o1 pricing for sentiment analysis

Quick start

Call o1 with the OpenAI Python SDK:

from openai import OpenAI

client = OpenAI()
response = client.chat.completions.create(
    model="o1",
    max_tokens=100,
    messages=[{"role": "user", "content": "Your prompt here"}]
)
# Cost: ~$0.0135 per call at standard rates
# Input:  $15.00/MTok
# Output: $60.00/MTok

How o1 compares on cost

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

Cheapest viable option: GPT 5.6 Luna at $0.000220/call (98% less, 91/100 quality).

What drives sentiment analysis cost

Short text in, a label or score out: the cheapest shape an API call can take. Output pricing is irrelevant at this size. Because these run in bulk over historical data as often as in real time, the batch API discount typically applies, and the effective rate lands well below list.

For o1 specifically, that means output tokens cost 4.0x more than input, at $60.00 vs $15.00 per MTok. At this use case’s 500/100 token split, output accounts for 44% of the $0.0135 per-call cost.

o1 quality benchmarks for sentiment analysis

Benchmark data for sentiment analysis is pending for o1. Test against your own evaluation suite before moving to production.

Performance across all task types

o1 scores by task type. Sentiment Analysis 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 o1

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 o1 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