GPT-3.5 Turbo (older v0613) with Jev
GPT-3.5 Turbo (older v0613) is a model from OpenAI, released 2024-01-25. It costs $1.00 per million input tokens and $2.00 per million output tokens, reads up to 4K tokens of context, and writes up to 3,685 tokens in one reply. Through llm11, set model to openai/gpt-3.5-turbo-0613.
- Input price
- $1.00 / 1M
- Output price
- $2.00 / 1M
- Context window
- 4K tokens
- Max output
- 4K tokens
- Released
- 2024-01-25
- Accepts
- text
Read from the live catalogue and refreshed daily. At blended list price, 36% of the 332 priced models we can call cost more.
Using GPT-3.5 Turbo (older v0613) with Jev
Jev is TypeSafe AI's System One model. It reads each request first and decides which model in your pool answers, with a calibrated confidence on that call. GPT-3.5 Turbo (older v0613) does the answering when Jev sends it work, or when you name it yourself. At list price GPT-3.5 Turbo (older v0613) falls in the llm11-balanced band, but no pack routes to it because its context window is under 32K tokens, the floor for pack members. You can still pin it: pass openai/gpt-3.5-turbo-0613 as model and routing steps aside while verification still runs.
Jev is new, so we have not published results for GPT-3.5 Turbo (older v0613) with and without it, and this page does not invent any. Every response comes with a receipt that names the model that answered and what it cost against your most expensive model, so you can measure the pairing on your own traffic.
What a request costs
List price arithmetic, the same sum a receipt does. llm11 adds nothing per request; the only fee is on buying credits.
| Request | Tokens in / out | One | A thousand |
|---|---|---|---|
| Short chat turn | 500 / 200 | $0.00090 | $0.900 |
| Question over retrieved documents | 4,000 / 500 | $0.00500 | $5.00 |
| Long document summary | 30,000 / 1,000 | $0.032 | $32.00 |
Cheaper models to try
The catalogue has no benchmark score for GPT-3.5 Turbo (older v0613), so this is a price ordering. It does not claim these answer as well.
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| DeepSeek DeepSeek V4 Pro 0423 | $0.955 | $1.91 | 1.05M | |
| DeepSeek R1 | $0.700 | $2.50 | 64K | |
| Qwen Qwen3.8 27B | $0.045 | $4.40 | 1M | |
| Google Gemini 3 Flash Preview | $0.500 | $3.00 | 1.05M |
Call it
Same OpenAI request shape. Naming the model pins it, so nothing is routed, and the answer is still checked.
python
from openai import OpenAI
client = OpenAI(base_url="https://www.llm11.com/v1", api_key="llm11_live_...")
res = client.chat.completions.create(
model="openai/gpt-3.5-turbo-0613",
messages=[{"role": "user", "content": "Hello"}],
)More from OpenAI
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| GPT-6 Luna | $0.100 | $0.500 | 1.05M | |
| GPT-6 Luna Pro | $0.100 | $0.500 | 1.05M | |
| GPT-6 Sol | $2.00 | $10 | 1.05M | |
| GPT-6 Sol Pro | $2.00 | $10 | 1.05M | |
| GPT-6 Astra | $10 | $50 | 1.05M | |
| GPT-6 Astra Pro | $10 | $50 | 1.05M |
Questions
- What is GPT-3.5 Turbo (older v0613) with Jev?
- Jev is TypeSafe AI's System One model. It reads each request first and decides which model in your pool answers, with a calibrated confidence on that call. GPT-3.5 Turbo (older v0613) does the answering when Jev sends it work, or when you name it yourself. At list price GPT-3.5 Turbo (older v0613) falls in the llm11-balanced band, but no pack routes to it because its context window is under 32K tokens, the floor for pack members. You can still pin it: pass openai/gpt-3.5-turbo-0613 as model and routing steps aside while verification still runs. Routing decisions are made by Jev, TypeSafe AI's System One model.
- Is GPT-3.5 Turbo (older v0613) a System One model?
- No. GPT-3.5 Turbo (older v0613) answers requests. The System One model is Jev, which decides which model answers each one, so the two do different jobs and llm11 uses both.
- How much does GPT-3.5 Turbo (older v0613) cost?
- $1.00 per million input tokens and $2.00 per million output tokens. A 4,000 token prompt with a 500 token answer costs about $0.00500, so a thousand of them is about $5.00. llm11 passes provider list price through and charges 5% when you buy credits.
- What is the GPT-3.5 Turbo (older v0613) context window?
- 4,095 tokens, with up to 3,685 tokens in a single reply.
- Does GPT-3.5 Turbo (older v0613) support tool calling and structured output?
- The catalogue lists tool calling and structured output, but it does not list reasoning controls.
- Can I use GPT-3.5 Turbo (older v0613) through llm11?
- Yes. Set model to openai/gpt-3.5-turbo-0613 on the OpenAI-compatible endpoint and the request goes to it directly, with verification still running.
- Does Jev route to GPT-3.5 Turbo (older v0613)?
- Routing decisions are made by Jev, TypeSafe AI's System One model. At list price GPT-3.5 Turbo (older v0613) falls in the llm11-balanced band, but no pack routes to it because its context window is under 32K tokens, the floor for pack members. You can still pin it: pass openai/gpt-3.5-turbo-0613 as model and routing steps aside while verification still runs.
- What is a cheaper alternative to GPT-3.5 Turbo (older v0613)?
- Nearest in price and below it: DeepSeek DeepSeek V4 Pro 0423 at $0.955 in and $1.91 out, DeepSeek R1 at $0.700 in and $2.50 out and Qwen Qwen3.8 27B at $0.045 in and $4.40 out. The catalogue has no benchmark score for GPT-3.5 Turbo (older v0613), so this is a price ordering. It does not claim these answer as well.