GPT-3.5-turbo API Pricing

OpenAI has deprecated this model. The price is kept here for reference; check the provider's documentation before building on it.

OpenAI · released Mar 1, 2023 · 16K context · API model ID gpt-3.5-turbo

GPT-3.5-turbo by OpenAI API pricing: $0.50 per 1M input tokens and $1.50 per 1M output tokens (provider list price via models.dev, Oct 10, 2026).

Prices

GPT-3.5-turbo prices, USD per 1M tokens
PriceUSD per 1M tokens
Input$0.50
Output$1.50
Cache readFree
Cache writeNot published

OpenAI's list price for its own API, as compiled by models.dev and checked Oct 10, 2026, 09:00 UTC. Prices on cloud platforms and resellers can differ. Provider documentation

Estimated monthly cost

$375.00

per month

per day
$12.50
per request
$0.00125

Cost = input tokens × input price + output tokens × output price, 30 days a month. Cached input uses the cache read price. Cache write fees are not included.

Compare this workload across models

Monthly cost by workload

WorkloadPer month
Chatbot1,000 in / 500 out tokens, 10,000 requests a day$375.00/mo
RAG8,000 in / 500 out tokens, 5,000 requests a day$712.50/mo
Coding agent50,000 in / 2,000 out tokens, 1,000 requests a day, 80% cached input$240.00/mo

Context and capabilities

Context
16,385 tokens
Max output
4,096 tokens
Input
text
Output
text
Knowledge cutoff
Sep 1, 2021
Open weights
No
Tool calling
No
Reasoning
No
Structured outputs
No

Capabilities and limits as listed by models.dev.

Similarly priced models

Price history

No price changes since we started tracking on Oct 8, 2026.

Questions

How much does GPT-3.5-turbo cost per month?
For a chatbot handling 10,000 requests a day with 1,000 input and 500 output tokens each, GPT-3.5-turbo costs about $375.00 per month at OpenAI's list prices ($0.50 per 1M input tokens, $1.50 per 1M output tokens).
Does GPT-3.5-turbo support prompt caching?
Yes. Cached input costs Free per 1M tokens, compared with $0.50 for regular input.
How long is GPT-3.5-turbo's context window?
GPT-3.5-turbo accepts up to 16,385 tokens (16K) of context and returns up to 4,096 tokens per response.