OpenAI · language model
GPT-3.5 Turbo: pricing, context and benchmarks
GPT-3.5 Turbo is a language model from OpenAI released on May 28, 2023. It costs $0.5 per million input tokens and $1.5 per million output tokens, with a 16.4K-token context window. No independent score has been published for it so far.
| Price | 15/30 | |
|---|---|---|
| Context | 1/15 | |
| Features | 8/15 |
What you need to know about GPT-3.5 Turbo
GPT-3.5 Turbo was released by OpenAI (United States) on May 28, 2023. It accepts text as input and produces text. Its context window reaches 16,385 tokens, larger than 4 % of the models in the registry, and it can write up to 4,096 tokens in one go.
Released more than 3 years ago, it belongs to a generation most vendors have since superseded.
GPT-3.5 Turbo pricing
On OpenRouter, GPT-3.5 Turbo costs $0.5 per million input tokens and $1.5 per million output tokens. Counting three tokens read for every token written, its average price is $0.75 per million, more expensive than 50 % of paid models (1 times cheaper than the median of $0.76).
A concrete example: a task that sends 2,000 tokens (about 1,500 words) and receives a 500-token answer costs $0.0018. At 1,000 tasks a day, budget $53 a month. The price calculator redoes this with your own volumes.
With batch processing (delayed answers), the price drops to $0.25 input and $0.75 output.
Performance and benchmarks
Epoch AI does not yet publish a capabilities index for GPT-3.5 Turbo. We therefore show no made-up performance rating: only price, context and features count towards its score.
Scores published by Epoch AI on the benchmarks the site tracks:
| Benchmark | What it measures | Score | Date |
|---|---|---|---|
| GPQA Diamond | PhD-level science questions | 28 % | Nov 6, 2023 |
Features, privacy and local use
- It supports tool calling, so it can drive an AI agent, call APIs or MCP servers.
- It can answer in an enforced JSON format (structured outputs).
- Its knowledge stops at September 2021.
Its weights are not published: it can only be used through the OpenAI API or a broker such as OpenRouter, which means sending your data off your machines.
Other OpenAI models
| Model | Released | Avg. price | ECI |
|---|---|---|---|
| GPT-6.1 Sol | Sep 29, 2026 | $4 | 168.4 |
| GPT-6.1 Sol Pro | Sep 29, 2026 | $4 | — |
| GPT-6 Sol | Sep 22, 2026 | $4 | 163.7 |
| GPT-6 Luna | Sep 22, 2026 | $0.2 | 156.8 |
| GPT-6 Luna Pro | Sep 22, 2026 | $0.2 | — |
| GPT-6 Sol Pro | Sep 22, 2026 | $4 | — |
| GPT-6 Astra | Sep 4, 2026 | $20 | 168.8 |
| GPT-6 Astra Pro | Sep 4, 2026 | $20 | — |
Verdict
GPT-3.5 Turbo scores 40/100 on our grid, which only uses published figures.
Strengths
- Agent-ready: tool calling and structured JSON output.
- Discounted batch pricing.
Limitations
- Short context (16.4K tokens): long documents must be split.
- No independent score published: performance cannot be verified.
- Older generation, often replaced by a newer model from the same vendor.
- Text only: reads neither images nor files.
Avoid if…
- your data must not leave your servers;
- you analyse long documents in one go.
Alternatives
- Qwen2.5 Coder 32B Instruct$0.75
- Moondream 3 Preview$0.85
- Moondream 3.1$0.85
- Gemma 2 27B$0.65
- Nano Banana (Gemini 2.5 Flash Image)$0.85
- Skyfall 36B V2$0.61
Comparisons and tools
Learn more
Frequently asked questions
How much does GPT-3.5 Turbo cost?
$0.5 per million input tokens and $1.5 per million output tokens on OpenRouter (checked October 25, 2026). A task with 2,000 tokens read and 500 written costs $0.0018.
How big is GPT-3.5 Turbo's context window?
16,385 tokens, roughly 12,000 words, with a maximum of 4,096 output tokens.
Can GPT-3.5 Turbo run locally?
No, OpenAI does not publish its weights: it is API-only.
Is GPT-3.5 Turbo suitable for an AI agent?
Technically yes: it supports tool calling and structured outputs. Then check its cost for your volume.
What are the alternatives to GPT-3.5 Turbo?
The closest models on price and performance are Qwen2.5 Coder 32B Instruct, Moondream 3 Preview, and Moondream 3.1.
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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score