GPT-4.1 Nano (batch) API Pricing
OpenAI · context window 1M · prices updated 2026-08-23
Where GPT-4.1 Nano (batch) sits on price
At $0.2 per million output tokens, GPT-4.1 Nano (batch) is a budget tier model — 11.3× cheaper than the median output price of $2.25, which puts it in the cheapest 10% of everything we track. It sits 3th cheapest of the 93 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 GPT-4.1 Nano (batch)
These three workloads are the ones teams actually run on a budget-priced model — a $0.2/1M model is not bought for the same job as one ten times the price.
| Workload | Per request | Per month |
|---|---|---|
| High-volume classification — 200K requests/day (400 in / 20 out) Short output, huge volume: the input price dominates the bill. | $0 | $144 |
| Small app — 1K requests/day (500 in / 150 out) The baseline most side projects actually run at. | $0.0001 | $1.65 |
| Long-context analysis — 200 runs/day (250K in / 4K out) Only possible on large-context models; input cost is nearly the whole bill. | $0.0133 | $79.80 |
Model your exact traffic in the API cost calculator — it preloads GPT-4.1 Nano (batch) with caching and batch options.
GPT-4.1 Nano (batch) price history
GPT-4.1 Nano (batch)'s price has not moved since we began tracking it on Aug 6, 2026 — 17 days of stability in a market where 55 of the 302 models we track have repriced over the same period, including 9 of OpenAI's own 93 models.
Change-points from our daily price snapshots (tracking since Aug 6, 2026; intraday moves between snapshots are not captured).
GPT-4.1 Nano (batch) vs Qwen2.5 7B Instruct
The closest-priced alternative from another vendor is Qwen2.5 7B Instruct (Alibaba (Qwen)) — priced within a rounding error on output, with $0.05 more 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 Qwen2.5 7B Instruct pricing →Cheaper alternatives
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Frequently asked questions
› How much does the GPT-4.1 Nano (batch) API cost?
GPT-4.1 Nano (batch) costs $0.05 per million input tokens and $0.2 per million output tokens, with cached input at $0.0125 per million (75% cheaper). That works out to roughly 5,000,000 output tokens per dollar.
› What does the high-volume classification workload cost on GPT-4.1 Nano (batch)?
High-volume classification — 200K requests/day (400 in / 20 out) costs about $0 per request and $144 per month on GPT-4.1 Nano (batch). Short output, huge volume: the input price dominates the bill.
› What does it cost to fill GPT-4.1 Nano (batch)'s 1M context window?
Sending 1M of input in a single request costs $0.0524 at $0.05 per million tokens — before any output. With prompt caching that same fill drops to about $0.0131 on repeat requests. This is why large context windows are cheap to advertise and expensive to actually use.
› Is GPT-4.1 Nano (batch) worth the price?
GPT-4.1 Nano (batch) is in the cheapest end of the market — cheaper than 93% of the models we track. At this price the question is not cost but capability: it is a good fit for classification, extraction, routing and bulk summarisation, and a poor fit for multi-step reasoning where a wrong answer costs more than the tokens saved.