Llama 3.3 70B Instruct with Jev
Llama 3.3 70B Instruct is a model from Meta, released 2024-12-06. It costs $0.100 per million input tokens and $0.320 per million output tokens, reads up to 131K tokens of context, and writes up to 16,384 tokens in one reply. Through llm11, set model to meta-llama/llama-3.3-70b-instruct.
- Input price
- $0.100 / 1M
- Output price
- $0.320 / 1M
- Context window
- 131K tokens
- Max output
- 16K tokens
- Released
- 2024-12-06
- Accepts
- text
Read from the live catalogue and refreshed daily. At blended list price, 82% of the 332 priced models we can call cost more.
Using Llama 3.3 70B Instruct 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. Llama 3.3 70B Instruct does the answering when Jev sends it work, or when you name it yourself. Llama 3.3 70B Instruct falls in the llm11-fast band, and the labs and limits it meets make it eligible for that pack. Packs keep a spread of eight models per band, and it is not one of the eight today, so it is only picked when you name it in a custom pool.
Jev is new, so we have not published results for Llama 3.3 70B Instruct 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 | $0.00011 | $0.114 |
| Question over retrieved documents | 4,000 / 500 | $0.00056 | $0.560 |
| Long document summary | 30,000 / 1,000 | $0.00332 | $3.32 |
Cheaper models to try
The catalogue has no benchmark score for Llama 3.3 70B Instruct, so this is a price ordering. It does not claim these answer as well.
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| Qwen Qwen3 235B A22B Instruct 2507 | $0.087 | $0.350 | 262K | |
| Google Gemma 4 31B | $0.090 | $0.340 | 262K | |
| Mistral Ministral 3 8B 2512 | $0.150 | $0.150 | 262K | |
| Mistral Voxtral Small 24B 2507 | $0.100 | $0.300 | 33K |
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="meta-llama/llama-3.3-70b-instruct",
messages=[{"role": "user", "content": "Hello"}],
)More from Meta
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| Llama Guard 4 12B | $0.180 | $0.180 | 164K | |
| Llama 4 Maverick | $0.188 | $0.652 | 1.05M | |
| Llama 4 Scout | $0.100 | $0.300 | 1.31M | |
| Llama 3.2 1B Instruct | $0.027 | $0.201 | 60K | |
| Llama 3.2 3B Instruct | $0.050 | $0.330 | 131K | |
| Llama 3.1 70B Instruct | $0.400 | $0.400 | 131K |
Questions
- What is Llama 3.3 70B Instruct 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. Llama 3.3 70B Instruct does the answering when Jev sends it work, or when you name it yourself. Llama 3.3 70B Instruct falls in the llm11-fast band, and the labs and limits it meets make it eligible for that pack. Packs keep a spread of eight models per band, and it is not one of the eight today, so it is only picked when you name it in a custom pool. Routing decisions are made by Jev, TypeSafe AI's System One model.
- Is Llama 3.3 70B Instruct a System One model?
- No. Llama 3.3 70B Instruct 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 Llama 3.3 70B Instruct cost?
- $0.100 per million input tokens and $0.320 per million output tokens. A 4,000 token prompt with a 500 token answer costs about $0.00056, so a thousand of them is about $0.560. llm11 passes provider list price through and charges 5% when you buy credits.
- What is the Llama 3.3 70B Instruct context window?
- 131,072 tokens, with up to 16,384 tokens in a single reply.
- Does Llama 3.3 70B Instruct support tool calling and structured output?
- The catalogue lists tool calling and structured output, but it does not list reasoning controls.
- Can I use Llama 3.3 70B Instruct through llm11?
- Yes. Set model to meta-llama/llama-3.3-70b-instruct on the OpenAI-compatible endpoint and the request goes to it directly, with verification still running.
- Does Jev route to Llama 3.3 70B Instruct?
- Routing decisions are made by Jev, TypeSafe AI's System One model. Llama 3.3 70B Instruct falls in the llm11-fast band, and the labs and limits it meets make it eligible for that pack. Packs keep a spread of eight models per band, and it is not one of the eight today, so it is only picked when you name it in a custom pool.
- What is a cheaper alternative to Llama 3.3 70B Instruct?
- Nearest in price and below it: Qwen Qwen3 235B A22B Instruct 2507 at $0.087 in and $0.350 out, Google Gemma 4 31B at $0.090 in and $0.340 out and Mistral Ministral 3 8B 2512 at $0.150 in and $0.150 out. The catalogue has no benchmark score for Llama 3.3 70B Instruct, so this is a price ordering. It does not claim these answer as well.