Grok 4.5 pricing for code review

Quick start

Call Grok 4.5 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-4.5",
    max_tokens=2000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0220 per call at standard rates
# Input:  $2.00/MTok
# Output: $6.00/MTok

How Grok 4.5 compares on cost

Per-call cost for all models scoring 50+ on code review benchmarks. Hover for details.

Cheapest viable option: Claude Sonnet 5 at $0.0300/call (-36% less, 96/100 quality).

What drives code review cost

Review is input-heavy in a way generation is not: the diff or file goes in whole, and structured feedback comes back short. That flips the usual optimization: input rate and cache discounts matter more than output rate. Reviewing the same repository repeatedly means the surrounding context is identical call over call, which is exactly the shape prompt caching is designed for.

For Grok 4.5 specifically, that means output tokens cost 3.0x more than input, at $6.00 vs $2.00 per MTok. At this use case’s 5,000/2,000 token split, output accounts for 55% of the $0.0220 per-call cost.

Grok 4.5 quality benchmarks for code review

Benchmark data for code review is pending for Grok 4.5. Test against your own evaluation suite before moving to production.

Performance across all task types

Grok 4.5 scores by task type. Code Review 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 4.5

Same list price as Grok 4.6 but a cheaper cached rate ($0.30/MTok vs $0.50), so cache-heavy workloads are cheaper here than on 4.6. xAI publishes release notes at month granularity only; dated to the start of the month.

Other models from Grok

You can compare Grok 4.5 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