

Read this with the numbers.

Current vendor documentation uses the SpaceXSI brand. Search/tool access is separate from training knowledge.

USD per million standard input/output tokens on the direct xAI API. The page warns that requests exceeding 200K context use different rates; these base rates must not be applied to every context size. Cached input, tools and regional deployment can differ.

Model identifiers and aliases 2
  • grok-4.5-latest
  • grok-build-latest

Follow the evidence

Official sources.

  1. grok 4.5 — official xAI documentation ↗docs.x.ai

From the Headless Thrones newsroom

Editorial about Grok 4.5

No published articles are linked to this exact model yet. New coverage will appear here as it is published.

Your starting point

Grok 4.5

xAI · API

Browse all models ↗
Inputs
Text · ImageSource ↗
Outputs
TextSource ↗
Context window
500,000 tokensSource ↗
Knowledge cutoff
Not documented

A place to begin comparing

76 models to consider.

Matches must share an access route, support every documented input type of your starting model, and return text. When both publish a context limit in the same field, the candidate must fall between half and twice that limit. Unknown or differently defined limits remain as broader matches, after verified near-context matches. Within each group, recent documented releases appear first. These criteria do not establish equal quality. The full current inventory is considered.

MiniMax

MiniMax-M3.1-Flash

Text + Image input; text output · Shared access: API · Documented context within ½–2×

Anthropic

Claude Haiku 5.5

Text + Image input; text output · Shared access: API · Documented context within ½–2×

Mistral AI

Mistral Large 4

Text + Image input; text output · Shared access: API · Documented context within ½–2×

Anthropic

Claude Sonnet 5.5

Text + Image input; text output · Shared access: API · Documented context within ½–2×

Anthropic

Claude Opus 5.5

Text + Image input; text output · Shared access: API · Documented context within ½–2×

Xiaomi

mimo-v2.6-flash

Text + Image input; text output · Shared access: API · Documented context within ½–2×

Xiaomi

mimo-v2.6-pro

Text + Image input; text output · Shared access: API · Documented context within ½–2×

Anthropic

Claude Fable 5.1

Text + Image input; text output · Shared access: API · Documented context within ½–2×

Anthropic

Claude Mythos 5.1

Text + Image input; text output · Shared access: API · Documented context within ½–2×

Anthropic

Claude Opus 5

Text + Image input; text output · Shared access: API · Documented context within ½–2×

Anthropic

Claude Sonnet 5

Text + Image input; text output · Shared access: API · Documented context within ½–2×

Anthropic

Claude Fable 5

Text + Image input; text output · Shared access: API · Documented context within ½–2×

A record you can follow

The source belongs beside the fact.

Official sources

Model records cite the developer’s documentation, release notes and model cards. A listing alone is not a tested service or a recommendation.

Dates mean different things

Knowledge cutoff, training-data cutoff, training completion and release date are separate fields. A model’s name or repository upload date does not establish any of them.

Limits need context

Some publishers use rounded K/M token figures. Deployment, reasoning settings and regional access can change usable limits. Read the source before choosing.

Coverage and last check

Independent editorial model library assembled from primary vendor documentation and official publisher model cards. This is a dated, auditable inventory of the sources reviewed, not a claim to every model worldwide. First-party language-model inventory for OpenAI, Anthropic, Google Gemini/Gemma, xAI, Meta and Reflection. Includes vendor-listed legacy/retired identities with explicit statuses; official pretrained and instruction-tuned checkpoints remain distinct. Excludes embeddings, moderation/guard models, image/audio/video-only generation, community fine-tunes, speculative draft helpers, format/runtime/quantization duplicates, and PaliGemma dataset-specific benchmark fine-tunes. Availability means documented vendor API or downloadable official weights, not guaranteed account eligibility. Unknown specifications and dates remain null. Rounded K/M limits preserve vendor granularity; exact integers are used only where documented. No OpenRouter facts are used. Primary-source inventory of language-capable models from Alibaba/Qwen, DeepSeek, Moonshot, MiniMax, Z.ai, ByteDance Seed, Tencent, Baidu, Xiaomi, StepFun, 01.AI, Shanghai AI Laboratory, Baichuan and OpenBMB. Includes full reachable official public weight inventories plus documented hosted API models and explicit retirements. Embeddings, reward/classifier/router/tokenizer/draft-head components, standalone OCR/document converters and image/video/audio-only generators are excluded; multimodal language models retained. Official packaging variants are folded into aliases where a canonical listing was identifiable; remaining research/base/SFT variants retain exact identities. Not a guarantee every historical/private/regional model is available. Unknown specifications remain null; K/M API display quantities use decimal normalization where explicitly noted, rather than implying verified exact serving ceilings. Model-name dates and repository creation timestamps are never used as release/training dates. Open weights does not mean unrestricted or OSI-open-source licensing. Some model-card bodies were unreachable; their public inventory metadata is retained and disclosed. Official Mistral, Cohere, AI21, NVIDIA Nemotron, Microsoft Phi/MAI, Amazon Nova, IBM Granite, AllenAI OLMo/Molmo, TII Falcon, Nous Research, Arcee and Essential AI model inventory checked 2026-10-23. Includes base, instruction, reasoning, coding and text-producing multimodal models, including legacy API versions. Excludes embeddings/rerankers/reward and safety classifiers, image/audio/video-only generation, robotics-only models, duplicate quantization/runtime packages, adapters, intermediate checkpoint experiments, and third-party mirrors. Arcee coverage focuses on its named product families rather than exploratory merge repositories. Repository listing means listed, not independently verified API availability. K/M figures are nominal decimal normalizations when the source supplies shorthand; deployment-specific exact token limits may differ. Unverified values remain null. This is a source-backed inventory, not a complete claim-level independent editorial review. Supplemental official Liquid AI, Reka and Inception generative language catalog. Excludes media-only generators and decision/classification-only models. No assumed training dates.

Catalog edition updated . Source links are provided on each model record.

View the full coverage report and discovery sources ↗