Grok Build 0.1 pricing for content moderation

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=100,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.000700 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 content moderation benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.000220/call (69% less, 91/100 quality).

What drives content moderation cost

The highest-volume, lowest-per-call task on this list: short input, a label out. Per-call cost is nearly negligible, which means total cost is a function of throughput alone. At moderation volume the difference between tiers is the entire budget, and a fast-tier model handling the clear cases with escalation for the ambiguous ones beats one model handling everything.

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 500/100 token split, output accounts for 29% of the $0.000700 per-call cost.

Grok Build 0.1 quality benchmarks for content moderation

Benchmark data for content moderation 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. Content Moderation 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