DeepSeek Harness

Run DeepSeek Harness on our endpoint.

If you are wiring up an agent harness, the endpoint is a configuration value. For most harnesses that is one line to change, and we handle everything commercial around it.

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Why this is usually a config change, not a migration

A harness is the scaffolding around a model: the loop that calls tools, keeps state, retries, and decides when it is done. It is real engineering, and it is the part you should not have to rewrite. The model endpoint underneath it is a configuration value.

Harnesses built on the OpenAI-compatible request shape take a base URL and a key. Point both at us and the harness keeps working — same tools, same prompts, same loop. If your harness is built around a different provider's native SDK, tell us and we will be honest about whether this is a five-minute change or a real project.

What to check before you switch

Request shape

Chat-completions with tool calling and streaming. If your harness speaks that, the change is a base URL.

  • OpenAI-compatible
  • Tool calling
  • Streaming

Context budget

1M tokens of context and up to 384K of output. Agent loops accumulate context fast — this is usually more headroom than you need.

  • 1M context
  • 384K output

Cost of the loop

Agent loops re-send a growing prefix on every step. Prompt caching is what keeps that affordable, and it is usually the first thing we look at with you.

  • Caching
  • Off-peak for batch

Before you commit

Ask us for a limited key and run your real harness against it. Testing on your own workload beats any benchmark we could show you.

  • Trial key
  • Your own workload

Questions from people wiring up harnesses

Does tool calling work?

Yes — tool calling and streaming are part of the chat-completions shape, and the official SDKs work unchanged. If your harness has a provider abstraction, add us as another provider.

Is there a DeepSeek Harness on GitHub?

There are open-source harnesses on GitHub; we are not one of them. We are the endpoint a harness points at, not the harness itself — so if you found yours in a repository, the change is in its config rather than its code: base URL and API key, then run it against your own workload.

Will long agent runs hit a limit?

Concurrency on Flash goes up to 2,500, and context is 1M tokens. Very long autonomous runs are usually limited by your own timeout budget rather than the API. Tell us your peak concurrency and we will confirm what we can commit to in writing.

Can we run some traffic through you and some direct?

Yes, and it is a sensible way to start. Keep your direct account configured, send a share of traffic to us, and compare on your own numbers.

Is the harness supported by you, or by DeepSeek?

The harness is yours and the model is DeepSeek's — we provide the endpoint and the commercial relationship. If something breaks, you have a named contact rather than a ticket queue, and we will help you work out which layer is at fault.

What if we need a different model later?

We serve DeepSeek V4.1 Flash and V4.1 Pro. If your harness needs a different family entirely, we are not the right provider and we will say so.

WE HANDLEYOU DO

Diagram of the flow: three stages connected by arrows, with the middle stage highlighted.

  1. 1

    Tell us your volume

    Monthly token usage, and what you are running today. If we cannot beat your current cost, we say so.

    • Quote
    • Contract
    • Invoice

  2. 2

    We quote and contract

    A named account contact, a negotiable agreement, an invoice.

    - base_url="…"
+ base_url="…"
# nothing else changes

  3. 3

    You change one line

    Point your existing client at our endpoint. Keep a fallback.

The harness stays. One configuration value changes.Diagram of the onboarding sequence. Not a screenshot.

Tell us what you're running.

Send us your monthly volume and what you use today. We usually reply within one business day with a price and a named contact.

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