nvidia/llama-3.3-nemotron-super-49b-v1.5

$0.10

Input / 1M

$0.40

Output / 1M

131K

Context

—

Speed

Capabilities

json_modetools

Use llama-3.3-nemotron-super-49b-v1.5 via Relay

Configure the model alias in YAML, then call it from Python.

YAML

# models.yaml
version: 1
models:
  llama:
    target: nvidia/llama-3.3-nemotron-super-49b-v1.5
    credential: $env.NVIDIA_API_KEY

Python

from relay import Hub

async with Hub.from_yaml("models.yaml") as hub:
    resp = await hub.chat(
        "llama",
        messages=[{"role": "user", "content": "Hello"}],
    )
    print(resp.text, resp.cost_usd)

pip install ai5labs-relay · full docs on GitHub

Compare with

vs groq/llama-3.3-70b-versatile vs anthropic/claude-haiku-4-5 vs mistral/mistral-large-latest vs openai/gpt-4o-mini