Grok 4.3 pricing for math reasoning

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=3000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.009375 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 math reasoning benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.003900/call (58% less, 86/100 quality).

What drives math reasoning cost

Short problems, long solutions. Input is trivial and output is large because the derivation is the answer, so output rate is effectively the only price that matters. Models differ sharply in how much they show their working, which means two models at the same output rate can differ substantially in real cost per problem.

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 1,500/3,000 token split, output accounts for 80% of the $0.009375 per-call cost.

Grok 4.3 quality benchmarks for math reasoning

Performance across all task types

Grok 4.3 scores by task type. Math Reasoning 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 4.3

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