Hey folks! 👋

As someone who loves tinkering with AI tools and keeping up with the LLM space, I recently found myself comparing two models that have been getting a lot of attention: DeepSeek-V3 and Claude 3.5 Sonnet.

They’re both incredibly powerful in different ways — one is open-source and cost-efficient, and the other is closed but insanely capable. So I decided to dig into how they actually perform, how much they cost, and which one might make more sense depending on your use case.

Here’s what I found 👇

🔍 Quick Intro to Both Models

Let’s start with a quick overview of the two:

*🤖 DeepSeek-V3
*

  • Open-source MoE (Mixture-of-Experts) model
  • 671B total parameters, 37B active per token
  • Trained on 14.8T tokens
  • Supports a 128K context window
  • Available on HuggingFace, RedPill, and DeepSeek’s own API

What stood out to me: it’s fast, surprisingly capable for the price, and best of all — completely open.

*🧠 Claude 3.5 Sonnet
*

  • Anthropic’s latest general-purpose model (launched June 2024)
  • Supports up to 200K tokens context window
  • Extremely strong at reasoning, tool use, and especially code generation
  • Available via Anthropic API, RedPill, Amazon Bedrock, and Google Cloud

In my experience, Claude is one of the most powerful models I’ve used — but it comes with a cost.

💸 Cost Comparison (Brace Yourself)

This is where the contrast really shows:

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😳 Yeah… Claude is ~43x more expensive than DeepSeek in terms of output tokens. So if you're building something at scale, price will definitely factor into your decision.

🧪 Benchmarks Breakdown

Here’s what the current benchmarks say (I pulled from a few public sources like LMSYS, OpenCompass, and their docs):

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Takeaways:

Claude consistently wins on complex reasoning and coding tasks.

DeepSeek holds up surprisingly well, especially given how affordable it is.

I’ve personally used Claude for agent workflows and technical writing assistants — it’s brilliant. But for summarization or general-purpose tasks where cost matters? DeepSeek is a killer value.

🔧 So... Which One Do I Use?

Here’s how I break it down:

Use Claude 3.5 Sonnet if:

  • You need top-tier performance in reasoning, math, or code.
  • You’re working on a production-grade assistant or tool that needs reliability.
  • You don’t mind paying more for the best.

Use DeepSeek-V3 if:

  • You’re building a cost-sensitive project or prototype.
  • You want more control (fine-tuning, self-hosting, etc.).
  • You’re looking for good-enough output at a fraction of the price.

Honestly, I use both depending on the task.

🧰 How I Use Them Without Switching APIs

Instead of managing different APIs and auth keys, I usually go through a platform I like called RedPill.

It’s a smart API router that lets me access Claude, DeepSeek, GPT-4o, Mixtral, and a bunch of other models — all through a single unified endpoint. Really handy when I’m experimenting or shipping small tools.

They also have this model called redpill/auto, which is basically an Auto Router — I just set that as the model name, and RedPill automatically chooses the best model based on task type, speed, and price.

Here’s a sample call using JavaScript:

fetch("https://api.redpill.ai/v1/chat/completions", {
  method: "POST",
  headers: {
    "Authorization": "Bearer ",
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    "model": "redpill/auto",
    "messages": [
      {
        "role": "user",
        "content": "What is the meaning of life?"
      }
    ]
  })
})

Want to use Python or Shell instead? You’ll find examples on the model page here.

Pretty neat.

*🔚 Final Thoughts
*
Both Claude and DeepSeek are great in their own ways. One gives you cutting-edge performance, the other gives you flexibility and affordability.

I love seeing open models like DeepSeek raise the bar — and I love that I don’t have to pick just one anymore.

If you’re exploring LLMs for your next project, I’d definitely recommend trying both. You might be surprised how far $0.28/million tokens can get you.

Thanks for reading! If you're also playing around with AI tools and models, I’d love to hear what you're building or experimenting with. Drop a comment or connect :)