Llama 3.2 1B Instruct with Jev
Llama 3.2 1B Instruct is a model from Meta, released 2024-09-25. It costs $0.027 per million input tokens and $0.201 per million output tokens, reads up to 60K tokens of context, and writes up to 54,000 tokens in one reply. Through llm11, set model to meta-llama/llama-3.2-1b-instruct.
- Input price
- $0.027 / 1M
- Output price
- $0.201 / 1M
- Context window
- 60K tokens
- Max output
- 54K tokens
- Released
- 2024-09-25
- Accepts
- text
Read from the live catalogue and refreshed daily. At blended list price, 95% of the 332 priced models we can call cost more.
Using Llama 3.2 1B 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 3.2 1B Instruct does the answering when Jev sends it work, or when you name it yourself. At list price Llama 3.2 1B Instruct falls in the llm11-fast band, but no pack routes to it because it does not advertise structured output, which the verification checks rely on. You can still pin it: pass meta-llama/llama-3.2-1b-instruct as model and routing steps aside while verification still runs.
Jev is new, so we have not published results for Llama 3.2 1B 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 | $0.00005 | $0.054 |
| Question over retrieved documents | 4,000 / 500 | $0.00021 | $0.208 |
| Long document summary | 30,000 / 1,000 | $0.00101 | $1.01 |
Cheaper models to try
The catalogue has no benchmark score for Llama 3.2 1B Instruct, so this is a price ordering. It does not claim these answer as well.
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| OpenAI gpt-oss-120b | $0.037 | $0.170 | 131K | |
| Cohere Command R7B (12-2024) | $0.037 | $0.150 | 128K | |
| Google Gemma 3 4B | $0.050 | $0.100 | 131K | |
| Mistral Mistral Small 3 | $0.050 | $0.080 | 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-3.2-1b-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 3.3 70B Instruct | $0.100 | $0.320 | 131K | |
| Llama 3.2 3B Instruct | $0.050 | $0.330 | 131K | |
| Llama 3.1 70B Instruct | $0.400 | $0.400 | 131K |
Questions
- What is Llama 3.2 1B 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 3.2 1B Instruct does the answering when Jev sends it work, or when you name it yourself. At list price Llama 3.2 1B Instruct falls in the llm11-fast band, but no pack routes to it because it does not advertise structured output, which the verification checks rely on. You can still pin it: pass meta-llama/llama-3.2-1b-instruct as model and routing steps aside while verification still runs. Routing decisions are made by Jev, TypeSafe AI's System One model.
- Is Llama 3.2 1B Instruct a System One model?
- No. Llama 3.2 1B 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 3.2 1B Instruct cost?
- $0.027 per million input tokens and $0.201 per million output tokens. A 4,000 token prompt with a 500 token answer costs about $0.00021, so a thousand of them is about $0.208. llm11 passes provider list price through and charges 5% when you buy credits.
- What is the Llama 3.2 1B Instruct context window?
- 60,000 tokens, with up to 54,000 tokens in a single reply.
- Does Llama 3.2 1B Instruct support tool calling and structured output?
- The catalogue does not list tool calling, structured output and reasoning controls.
- Can I use Llama 3.2 1B Instruct through llm11?
- Yes. Set model to meta-llama/llama-3.2-1b-instruct on the OpenAI-compatible endpoint and the request goes to it directly, with verification still running.
- Does Jev route to Llama 3.2 1B Instruct?
- Routing decisions are made by Jev, TypeSafe AI's System One model. At list price Llama 3.2 1B Instruct falls in the llm11-fast band, but no pack routes to it because it does not advertise structured output, which the verification checks rely on. You can still pin it: pass meta-llama/llama-3.2-1b-instruct as model and routing steps aside while verification still runs.
- What is a cheaper alternative to Llama 3.2 1B Instruct?
- Nearest in price and below it: OpenAI gpt-oss-120b at $0.037 in and $0.170 out, Cohere Command R7B (12-2024) at $0.037 in and $0.150 out and Google Gemma 3 4B at $0.050 in and $0.100 out. The catalogue has no benchmark score for Llama 3.2 1B Instruct, so this is a price ordering. It does not claim these answer as well.