DeepSeek V3-0324 Live on Lambda!

A Fresh Take on AI Endpoints

The DeepSeek V3-0324 endpoint is here and it’s just an API key away with lightning fast responses, and up to 128K massive context window. With this endpoint, AI developers have access to a 685B parameter model with no rate limiting and for the low price of $0.88 per 164K output. 

DeepSeek V3-0324 highlights:

• Major Boost in Reasoning performance
• 685B total parameters (671B Main Model weights plus 14B Multi-Token Prediction Module weights) using a Mixture-of-Experts (MoE) design
• Stronger front-end development skills
• Smarter tool-use capabilities
• Trained on 14.8 trillion tokens, using an auxiliary-loss-free load balancing strategy and multi-token prediction (MTP)

So..How Good Is It? 

In structured reasoning and creative tasks, DeepSeek V3-0324 isn’t “close enough”, it’s better than most closed models on a lot of the benchmarks that actually matter in the wild.

Here’s what DeepSeek V3-0324 is able to pull off:

• MATH-500: A whooping 94%, higher than GPT-4.5 and Claude-Sonnet-3.7
• Massive Multitask Language Understanding(MMLU Pro): 81.2%, higher than DeepSeek v3 and Qwen-Max.
• GPQA Diamond: 68.4%, which is 13% higher than Qwen-Max
• AIME: 59.4% (top-tier math reasoning)
• LiveCodeBench: 49.2% massive jump from DeepSeek V3, GPT-4.5 and Claude-Sonnet-3.7

Put it to work yourself 

It’s easy to get started with DeepSeek v3-0324 on the Lambda Inference API. So whether you’re a CLI master or a VS code crusader, integrating is trivial:

1. Generate your API key
2. Choose your endpoint:
   • /completions - for single-prompt responses
   • /chat/completions - for multi-turn conversations
3. Call it from your favorite language

VS Code Quickstart(Python example)

Step 1:

# 1. Create and activate a virtual environment
python3 -m venv venv && source venv/bin/activate

# 2. Install OpenAI library
pip install openai

Step 2:

from openai import OpenAI


client = OpenAI(
 api_key="YOUR_API_KEY",
 base_url="https://api.lambda.ai/v1"
)


chat = client.chat.completions.create(
 model="deepseek-v3-0324",
 messages=[
 {"role": "system", "content": "You're an expert conversationalist."},
 {"role": "user", "content": "Who won the World Series in 2020?"},
 {"role": "assistant", "content": "The Los Angeles Dodgers."},
 {"role": "user", "content": "Where was it played?"}
 ]
)

print(chat.choices[0].message.content)

For detailed information, check out our Documentation. 

Ready to Break Free from Rate Limits? 

Tired of hitting ceilings with closed APIs and capped usage? DeepSeek V3‑0324 on Lambda gives you the freedom to build, experiment and scale without artificial limitations.

No rate limits. No throttling. No fine print.
You get full access to state-of-the-art, open-source models, ready for everything from rapid prototyping to production-grade deployments.