DigitalOcean Gradient Review: Pricing & Comparison

For developers already on DigitalOcean

DigitalOcean holds a distinct place in the developer community: not the full-featured enterprise version of AWS, nor the academic-research version of GCP, but a clean cloud platform built for independent developers and small teams. Droplets, Spaces, Managed Databases — every product is designed around “quick to get started, well documented, transparent pricing.”

Gradient is DigitalOcean’s AI inference product, and it carries that same style forward: focused on open-source model inference, compatible with the OpenAI API format, billed by usage, no minimum spend.

How to connect

DigitalOcean Gradient is fully compatible with the OpenAI SDK format — you just need to swap the base_url:

from openai import OpenAI

client = OpenAI(
    api_key="your DigitalOcean API token",
    base_url="https://inference.do-ai.run/v1"
)

response = client.chat.completions.create(
    model="llama-4-scout-17b-16e-instruct",
    messages=[
        {"role": "system", "content": "You are a helpful assistant"},
        {"role": "user", "content": "Explain what a vector database is"}
    ],
    max_tokens=500
)

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

Working alongside DigitalOcean infrastructure

Gradient has one practical advantage: if you’re already running application servers on DigitalOcean, your AI calls and your app live in the same account ecosystem:

• Unified billing: AI-call charges are consolidated with your Droplet/bandwidth charges, simplifying financial management
• Intra-network latency: calling the Gradient API from inside a DO data center has lower latency than a cross-cloud call
• The same API token: your DO personal access token works for both Gradient AI and DO infrastructure APIs

For projects already built on DigitalOcean’s backend that want to add AI features, Gradient is the path of least resistance for integration.

Open-source model coverage

Gradient currently mainly supports:

• The Llama series: Meta’s various Llama generations, from Llama 3 through Llama 4
• The Mistral series: Mistral 7B, Mixtral, and more
• Code models: Code Llama and other programming-specialized models
• The Phi series: Microsoft’s small, efficient models

Coverage isn’t as broad as DeepInfra’s 200+ models or Together AI, but the commonly used mainstream open-source models are essentially all there.

Who it fits

Gradient is especially well suited to developers already using DigitalOcean who want to add AI features to an existing project without setting up a separate account system and payment method just for that.

If you’re choosing an open-source model inference platform from scratch, Gradient is also worth putting on your comparison list — its developer experience and documentation quality are top-tier among comparable platforms.

Information verified 2026-07-04. Model list and pricing reflect the current DigitalOcean Gradient website at time of writing.

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