🔥 Qwen/Qwen3-32B
High-performance 32B parameter LLM. Excellent for reasoning, coding, and multilingual tasks.
Input: $0.15/M tokensOutput: $0.44/M tokens
33.54M runs in 7 days
Meta's most capable 70B model with 128K context, competing with models 5x its size.
Parameters
70B
Context
128,000 tokens
Organization
Meta
Start using Llama 3.3 70B in minutes. VoltageGPU provides an OpenAI-compatible API — just change the base_url.
from openai import OpenAI
client = OpenAI(
base_url="https://api.voltagegpu.com/v1",
api_key="YOUR_VOLTAGE_API_KEY"
)
response = client.chat.completions.create(
model="meta-llama/Llama-3.3-70B-Instruct",
messages=[
{"role": "system", "content": "You are a senior software engineer."},
{"role": "user", "content": "Review this code and suggest improvements:\n\ndef fib(n):\n if n <= 1: return n\n return fib(n-1) + fib(n-2)"}
],
max_tokens=2048,
temperature=0.3
)
print(response.choices[0].message.content)curl -X POST https://api.voltagegpu.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_VOLTAGE_API_KEY" \
-d '{
"model": "meta-llama/Llama-3.3-70B-Instruct",
"messages": [
{"role": "system", "content": "You are a senior software engineer."},
{"role": "user", "content": "Review this code and suggest improvements."}
],
"max_tokens": 2048,
"temperature": 0.3
}'| Component | Price | Unit |
|---|---|---|
| Input tokens | $0.7 | per 1M tokens |
| Output tokens | $0.9 | per 1M tokens |
New accounts receive $5 free credit. No credit card required to start.
Llama 3.3 70B achieves strong results across benchmarks: MMLU (86.0%), HumanEval (88.4%), MATH (77.0%), and GSM8K (91.1%). It supports tool use, structured output (JSON mode), and multilingual generation in English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai. With 128K context it can process entire codebases and long documents.
Llama 3.3 70B is Meta's most capable open-weight model in the 70B parameter class. It delivers performance competitive with much larger models including Llama 3.1 405B on many tasks. Built on Meta's latest Llama 3 architecture with grouped query attention (GQA), it supports a 128K context window and excels at instruction following, reasoning, coding, and multilingual tasks. The model was trained on over 15 trillion tokens of publicly available data and fine-tuned with RLHF for safe and helpful responses.
Deploy production-grade conversational AI with strong safety guarantees and instruction following.
Generate, review, and debug code across multiple languages with high accuracy.
Summarize, extract information from, and analyze long documents with 128K context.
Build applications serving users in 8+ languages with native-quality generation.
Use as the generation component in Retrieval-Augmented Generation for knowledge-grounded responses.
https://api.voltagegpu.com/v1/chat/completions| Authorization | Bearer YOUR_VOLTAGE_API_KEY | Required |
| Content-Type | application/json | Required |
meta-llama/Llama-3.3-70B-InstructUse this value as the model parameter in your API requests.
curl -X POST https://api.voltagegpu.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_VOLTAGE_API_KEY" \
-d '{
"model": "meta-llama/Llama-3.3-70B-Instruct",
"messages": [
{"role": "system", "content": "You are a senior software engineer."},
{"role": "user", "content": "Review this code and suggest improvements."}
],
"max_tokens": 2048,
"temperature": 0.3
}'Recommended GPU for large models requiring high VRAM and memory bandwidth.
Best performance for large model inference with HBM3 memory.
Access this model and 140+ others through our OpenAI-compatible API.
Compare GPU cloud pricing and model hosting features.
View GPU compute and AI inference pricing with no hidden fees.
Deploy a GPU pod in under 60 seconds to run models locally.
Llama 3.3 70B matches the performance of Llama 3.1 405B on many benchmarks while being significantly cheaper and faster to run. On MMLU it scores 86.0% vs 405B's 88.6%. For most practical use cases, the 70B model provides excellent quality at much lower cost.
Llama 3.3 70B is released under Meta's Llama 3.3 Community License, which allows commercial use for companies with fewer than 700 million monthly active users. Through VoltageGPU's API, you can use it immediately at $0.70/M input tokens with no licensing concerns.
Llama 3.3 70B supports a 128,000 token context window, allowing it to process approximately 96,000 words or 300 pages of text in a single request.
Yes, Llama 3.3 70B supports tool use and function calling through the VoltageGPU API. You can define tools using the standard OpenAI function calling format.
Get $5 free credit when you sign up. No credit card required. Deploy in under 30 seconds with our OpenAI-compatible API.