DeepSeek V4.1 Flash JSON Output vs Sume output_schema: what differs

The two do different jobs. DeepSeek's JSON Output mode asks the model to return valid JSON, and the page does not describe schema enforcement. A Sume output_schema on an Agent Completion or Format run is checked: you get an object that fits it, or output is null and output_error says why. Use DeepSeek V4.1 Flash for the first kind of work, such as cheap extraction that you validate yourself, and use the Sume schema when a run's result feeds code.

Side by side

The table sets the guarantees side by side. The Sume column comes from the structured output docs. The DeepSeek column comes from the vendor page that was read on the date in the caption.

A validation habit that works for both

If you call DeepSeek for a step inside your own code, validate its JSON with a schema library, and treat a failure as a retry or a skip. If the step is a Sume run, put the contract in the request and read output_error on a miss.

import json

REQUIRED = {"team": str, "urgent": bool}


def parse(raw: str) -> dict:
    obj = json.loads(raw)
    for key, typ in REQUIRED.items():
        if not isinstance(obj.get(key), typ):
            raise ValueError(f"bad field: {key}")
    return obj


print(parse('{"team": "billing", "urgent": true}'))
try:
    parse('{"team": "billing"}')
except ValueError as e:
    print("rejected:", e)

Check the docs before you ship

Sume's limits and field names change faster than blog posts do. Read the linked docs pages for the current request fields before you ship, and send a dry_run or a low spend cap on your first real call.