🔥 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
High-performance general-purpose LLM with MoE architecture, comparable to GPT-4o at 95% lower cost.
Parameters
685B (MoE, 37B active)
Context
128,000 tokens
Organization
DeepSeek
Start using DeepSeek V3 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="deepseek-ai/DeepSeek-V3",
messages=[
{"role": "system", "content": "You are a helpful coding assistant."},
{"role": "user", "content": "Write a Python function to find the longest palindromic substring."}
],
max_tokens=2048,
temperature=0.7
)
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": "deepseek-ai/DeepSeek-V3",
"messages": [
{"role": "system", "content": "You are a helpful coding assistant."},
{"role": "user", "content": "Write a Python function to find the longest palindromic substring."}
],
"max_tokens": 2048,
"temperature": 0.7
}'| Component | Price | Unit |
|---|---|---|
| Input tokens | $0.1 | per 1M tokens |
| Output tokens | $0.2 | per 1M tokens |
New accounts receive $5 free credit. No credit card required to start.
DeepSeek V3 excels across a wide range of benchmarks: MMLU (88.5%), MATH-500 (90.2%), HumanEval (82.6%), and GPQA (59.1%). It supports multi-turn conversations, tool use, function calling, and JSON mode. The MoE architecture activates only 37B of the total 685B parameters per token, enabling fast inference while maintaining the quality of much larger dense models.
DeepSeek V3 is a powerful general-purpose language model featuring 685 billion total parameters in a Mixture-of-Experts (MoE) architecture with 37 billion active parameters. Developed by DeepSeek, it delivers exceptional performance across coding, math, reasoning, and general knowledge tasks. V3 uses Multi-head Latent Attention (MLA) and DeepSeekMoE for efficient inference, achieving performance comparable to GPT-4o and Claude 3.5 Sonnet at a fraction of the cost. The model was trained on 14.8 trillion tokens with innovative FP8 mixed-precision training.
Build chatbots and conversational AI with broad knowledge and strong instruction following.
Generate, complete, and refactor code across 50+ programming languages with high accuracy.
Write articles, marketing copy, emails, and creative content with nuanced language.
Analyze datasets, generate insights, create SQL queries, and process structured data.
Translate between languages and process multilingual content with high fidelity.
https://api.voltagegpu.com/v1/chat/completions| Authorization | Bearer YOUR_VOLTAGE_API_KEY | Required |
| Content-Type | application/json | Required |
deepseek-ai/DeepSeek-V3Use 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": "deepseek-ai/DeepSeek-V3",
"messages": [
{"role": "system", "content": "You are a helpful coding assistant."},
{"role": "user", "content": "Write a Python function to find the longest palindromic substring."}
],
"max_tokens": 2048,
"temperature": 0.7
}'Great price-performance for smaller models with 24GB VRAM.
Enterprise-grade GPU for production inference at scale.
Access this model and 140+ others through our OpenAI-compatible API.
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DeepSeek V3 achieves comparable performance to GPT-4o on most benchmarks while costing $0.10/M input tokens versus GPT-4o's $2.50/M. On MMLU it scores 88.5% (GPT-4o: 88.7%), and on HumanEval for coding it scores 82.6% (GPT-4o: 90.2%). For most production use cases, V3 provides excellent quality at 95% lower cost.
Mixture-of-Experts (MoE) is an architecture where only a subset of the model's parameters are activated for each token. DeepSeek V3 has 685B total parameters but only activates 37B per token, giving it the knowledge capacity of a massive model with the inference speed of a much smaller one.
Yes, DeepSeek V3 supports OpenAI-compatible function calling and tool use through the VoltageGPU API. You can define tools in the standard OpenAI format and the model will generate appropriate function calls based on user queries.
DeepSeek V3 supports English, Chinese, and many other languages. It was trained on a diverse multilingual corpus and performs well for translation, multilingual content generation, and cross-lingual tasks.
Get $5 free credit when you sign up. No credit card required. Deploy in under 30 seconds with our OpenAI-compatible API.