Nemotron 3.5 Content Safety with Jev
Nemotron 3.5 Content Safety is a model from NVIDIA, released 2026-06-04. It costs $0.200 per million input tokens and $0.200 per million output tokens, reads up to 131K tokens of context, and writes up to 117,964 tokens in one reply. Through llm11, set model to nvidia/nemotron-3.5-content-safety.
- Input price
- $0.200 / 1M
- Output price
- $0.200 / 1M
- Context window
- 131K tokens
- Max output
- 118K tokens
- Released
- 2026-06-04
- Accepts
- text, image
Read from the live catalogue and refreshed daily. At blended list price, 77% of the 332 priced models we can call cost more.
Using Nemotron 3.5 Content Safety 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. Nemotron 3.5 Content Safety does the answering when Jev sends it work, or when you name it yourself. At list price Nemotron 3.5 Content Safety 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 nvidia/nemotron-3.5-content-safety as model and routing steps aside while verification still runs.
Jev is new, so we have not published results for Nemotron 3.5 Content Safety 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 | $0.00014 | $0.140 |
| Question over retrieved documents | 4,000 / 500 | $0.00090 | $0.900 |
| Long document summary | 30,000 / 1,000 | $0.00620 | $6.20 |
Cheaper models to try
The catalogue has no benchmark score for Nemotron 3.5 Content Safety, so this is a price ordering. It does not claim these answer as well.
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| Qwen Qwen3 VL 32B InstructRetires 2026-10-09 | $0.104 | $0.416 | 131K | |
| Google Gemini 2.5 Flash LiteRetires 2026-10-20 | $0.100 | $0.400 | 1.05M | |
| OpenAI GPT-4.1 Nano | $0.100 | $0.400 | 1.05M | |
| Google Gemma 3 27B | $0.080 | $0.450 | 131K |
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="nvidia/nemotron-3.5-content-safety",
messages=[{"role": "user", "content": "Hello"}],
)More from NVIDIA
| Model | Input / 1M | Output / 1M | Context | Released |
|---|---|---|---|---|
| Nemotron 3.5 Lightning | $0.060 | $0.160 | 262K | |
| Nemotron 3 Ultra | $0.600 | $2.40 | 262K | |
| Nemotron 3 Super | $0.080 | $0.450 | 262K | |
| Nemotron 3 Nano 30B A3B | $0.050 | $0.200 | 262K |
Questions
- What is Nemotron 3.5 Content Safety 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. Nemotron 3.5 Content Safety does the answering when Jev sends it work, or when you name it yourself. At list price Nemotron 3.5 Content Safety 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 nvidia/nemotron-3.5-content-safety as model and routing steps aside while verification still runs. Routing decisions are made by Jev, TypeSafe AI's System One model.
- Is Nemotron 3.5 Content Safety a System One model?
- No. Nemotron 3.5 Content Safety 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 Nemotron 3.5 Content Safety cost?
- $0.200 per million input tokens and $0.200 per million output tokens. A 4,000 token prompt with a 500 token answer costs about $0.00090, so a thousand of them is about $0.900. llm11 passes provider list price through and charges 5% when you buy credits.
- What is the Nemotron 3.5 Content Safety context window?
- 131,072 tokens, with up to 117,964 tokens in a single reply.
- Does Nemotron 3.5 Content Safety support tool calling and structured output?
- The catalogue lists reasoning controls, but it does not list tool calling and structured output.
- Can I use Nemotron 3.5 Content Safety through llm11?
- Yes. Set model to nvidia/nemotron-3.5-content-safety on the OpenAI-compatible endpoint and the request goes to it directly, with verification still running.
- Does Jev route to Nemotron 3.5 Content Safety?
- Routing decisions are made by Jev, TypeSafe AI's System One model. At list price Nemotron 3.5 Content Safety 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 nvidia/nemotron-3.5-content-safety as model and routing steps aside while verification still runs.
- What is a cheaper alternative to Nemotron 3.5 Content Safety?
- Nearest in price and below it: Qwen Qwen3 VL 32B Instruct at $0.104 in and $0.416 out, Google Gemini 2.5 Flash Lite at $0.100 in and $0.400 out and OpenAI GPT-4.1 Nano at $0.100 in and $0.400 out. The catalogue has no benchmark score for Nemotron 3.5 Content Safety, so this is a price ordering. It does not claim these answer as well.