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OpenAI: GPT-3.5 Turbo Instruct API Pricing

OpenAI: GPT-3.5 Turbo Instruct costs $1.50 per 1M input tokens and $2.00 per 1M output tokens. Context window: 4K. Prices verified 2026-10-21 · source

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Alternatives to consider

🏠 Same provider
OpenAI: gpt-oss-20b
$0.018 in / $0.090 out
Quality score: 10

Cheapest openai model — 98% less per month

Price history
2026-08-23 → 2026-10-21 · 59 daily snapshots
inputoutput

Rebuilt daily from our snapshot archive — the chart appears once a model has 5+ snapshots of history.

Pricing behavior
Stable — no price moves across our 59 daily snapshots (2026-08-23 → 2026-10-21).

From our own daily snapshot archive — independent of provider announcements.

Input / 1M tokens
$1.50
Output / 1M tokens
$2.00
Context window
4K
Max output
4K
Knowledge cutoff
2021-09-30

Training data ends here — newer events require retrieval or web search.

What would OpenAI: GPT-3.5 Turbo Instruct cost you per month?

WorkloadRequests/moAvg tokens (in/out)Est. monthly cost
Light chatbot10,000800 / 400$20.00
Coding agent5,0008,000 / 2,000$80.00
RAG pipeline30,0004,000 / 500$210.00
Doc summarizer2,00020,000 / 1,000$64.00

Estimates use list prices without prompt caching. Caching can cut input cost by up to 90% on repeated context.

About OpenAI: GPT-3.5 Turbo Instruct

This model is a variant of GPT-3.5 Turbo tuned for instructional prompts and omitting chat-related optimizations. Training data: up to Sep 2021.

Compare OpenAI: GPT-3.5 Turbo Instruct with

Popular head-to-heads — see all on the comparisons index.

Frequently asked questions

How much does OpenAI: GPT-3.5 Turbo Instruct cost?

OpenAI: GPT-3.5 Turbo Instruct costs $1.50 per 1M input tokens and $2.00 per 1M output tokens. Verified 2026-10-21 — provider source.

What is the context window?

4K tokens, with up to 4K output tokens per response. That's roughly 5 pages of text in a single request.

Does it support prompt caching?

Prompt-caching pricing is not published for this model via OpenRouter.

What's a cheaper alternative?

ScaleDown: Summarize saves about 98% on a typical workload with comparable quality.

Official resources