Updated 2026-10-13
DeepSeek Temperature Parameter Guide: use the official range for the actual task
Check the mode before tuning temperature: DeepSeek enables thinking by default, and thinking mode ignores this parameter without an error. The recommendations below apply to non-thinking requests. DeepSeek's official page is more concrete: it gives a default of `1.0` and then publishes recommended values for coding, math, data analysis, conversation, translation, and creative writing. That makes temperature a support topic with a real first-party baseline rather than endless folklore.
1. Start from DeepSeek's official default, not from another provider's habit
For non-thinking requests, DeepSeek's official parameter page says the default `temperature` value is `1.0`. That is the baseline to remember before you start cargo-culting `0`, `0.2`, or `1.5` from unrelated tutorials.
To tune temperature, explicitly disable thinking with the request field `thinking: { type: "disabled" }`. Keep thinking enabled when your task needs reasoning, and do not expect temperature changes to affect that mode.
The more useful interpretation is practical: if a workload already behaves well at the default, you do not need to change it just because a community thread says every coding model should be colder by default.
Sources
- DeepSeek official Thinking Mode guide - Thinking is enabled by default and ignores temperature; disable thinking to use this sampling control.
- DeepSeek official Temperature Parameter page - Primary source for the default value and official per-task recommendations.
2. Use the official task table before inventing your own scale
DeepSeek does not leave the reader guessing. The official table recommends `0.0` for coding and math, `1.0` for data cleaning and data analysis, `1.3` for general conversation, `1.3` again for translation, and `1.5` for creative writing or poetry.
That table is useful because it separates deterministic workloads from expressive ones. A coding patch, SQL fix, or numeric derivation usually benefits from lower variance, while translation and open conversation can tolerate more variation without becoming wrong by definition.
| Use case | Temperature | Why it fits |
|---|---|---|
| Coding / Math | 0.0 | Reduce variation; does not guarantee determinism |
| Data Cleaning / Data Analysis | 1.0 | Use the platform default |
| General Conversation | 1.3 | Allow more natural variation |
| Translation | 1.3 | Balance fluency with consistency |
| Creative Writing / Poetry | 1.5 | Allow the widest stylistic variation |
3. For coding workflows, keep temperature at 0.0 until you have a reason not to
For non-thinking coding and math, DeepSeek recommends `0.0`. This reduces sampling variation but does not guarantee identical or correct output. That makes it the clean default for bug fixes, code transforms, test generation, and bounded agent steps where drift is more expensive than personality.
If your next problem is schema discipline rather than sampling variance, pair this with `/guides/deepseek-json-output-guide` or `/guides/deepseek-thinking-mode-tool-calls`. Temperature does not replace those contracts.
{
"model": "deepseek-v4-pro",
"messages": [
{ "role": "user", "content": "Refactor this SQL query without changing behavior." }
],
"thinking": { "type": "disabled" },
"temperature": 0.0
}4. Use 1.3 for translation and conversation only when variation helps
DeepSeek's own table groups general conversation and translation at `1.3`. That does not mean every production translation pipeline should run loose forever. It means the official baseline allows more fluency than strict coding routes do.
If your translation or chat workflow starts drifting too much, bring the prompt under tighter structural control first and then decide whether the task truly needs the warmer setting. Temperature is one lever, not the whole reliability story.
5. Treat 1.5 as a creative-writing lane, not as a universal upgrade
The highest official recommendation on the page is `1.5`, and DeepSeek reserves it for creative writing and poetry. That is a narrow endorsement, not a sign that every app should 'sound more human' by turning the knob up.
For buyer and support pages, the safer pattern is to keep utilitarian routes cold and reserve high-temperature settings for content ideation, fiction, slogan exploration, and other tasks where novelty is the point rather than a side effect.
If your real problem is prompt size or budget rather than sampling style, continue with `/guides/deepseek-v4-pricing-per-million-tokens` or `/guides/deepseek-context-caching-hit-rules` instead of adjusting temperature blindly.
FAQ
What is the default DeepSeek temperature?
The documented default is `1.0` for non-thinking requests. Thinking mode is enabled by default and ignores temperature.
What temperature does DeepSeek recommend for coding?
For non-thinking requests, DeepSeek recommends `0.0` for coding and math. Thinking mode ignores temperature.
What temperature does DeepSeek recommend for translation?
DeepSeek's official table lists `1.3` for translation in non-thinking mode.
Should I use 1.5 for every DeepSeek task?
No. DeepSeek reserves `1.5` for creative writing and poetry, not for general coding or production support flows.
Does changing temperature create a new DeepSeek product on /pricing?
No. Temperature is an API request parameter only. It does not imply a new stocked plan card or inventory change.
First check the mode: thinking requests ignore temperature. For non-thinking requests, keep coding and math at `0.0`, trust `1.0` as the default, move to `1.3` when fluency matters, and reserve `1.5` for genuinely creative tasks instead of treating warmth as a universal quality boost.
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