Grok 4.5 pricing for product descriptions

Quick start

Call Grok 4.5 with the OpenAI Python SDK pointed at api.x.ai:

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.x.ai/v1",
    api_key=os.environ["XAI_API_KEY"],
)
response = client.chat.completions.create(
    model="grok-4.5",
    max_tokens=1500,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0100 per call at standard rates
# Input:  $2.00/MTok
# Output: $6.00/MTok

How Grok 4.5 compares on cost

Per-call cost for all models scoring 50+ on product descriptions benchmarks. Hover for details.

Cheapest viable option: Claude Sonnet 5 at $0.0160/call (-60% less, 87/100 quality).

What drives product descriptions cost

Catalogue-scale generation: modest output per item, multiplied across thousands of SKUs. Per-call price is small and total spend is set by catalogue size, which makes this a batch API workload almost by definition: descriptions are rarely needed within seconds. Shared brand and formatting context belongs in the cached prefix.

For Grok 4.5 specifically, that means output tokens cost 3.0x more than input, at $6.00 vs $2.00 per MTok. At this use case’s 500/1,500 token split, output accounts for 90% of the $0.0100 per-call cost.

Grok 4.5 quality benchmarks for product descriptions

Benchmark data for product descriptions is pending for Grok 4.5. Test against your own evaluation suite before moving to production.

Performance across all task types

Grok 4.5 scores by task type. Product Descriptions highlighted.

Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 8 weeks old, so treat the scores as directional and validate against your own evals.

About Grok 4.5

Same list price as Grok 4.6 but a cheaper cached rate ($0.30/MTok vs $0.50), so cache-heavy workloads are cheaper here than on 4.6. xAI publishes release notes at month granularity only; dated to the start of the month.

Other models from Grok

You can compare Grok 4.5 head-to-head against any other model on our model comparison pages, or track how pricing has changed over time on the pricing history tracker.

Frequently asked questions