GPT-3.5 Turbo 16k with Jev
GPT-3.5 Turbo 16k is a model from OpenAI, released 2023-08-28. It costs $3.00 per million input tokens and $4.00 per million output tokens, reads up to 16K tokens of context, and writes up to 4,096 tokens in one reply. Through llm11, set model to openai/gpt-3.5-turbo-16k.
- Input price
- $3.00 / 1M
- Output price
- $4.00 / 1M
- Context window
- 16K tokens
- Max output
- 4K tokens
- Released
- 2023-08-28
- Accepts
- text
Read from the live catalogue and refreshed daily. At blended list price, 21% of the 332 priced models we can call cost more.
Using GPT-3.5 Turbo 16k 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 16k does the answering when Jev sends it work, or when you name it yourself. At list price GPT-3.5 Turbo 16k 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-16k as model and routing steps aside while verification still runs.
Jev is new, so we have not published results for GPT-3.5 Turbo 16k 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 | $0.00230 | $2.30 |
| Question over retrieved documents | 4,000 / 500 | $0.014 | $14.00 |
| Long document summary | 30,000 / 1,000 | $0.094 | $94.00 |
Cheaper models to try
The catalogue has no benchmark score for GPT-3.5 Turbo 16k, so this is a price ordering. It does not claim these answer as well.
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| SpaceXAI Grok 4.7 | $2.00 | $6.00 | 500K | |
| Qwen Qwen3.8 Max (0902) | $2.00 | $6.00 | 1M | |
| Qwen Qwen3.8 2.4T A95B | $2.00 | $6.00 | 1.05M | |
| SpaceXAI Grok 4.6 | $2.00 | $6.00 | 500K |
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-16k",
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 16k 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 16k does the answering when Jev sends it work, or when you name it yourself. At list price GPT-3.5 Turbo 16k 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-16k 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 16k a System One model?
- No. GPT-3.5 Turbo 16k 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 16k cost?
- $3.00 per million input tokens and $4.00 per million output tokens. A 4,000 token prompt with a 500 token answer costs about $0.014, so a thousand of them is about $14.00. llm11 passes provider list price through and charges 5% when you buy credits.
- What is the GPT-3.5 Turbo 16k context window?
- 16,385 tokens, with up to 4,096 tokens in a single reply.
- Does GPT-3.5 Turbo 16k 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 16k through llm11?
- Yes. Set model to openai/gpt-3.5-turbo-16k on the OpenAI-compatible endpoint and the request goes to it directly, with verification still running.
- Does Jev route to GPT-3.5 Turbo 16k?
- Routing decisions are made by Jev, TypeSafe AI's System One model. At list price GPT-3.5 Turbo 16k 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-16k as model and routing steps aside while verification still runs.
- What is a cheaper alternative to GPT-3.5 Turbo 16k?
- Nearest in price and below it: SpaceXAI Grok 4.7 at $2.00 in and $6.00 out, Qwen Qwen3.8 Max (0902) at $2.00 in and $6.00 out and Qwen Qwen3.8 2.4T A95B at $2.00 in and $6.00 out. The catalogue has no benchmark score for GPT-3.5 Turbo 16k, so this is a price ordering. It does not claim these answer as well.