How to use DeepSeek V4.1 Flash Free with OpenCode

OpenCode is an AI coding tool that reads project files and helps explain or edit code. Connect **DeepSeek V4.1 Flash Free** to request reviews without downloading its model files. OpenCode prepares the request and the hosted model generates the answer.

DeepSeek V4.1 Flash has publicly released weights under the MIT license. If hosting the large model is a significant commitment, its free API¹ offer provides a way to assess its answers first. Here we start by reviewing a short Python function that is safe to share.

As of October 16, 2026, OpenCode lists input, output and cache reads as free for DeepSeek V4.1 Flash Free. Check for the Free suffix in the model picker. The ordinary DeepSeek V4.1 Flash entry is a separate paid option.

This is a limited-time promotion. No end date or guaranteed per-minute or daily quota is published, so start with model evaluation rather than an unattended long-running job.

For a first installation, run node --version and npm --version in a terminal to check that Node.js and npm are available. Once both commands show a version, install OpenCode V2 with the command below. Existing OpenCode users should read the V2 installation and migration instructions first. Start in a separate folder containing a public sample rather than a private repository.

npm install -g @opencode/cli

Run opencode in the sample folder, then enter /connect. Choose the OpenCode pay-as-you-go provider and connect an API key issued in Console. Next, use /models to select DeepSeek V4.1 Flash Free. If the account screen requests payment or a top-up, check the free-access conditions before proceeding; do not purchase credits just to follow this example.

To start with the same model, set the model value below in the project's opencode.jsonc. Merge this field into existing configuration instead of overwriting the file. Check that the selected model still includes Free in a new session.

{
  "$schema": "https://opencode.ai/config.json",
  "model": "opencode/deepseek-v4.1-flash-free"
}

Save the function below as average.py in the sample folder. Before sending a question, select Plan through /agents to start by exploring without editing normal project files.

def average(values):
    return sum(values) / len(values)

Type @ in OpenCode to attach average.py, then ask: ‘Explain what happens with an empty list and how to fix it. Do not edit files or run commands.’ Reject shell-command requests for this exercise. In the response, look for the connection between an empty list having length zero and the resulting division by zero.

If the review is useful, request a proposed fix next. To let OpenCode apply it, switch to an agent that permits file edits and approve the change request. In a Git repository, inspect the changes with git diff; in a plain sample folder, compare the files before and after editing. Run tests with both empty and non-empty lists to check the result.

Check Auto-recharge rules under Console Settings → Billing and keep them off on an account used only for free evaluation. OpenCode may use other low-cost models to generate session titles. Review the model IDs and costs of both the main answer and auxiliary requests in usage history.

To isolate the request, call only the free model API directly as shown below. The example uses Python 3's standard library and prompts² for the key without echoing it. Save it as opencode-free-check.py and run python3 opencode-free-check.py. It makes one request without automatic retries or switching to a paid model.

import getpass
import json
import urllib.request

key = getpass.getpass('OpenCode API key: ')
payload = {
    'model': 'deepseek-v4.1-flash-free',
    'messages': [{'role': 'user', 'content':
        'Review this Python function for empty-list handling:\n'
        'def average(values):\n    return sum(values) / len(values)'}],
    'max_tokens': 2048,
}
request = urllib.request.Request(
    'https://opencode.ai/inference/openai/v1/chat/completions',
    data=json.dumps(payload).encode(),
    headers={'Authorization': 'Bearer ' + key,
             'Content-Type': 'application/json'},
)
with urllib.request.urlopen(request, timeout=120) as response:
    result = json.load(response)
choice = result['choices'][0]
print(choice['message'].get('content') or '(empty content)')
print('finish_reason:', choice.get('finish_reason'))

In a normal response, review text is returned in choices[0].message.content. If finish_reason is length or the answer is empty, reasoning may have exhausted the output budget; try a shorter input. For authentication errors, check the key and account. For limit errors, check the free entry's availability and retry guidance.

The provider behind the free DeepSeek entry states a zero-retention policy and no use of request data for model training. The code is still sent to a hosted service, so begin with public samples containing no secrets or customer data. Other free entries, including MiMo and NVIDIA models, have different data terms; review those when switching models.

For occasional reviews of public projects, this free route is a useful place to start. If private material must stay on your machine or you want to run on your own hardware without a provider quota, continue with the local agent starter guide. The free open-weight service comparison brings together other providers' limits and connection methods.