Grok 4.3 pricing for data extraction

Quick start

Call Grok 4.3 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-4.3",
    max_tokens=1000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.007500 per call at standard rates
# Input:  $1.25/MTok
# Output: $2.50/MTok

How Grok 4.3 compares on cost

Per-call cost for all models scoring 50+ on data extraction benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.002000/call (73% less, 89/100 quality).

What drives data extraction cost

Extraction is input-heavy and output-light (the raw document goes in, structured fields come out), which makes it one of the cheapest tasks per unit of value on this list. Output is small enough that output pricing is nearly irrelevant. Cost tracks document size, so the lever is sending only the pages that contain the fields you want.

For Grok 4.3 specifically, that means output tokens cost 2.0x more than input, at $2.50 vs $1.25 per MTok. At this use case’s 4,000/1,000 token split, output accounts for 33% of the $0.007500 per-call cost.

Grok 4.3 quality benchmarks for data extraction

Benchmark data for data extraction is pending for Grok 4.3. Test against your own evaluation suite before moving to production.

Performance across all task types

Grok 4.3 scores by task type. Data Extraction 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 4.3

xAI publishes no release date for this model; dated to the March 4.20-generation launch whose pricing and 1M context window it shares. Priced from the live models table, which is what matters for costing traffic.

Other models from Grok

You can compare Grok 4.3 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