Grok 4.5
Up to 30%Grok 4.5 is available on LLM.API as an OpenAI-compatible chat endpoint—route xAI quality through one key with transparent token pricing.
What is Grok 4.5?
On LLM.API, Grok 4.5 (grok-4.5) serves as a xAI conversational model for products that need 500K tokens context windows and predictable token pricing. xAI's latest Grok for chat, coding, agentic tools, and lower hallucination risk.
Providers
LLM.API routes Grok 4.5 to the providers below, with discounted effective rates versus list price.
List price by provider ($ / 1M tokens)
InputOutputProvider list prices; the LLM.API discount applies on top.
| Provider | Pricing | Context | Capabilities |
|---|---|---|---|
| in $2000; out — per 1M tokens | 500K tokens | vision, tools, streaming, reasoning, JSON, structured | |
| in $2000; out — per 1M tokens | 500K tokens | vision, tools, streaming, reasoning, JSON, structured |
Prices and availability from the LLMAPI catalogue, updated nightly. Last updated 21 Sept 2026.
Try this model
Test Grok 4.5 right here — free to start.
Suggestions for your first prompt
Code snippet
Call Grok 4.5 through the OpenAI-compatible API — POST /v1/chat/completions.
from openai import OpenAI
client = OpenAI(
api_key="YOUR_LLMAP_KEY",
base_url="https://api.llmapi.ai/v1",
)
resp = client.chat.completions.create(
model="grok-4.5",
messages=[
{"role": "system", "content": "You are a precise product assistant."},
{"role": "user", "content": "Give me three crisp launch checklist items."},
],
)
print(resp.choices[0].message.content){
"model": "grok-4.5",
"messages": [
{"role": "system", "content": "You are a precise product assistant."},
{"role": "user", "content": "Give me three crisp launch checklist items."}
]
}5 Core Capabilities
Conversational UX
Maintains coherent multi-turn assistant behavior for product chat surfaces. Relevant for `grok-4.5` workloads on LLM.API.
Multilingual drafting
Drafts and translates professional content across major business languages. Grounded in the model's chat role rather than generic chat claims.
Tool-ready dialogue
Works well in agent loops that call functions, browsers, or retrieval APIs. Relevant for `grok-4.5` workloads on LLM.API.
Safety-aware replies
Supports product policies with refusals and cautious handling of sensitive topics. Relevant for `grok-4.5` workloads on LLM.API.
Structured outputs
Can produce JSON-friendly or schema-oriented responses when prompted carefully.
6 Most Valuable Use Cases
- Multilingual localization drafts for UX copy with Grok 4.5
- Research synthesis across long documents and tickets
- Coding agents for refactors, tests, and PR explanations with Grok 4.5
- Internal knowledge assistants grounded with your retrieval layer
- Sales and success email drafting with CRM context with Grok 4.5
- Policy Q&A bots with careful refusal behavior
Why Build on LLM.API?
One unified API. Every major model. Built-in reliability, cost control, and observability.
-
Intelligent AI Routing
Automatically route each request to the best model across providers based on latency, cost, and quality—without changing your integration or redeploying code.
One endpoint, every model. -
Cost-Aware Execution
Control spend with per-request cost estimation, smart model selection, and centralized quotas so teams can experiment fast without runaway bills or manual tracking.
More performance, less spend. -
Resilient Fallback Flows
Define automatic, provider-agnostic fallbacks to keep your app up during outages, rate limits, or timeouts—no brittle failover logic scattered through your codebase.
Never go dark on users. -
Deep LLM Observability
Trace every call across providers with logs, metrics, and request replay so you can debug, tune prompts, and optimize model choices from one unified dashboard.
See every token, everywhere. -
Task-Level Orchestration
Describe tasks, not models. LLM.API maps them to the right tools, models, and prompts so you ship complex AI workflows with minimal glue code.
Think tasks, not models. -
High-Throughput Batch APIs
Process millions of inferences efficiently with optimized batch pipelines, concurrency controls, and retry logic—all behind the same simple interface you use for single calls.
Scale from 1 to millions.
Why run Grok 4.5 on LLM.API?
Unified AI Routing
Reach Grok 4.5 and sibling models through one OpenAI-compatible endpoint.
Cost Control
Compare provider price points and keep spend visible as you scale Grok 4.5.
Reliability Layer
Practical: Retry and route across configured providers when a single upstream blips.
Observability
Practical: Trace prompts, tokens, and errors for Grok 4.5 alongside the rest of your stack.
Drop-in SDKs
Production: Keep using familiar OpenAI client patterns with base URL https://api.llmapi.ai/v1.
Model Breadth
Production: Swap Grok 4.5 for chat, media, or embedding alternatives without rewriting auth.
When to Use — When NOT to Use
Use it if...
- You want OpenAI-compatible chat completions through a single LLM.API key (Grok 4.5)
- You need provider failover options exposed for this model id (Grok 4.5)
- Your prompts benefit from the model's family strengths (reasoning, speed, or cost) (Grok 4.5)
- You need a general-purpose text model for assistants, agents, or content workflows (Grok 4.5)
Avoid if...
- You require on-prem only deployment with no cloud inference
- You need pure embedding, OCR, or media generation instead of chat
- Your use case depends on unpublished proprietary benchmarks not listed here
- You need guaranteed real-time hard latency SLAs without benchmarking the provider
BENCHMARKS
Grok 4.5 benchmark scores
Intelligence index
Scale: 0-100 index points
Output speed
Scale: 0-400 tokens per second
Reference price per 1M tokens
Bars compare input and output list prices for this model.
Independent scores published by Artificial Analysis (source). Reference prices are provider list prices, not LLM.API pricing.
COMMUNITY
What developers say about Grok models
Summarised from publicly published developer and community reviews of this model family. Opinions are the sources’, not LLM.API’s, and may not be specific to Grok 4.5.
- API reviews highlight the very large context window, fast responses, and competitive agentic coding scores.
- Head-to-head write-ups against Gemini Flash focus on hybrid reasoning modes and API latency rather than raw benchmark wins.
- Community sentiment is mixed on consistency between reasoning modes; testers advise pinning a mode per workload.
SOURCES
Frequently Asked Questions
What modalities does Grok 4.5 support?
Grok 4.5 accepts text, image and produces text according to its architecture metadata on LLM.API.
How do I call Grok 4.5 via API?
Send OpenAI-compatible requests to https://api.llmapi.ai/v1 with model "grok-4.5" and your LLM.API key. See the code snippet on this page.
Does Grok 4.5 support streaming?
Yes—at least one listed provider advertises streaming.
What is the context length for Grok 4.5?
Reported context for Grok 4.5 is 500K tokens. Always verify the active provider row if multiple providers are listed.
Can I use tools or structured outputs with Grok 4.5?
Tool and/or structured-output flags appear on one or more providers for this model—confirm in the providers table.
Which providers serve Grok 4.5?
LLM.API currently lists: novita, xai. Availability can vary by region and account.
Where is the canonical page for Grok 4.5?
https://llmapi.ai/models/x-ai-grok-4-5/
How is Grok 4.5 priced on LLM.API?
Listed pricing metadata shows: In $2.00 / 1M tokens · Out $6.00 / 1M tokens. LLM.API may offer discounted effective rates (illustrative ~30% callout vs list when available).. Confirm live rates in the LLM.API dashboard or docs before production budgeting.
What are limitations of Grok 4.5?
Like other API models, Grok 4.5 can be wrong, incomplete, or uneven on edge cases. Validate outputs for high-stakes use. Media/OCR/STT models additionally depend on input quality.
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