GPT 4.1 Nano pricing for customer support bot

Quick start

Call GPT 4.1 Nano with the OpenAI Python SDK:

from openai import OpenAI

client = OpenAI()
response = client.chat.completions.create(
    model="gpt-4.1-nano",
    max_tokens=1000,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.000700 per call at standard rates
# Input:  $0.10/MTok
# Output: $0.40/MTok

How GPT 4.1 Nano compares on cost

Per-call cost for all models scoring 50+ on customer support bot benchmarks. Hover for details.

Cheapest viable option: GPT 5.6 Luna at $0.001800/call (-157% less, 85/100 quality).

What drives customer support bot cost

Support bots combine RAG's retrieved context with a chatbot's growing history, so they carry both cost curves at once. Volume is high and margins per conversation are thin, which makes the per-call rate matter more than in almost any other use case here. Caching the knowledge base and product context is the single highest-leverage change.

For GPT 4.1 Nano specifically, that means output tokens cost 4.0x more than input, at $0.40 vs $0.10 per MTok. At this use case’s 3,000/1,000 token split, output accounts for 57% of the $0.000700 per-call cost.

GPT 4.1 Nano quality benchmarks for customer support bot

Benchmark data for customer support bot is pending for GPT 4.1 Nano. Test against your own evaluation suite before moving to production.

Performance across all task types

GPT 4.1 Nano scores by task type. Customer Support Bot highlighted.

Confidence scores are a third-party benchmark snapshot from week 29 of 2026. This snapshot is 10 weeks old, so treat the scores as directional and validate against your own evals.

About GPT 4.1 Nano

Backfilled on 2026-09-23. Prices confirmed by the provider pricing page and the LiteLLM cross-check. Release date not published in a machine-readable source. Not yet benchmarked, so never recommended.

Other models from GPT

You can compare GPT 4.1 Nano 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