OpenAI · language model
GPT-3.5 Turbo (older v0613): pricing, context and benchmarks
GPT-3.5 Turbo (older v0613) is OpenAI's model released on January 25, 2024. It costs $1 per million input tokens and $2 per million output tokens, with a 4.1K-token context window. No independent score has been published for it so far.
| Price | 11/30 | |
|---|---|---|
| Context | 0/15 | |
| Features | 8/15 |
What you need to know about GPT-3.5 Turbo (older v0613)
OpenAI, based in United States, put GPT-3.5 Turbo (older v0613) online on January 25, 2024. It accepts text as input and produces text. Its context window reaches 4,095 tokens, larger than 1 % of the models in the registry, and it can write up to 3,685 tokens in one go.
Released more than 2 years ago, it belongs to a generation most vendors have since superseded.
GPT-3.5 Turbo (older v0613) pricing
On OpenRouter, GPT-3.5 Turbo (older v0613) costs $1 per million input tokens and $2 per million output tokens. Counting three tokens read for every token written, its average price is $1.25 per million, more expensive than 63 % of paid models (1.6 times 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 $0.003. At 1,000 tasks a day, budget $90 a month. The price calculator redoes this with your own volumes.
Performance and benchmarks
Epoch AI does not yet publish a capabilities index for GPT-3.5 Turbo (older v0613). 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
Computed score: 32/100, from public data (performance, price, context, features).
Strengths
- Agent-ready: tool calling and structured JSON output.
Limitations
- Short context (4.1K 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
Comparisons and tools
Learn more
Frequently asked questions
How much does GPT-3.5 Turbo (older v0613) cost?
$1 per million input tokens and $2 per million output tokens on OpenRouter (checked October 25, 2026). A task with 2,000 tokens read and 500 written costs $0.003.
How big is GPT-3.5 Turbo (older v0613)'s context window?
4,095 tokens, roughly 3,000 words, with a maximum of 3,685 output tokens.
Can GPT-3.5 Turbo (older v0613) run locally?
No, OpenAI does not publish its weights: it is API-only.
Is GPT-3.5 Turbo (older v0613) 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 (older v0613)?
The closest models on price and performance are Nano Banana 2 (Gemini 3.1 Flash Image Preview), Aion-RP 1.0 (8B), and Qwen3 235B A22B Thinking 2507.
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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