Grok Build 0.1 pricing for blog writing

Quick start

Call Grok Build 0.1 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-build-0.1",
    max_tokens=8000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0170 per call at standard rates
# Input:  $1.00/MTok
# Output: $2.00/MTok

How Grok Build 0.1 compares on cost

Per-call cost for all models scoring 50+ on blog writing benchmarks. Hover for details.

Cheapest viable option: Claude Sonnet 5 at $0.0820/call (-382% less, 87/100 quality).

What drives blog writing cost

The most output-heavy use case tracked here. A brief of a few hundred tokens produces an article of several thousand, so output pricing is essentially the entire cost and input rate is noise. Generating section by section rather than whole-article gives you more control over both quality and spend, at the cost of more calls.

For Grok Build 0.1 specifically, that means output tokens cost 2.0x more than input, at $2.00 vs $1.00 per MTok. At this use case’s 1,000/8,000 token split, output accounts for 94% of the $0.0170 per-call cost.

Grok Build 0.1 quality benchmarks for blog writing

Benchmark data for blog writing is pending for Grok Build 0.1. Test against your own evaluation suite before moving to production.

Performance across all task types

Grok Build 0.1 scores by task type. Blog Writing 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 Build 0.1

xAI's coding-specialised model and the cheapest Grok row on output. Released in early access; xAI publishes release notes at month granularity only.

Other models from Grok

You can compare Grok Build 0.1 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