Skip to content
OpenKey

Llama 3.3 Nemotron Super 49B V1.5

NVIDIAReleased Oct 10, 2025

Llama-3.3-Nemotron-Super-49B-v1.5 is a 49B-parameter, English-centric reasoning/chat model derived from Meta’s Llama-3.3-70B-Instruct with a 128K context. It’s post-trained for agentic workflows (RAG, tool calling) via SFT across math, code, science, and...

Try in playground
Context window
131K tokens
Max output
16K tokens
Input
text
Output
text
Tokenizer
Llama3
Knowledge cutoff
Mar 31, 2024
Released
Oct 10, 2025
Reasoning
optional

Pricing

Per 1M tokens. The provider price and our flat 3% fee are separate columns — what you pay is their sum.

Per 1M tokensProvider+ 3% feeYou pay
Input$0.400$0.012$0.412
Output$0.400$0.012$0.412

Supported parameters

  • frequency_penalty
  • include_reasoning
  • logit_bias
  • max_tokens
  • min_p
  • presence_penalty
  • reasoning
  • repetition_penalty
  • response_format
  • seed
  • stop
  • temperature
  • tool_choice
  • tools
  • top_k
  • top_p

Call it

OpenAI-compatible: point your SDK at api.openkey.ai/v1 and use model nvidia/llama-3.3-nemotron-super-49b-v1.5.

Code sample language
curl https://api.openkey.ai/v1/chat/completions \
  -H "Authorization: Bearer $OPENKEY_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "nvidia/llama-3.3-nemotron-super-49b-v1.5",
    "messages": [{"role": "user", "content": "Hello"}]
  }'
import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.openkey.ai/v1",
    api_key=os.environ["OPENKEY_API_KEY"],
)

completion = client.chat.completions.create(
    model="nvidia/llama-3.3-nemotron-super-49b-v1.5",
    messages=[{"role": "user", "content": "Hello"}],
)
print(completion.choices[0].message.content)
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.openkey.ai/v1",
  apiKey: process.env.OPENKEY_API_KEY,
});

const completion = await client.chat.completions.create({
  model: "nvidia/llama-3.3-nemotron-super-49b-v1.5",
  messages: [{ role: "user", content: "Hello" }],
});
console.log(completion.choices[0].message.content);

Questions

How much does Llama 3.3 Nemotron Super 49B V1.5 cost via API?
Through OpenKey, Llama 3.3 Nemotron Super 49B V1.5 costs $0.412 per 1M input tokens and $0.412 per 1M output tokens. That is the provider price ($0.400 / $0.400) plus a flat 3% fee — nothing else.
What is Llama 3.3 Nemotron Super 49B V1.5's context window?
Llama 3.3 Nemotron Super 49B V1.5 accepts up to 131K tokens of context and returns up to 16K tokens per request.
Is Llama 3.3 Nemotron Super 49B V1.5 OpenAI-compatible?
Yes. Send requests to OpenKey's /v1/chat/completions endpoint with model "nvidia/llama-3.3-nemotron-super-49b-v1.5" using any OpenAI SDK — only the base URL and API key change.
What inputs does Llama 3.3 Nemotron Super 49B V1.5 support?
Llama 3.3 Nemotron Super 49B V1.5 accepts text input and produces text output. Its knowledge cutoff is Mar 31, 2024.

More from NVIDIA

All NVIDIA models →