Grok 4.6 pricing for legal analysis

Quick start

Call Grok 4.6 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-4.6",
    max_tokens=4000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0440 per call at standard rates
# Input:  $2.00/MTok
# Output: $6.00/MTok

How Grok 4.6 compares on cost

Per-call cost for all models scoring 50+ on legal analysis benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.006800/call (85% less, 86/100 quality).

What drives legal analysis cost

Legal work is heavy on both sides: long source documents in, detailed analysis out. It is also the case where accuracy is worth the most, so the cheapest-viable-model logic that works for classification does not apply. Long contracts frequently cross long-context pricing thresholds, which can re-rate the entire request rather than just the excess.

For Grok 4.6 specifically, that means output tokens cost 3.0x more than input, at $6.00 vs $2.00 per MTok. At this use case’s 10,000/4,000 token split, output accounts for 55% of the $0.0440 per-call cost.

Grok 4.6 quality benchmarks for legal analysis

Performance across all task types

Grok 4.6 scores by task type. Legal Analysis highlighted.

Confidence scores are a third-party benchmark snapshot from week 26 of 2026. This snapshot is 17 weeks old, so treat the scores as directional and validate against your own evals.

About Grok 4.6

Other models from Grok

You can compare Grok 4.6 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