nvidia/llama-3.3-nemotron-super-49b-v1.5
Ngày phát hành: 2025-10-10
131,072 context · $0.10/M input tokens · $0.40/M output tokens
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...
Pay-per-use
No upfront costs, pay only for what you use
Use the following code examples to integrate with our API:
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="nvidia/llama-3.3-nemotron-super-49b-v1.5",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)nvidia llama-3.3-nemotron-super-49b-v1.5
| Specification | Value |
|---|---|
| Provider | Nvidia |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 131072 tokens |
| Max Output | 4096 tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $0.1 |
| Output | $0.4 |
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: nvidia/llama-3.3-nemotron-super-49b-v1.5
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="nvidia/llama-3.3-nemotron-super-49b-v1.5",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "nvidia/llama-3.3-nemotron-super-49b-v1.5",
"messages": [{"role": "user", "content": "Hello!"}]
}'nvidia/llama-3.3-nemotron-super-49b-v1.5
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...
Input
$0.1 /M
Output
$0.4 /M
Context
131K
Max Output
4K
Tool Use
Supported
Access Llama 3.3 Nemotron Super 49b V1.5 through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Pricing on WaveSpeedAI: $0.10 per million input tokens and $0.40 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.
Llama 3.3 Nemotron Super 49b V1.5 supports up to 131K tokens of context with up to 4K tokens of output per request.
Yes. WaveSpeedAI exposes Llama 3.3 Nemotron Super 49b V1.5 through an OpenAI-compatible endpoint at https://llm.wavespeed.ai/v1. Point the official OpenAI SDK at this base URL with your WaveSpeedAI API key — no other code changes required.
Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with model id set to the value shown above. New accounts receive free credits to evaluate Llama 3.3 Nemotron Super 49b V1.5 before paying per token.