Chinese Output Stability Guide

Target audience: Developers Last updated: 2026-08-06

deepseek-v4-flash and kimi-k3 may occasionally mix in non-target languages when processing code, logs, or multilingual materials. Below are several configuration approaches to improve stability.

Symptoms

When handling code explanations, log analysis, long-context conversations, or mixed-language materials, models may exhibit the following behaviors:

• Chinese responses interspersed with unnecessary foreign language text;
• Explanations not rendered in Simplified Chinese;
• Continuing in the log's original language after quoting raw log content;
• Gradually drifting away from the initial language requirement over long conversations.

These issues are typically related to context content, prompt constraints, and sampling parameters. The platform is responsible for unified access, routing, billing, and stability assurance, and does not actively alter model output.

How to Improve Chinese Output Stability

1. Specify the Language Requirement in Your System Prompt

You must always respond in standard Simplified Chinese.
Code, commands, variable names, function names, and necessary error messages may be kept in their original language;
explanations, analyses, summaries, and procedural steps must be in Simplified Chinese.

2. Add Output Boundaries Based on Your Use Case

Customer service, knowledge base, and internal assistant scenarios often require restricting the scope of responses. You can include these boundaries in your system prompt:

Only answer questions covered by the knowledge base. When encountering information
that cannot be confirmed, explicitly state that it cannot be confirmed rather than
fabricating facts. For questions involving accounts, fees, or business decisions,
direct the user to contact human support.

For user-facing services, you can add keyword checks, risk classification, and human handoff after model output, rather than relying solely on prompts.

3. Lower Randomness

When stable responses are needed, set temperature to a lower value:

{
  "model": "deepseek-v4-flash",
  "temperature": 0.2
}

Refer to the model and API documentation for the specific supported parameter ranges.

4. Use Code Blocks to Isolate Raw Materials

Please explain the following log in Simplified Chinese without rewriting the original log content:
 
```text
Error: connection timeout when requesting model endpoint
```

Placing logs, code, JSON, and foreign-language materials inside code blocks helps the model distinguish between raw materials and the Chinese explanation requirement.

5. Periodically Restate Constraints in Long Conversations

Long contexts may dilute earlier prompt instructions. You can add a reminder before starting a new phase of the task:

Continue responding in Simplified Chinese. Code and proper nouns may remain in their original language; all other content must not switch languages.

6. Apply Programmatic Validation to Output

For production systems, consider adding:

• Non-Chinese character ratio detection;
• Sensitive and personally identifiable information detection;
• Illegal or non-compliant content detection;
• Business-specific keyword and prompt phrase checks;
• Output truncation, retry, and manual review strategies;
• Necessary request and processing logs.

Model Selection Recommendations

Model capabilities, pricing, and available groups are subject to change. Always refer to the console's "Model Plaza" and "Call Guide" for the latest information.

Input and Log Handling

The content sent to the model also affects output quality. Before sending a request, you can remove irrelevant fields and redact sensitive information such as API keys, phone numbers, and ID numbers. Request logs should retain only the fields necessary for troubleshooting, with access permissions and retention periods following your organization's existing data management policies.

For specialized domains such as healthcare, finance, and law, model responses should not be used as final conclusions. Consider adding professional review as part of your workflow.

What to Do When Non-Target Language Appears

1. Append an explicit Simplified Chinese constraint and retry;
2. Remove mixed-language context unrelated to the task;
3. Lower temperature;
4. Start a new session and re-execute;
5. Switch between deepseek-v4-flash and kimi-k3 for comparative testing;
6. If the issue occurs frequently, retain the redacted request ID, model name, and timestamp, then contact the platform's technical support.