o3 (batch) API Pricing
OpenAI · context window 200K · prices updated 2026-09-29
Where o3 (batch) sits on price
At $4.00 per million output tokens, o3 (batch) is a mid tier model — 1.8× the median output price of $2.20, which puts it cheaper than 39% and pricier than 61% of the models we track. It sits 38th cheapest of the 100 OpenAI models we track. Output costs 4.0× input, the usual spread — trim both, starting with the answer length.
Cached input is 75% cheaper. On an input-heavy workload you need roughly a 33% cache-hit rate to take 25% off the input line — reachable for chatbots and agents that resend the same system prompt and history.
What real workloads cost on o3 (batch)
These three workloads are the ones teams actually run on a mid-priced model — a $4.00/1M model is not bought for the same job as one ten times the price.
| Workload | Per request | Per month |
|---|---|---|
| Support chatbot — 500 conversations/day (5K in / 1.4K out) Conversation history re-sent each turn — the classic prompt-caching win. | $0.0106 | $159 |
| Document pipeline — 10K docs/day (3K in / 500 out) Batch-friendly: no user waiting, so a ~50% batch discount usually applies. | $0.005 | $1500 |
| Small app — 1K requests/day (500 in / 150 out) The baseline most side projects actually run at. | $0.0011 | $33.00 |
Model your exact traffic in the API cost calculator — it preloads o3 (batch) with caching and batch options.
o3 (batch) price history
o3 (batch)'s price has not moved since we began tracking it on Aug 6, 2026 — 54 days of stability in a market where 88 of the 353 models we track have repriced over the same period, including 12 of OpenAI's own 100 models.
Change-points from our daily price snapshots (tracking since Aug 6, 2026; intraday moves between snapshots are not captured).
o3 (batch) vs Qwen3 VL 235B A22B Thinking
The closest-priced alternative from another vendor is Qwen3 VL 235B A22B Thinking (Alibaba (Qwen)) — priced within a rounding error on output, with $0.6 less per million input tokens. When two models land this close on price, the decision is quality on your own workload, not the price sheet: run 50 real requests through both and compare.
See Qwen3 VL 235B A22B Thinking pricing →Cheaper alternatives
More OpenAI models
Frequently asked questions
› How much does the o3 (batch) API cost?
o3 (batch) costs $1.00 per million input tokens and $4.00 per million output tokens, with cached input at $0.25 per million (75% cheaper). That works out to roughly 250,000 output tokens per dollar.
› What does the support chatbot workload cost on o3 (batch)?
Support chatbot — 500 conversations/day (5K in / 1.4K out) costs about $0.0106 per request and $159 per month on o3 (batch). Conversation history re-sent each turn — the classic prompt-caching win.
› What does it cost to fill o3 (batch)'s 200K context window?
Sending 200K of input in a single request costs $0.2 at $1.00 per million tokens — before any output. With prompt caching that same fill drops to about $0.05 on repeat requests. This is why large context windows are cheap to advertise and expensive to actually use.
› Is o3 (batch) worth the price?
o3 (batch) sits in the middle of the market (38 of 100 by price within OpenAI). The honest test is a routing experiment: send the same 200 real requests to this model and to a tier below, and compare failure rate against the price gap — most teams find a majority of traffic never needed the pricier model.