Grok Build 0.1 pricing for invoice parsing

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=600,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.003200 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 invoice parsing benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.001120/call (65% less, 89/100 quality).

What drives invoice parsing cost

Invoices are short, highly repetitive documents processed in bulk: the ideal batch API workload. Per-document cost is low; total cost is set by volume and by whether you are paying full rate for a job that could have run asynchronously overnight at a discount. The extraction schema is constant, so it should never be paying full input rate either.

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 2,000/600 token split, output accounts for 38% of the $0.003200 per-call cost.

Grok Build 0.1 quality benchmarks for invoice parsing

Benchmark data for invoice parsing 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. Invoice Parsing 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