First identify what is going wrong: Qwen3.8-27B may be showing a long thinking trace, giving an unnecessarily long final answer, repeating phrases, or failing to produce a final answer at all. These symptoms have different controls. For visible reasoning, try a lower reasoning effort or the instruct/non-thinking path; for repeated phrases, verify parameter support and test a presence-penalty change. Change one setting at a time and compare the same prompts.
Identify which kind of verbosity you’re seeing
Qwen’s model guidance says Qwen3.8 operates in thinking mode by default and identifies xhigh as the default reasoning effort. That can mean reasoning appears before the final response, depending on how your serving setup handles it. A long final answer, repeated wording, and an empty final response are separate symptoms—not one problem with one universal fix. Qwen’s Qwen3.8-27B model guidance
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- Visible thinking: A long
<think>...</think>section is being returned or displayed. - Overlong final answer: The final response is lengthy but does not loop or repeat the same phrases.
- Repetition: The final answer repeats words, phrases, or passages in a loop.
- Empty final answer: The response contains reasoning but no usable final content. Check the finish reason and returned fields before treating this as verbosity.
Where your endpoint exposes them, record the final-answer field, finish reason, token usage, and whether thinking content is preserved. That helps distinguish generation behavior from how your client displays or parses the response.
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For long thinking or overlong answers, change effort or mode
Try a lower reasoning effort
Qwen documents low, medium, and xhigh reasoning effort, with xhigh as the default. If a prompt does not need extensive deliberation, compare medium or low with your current setting. Lower effort may reduce reasoning depth and cost, but it may also be less suitable for complex tasks. Test on the kinds of prompts where answer quality matters to you.
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Use the instruct/non-thinking path for a direct response
Qwen also documents an instruct/non-thinking path for situations where you want a direct response rather than visible thinking content. This changes the requested behavior, so compare usefulness as well as length. Do not assume that hiding or disabling thinking will preserve the same analysis on tasks that depend on it.
Use the same prompt and serving endpoint for each comparison. If changing effort or mode has no effect, check whether your runtime supports and forwards that control.
Use Qwen’s sampling recommendations as a baseline
Qwen publishes different suggested sampling settings for thinking and instruct/non-thinking modes. These are starting points from the model documentation, not guaranteed optimal settings for every framework or workload.
| Mode | temperature | top_p | top_k | min_p | presence_penalty | repetition_penalty |
|---|---|---|---|---|---|---|
| Thinking | 1.0 | 0.95 | 20 | 0.0 | 0.0 | 1.0 |
| Instruct/non-thinking | 0.7 | 0.80 | 20 | 0.0 | 1.5 | 1.0 |
Apply the set that matches the mode you are using, then evaluate it on representative prompts. Avoid combining multiple changes before you know which one helped.
For repeated phrases, test presence penalty carefully
Qwen says that, in supported frameworks, presence_penalty can be adjusted from 0 to 2 to reduce endless repetition. Its model guidance also warns that higher values may cause language mixing and a slight decrease in performance. Start from the documented baseline for your mode and change this parameter modestly, on its own, while checking both repetition and answer quality.
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Qwen Cloud’s DashScope API reference documents an accepted presence-penalty range of -2 to 2 and lists 1.5 as the Qwen3.8 non-thinking default. These figures describe that API’s parameter range and default; they are not a universal setting for every local runtime or mode. DashScope API reference: chat parameters
Do not stack presence and repetition penalties blindly. Confirm which parameter your endpoint implements, what value it actually receives, and which mode-specific recommendation applies. A client library accepting a field does not by itself prove that the serving framework uses it.
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Check the runtime and prompt template
Qwen notes that inference-framework support varies and names vLLM, SGLang, and TokenSpeed as serving options, recommending current framework versions for compatibility. Consult the documentation for your exact endpoint or local runtime and inspect the effective generation configuration where available. Verify that the mode, effort, and sampling values you selected reach the model, and that your client handles thinking and final-answer fields as intended.
If the final answer is empty, inspect effort and finish details
A QwenLM GitHub issue dated 2026-08-19 reports empty final content with finish_reason: stop alongside repeated reasoning in one reporter’s Qwen3.8-27B setup. The reporter suggests comparing low or medium effort. They also describe a repetition-penalty workaround, but characterize the evidence as preliminary and limited. Treat those suggestions as troubleshooting leads, not as a confirmed fix or evidence of a general failure rate. QwenLM/Qwen3.8 issue #216
If you see this symptom, compare effort settings in the same setup and inspect whether the response contains separate reasoning and final fields. Record the finish reason and token usage for each call. The issue documents one reporter’s experiment, not how often this happens across users or deployments.
Quick Recap
Run a small before-and-after check
- Choose representative prompts. Include the prompts that produce the unwanted behavior, not just simple questions.
- Save a baseline. Record the mode, effort, sampling values, output fields, finish reason, and token usage where available.
- Change one setting. For example, lower effort without changing penalties, or adjust presence penalty without changing mode.
- Repeat the same prompts. Compare usefulness, answer length, phrase repetition, and whether a final answer is returned.
- Keep only changes that help. A single generation is not enough to show that a setting reliably fixes the issue.
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