The problem

n8n's DeepSeek chat node has no parameter to control thinking effort. Every call runs at the server default, whether the task is a one word classification or a multi step analysis.

This node fixes that.

The fix

Same node, plus a Thinking Level dropdown sent as reasoning_effort.

| Setting | Sent as | Behaviour | |---|---|---| | API Default | (omitted) | Server decides | | None | none | Thinking off, fastest and cheapest | | Low / Medium | low / medium | Normalised to high | | High | high | Default thinking effort | | Extra High | xhigh | Normalised to max | | Max | max | Maximum effort |

Any value except none enables thinking mode.

Models

Graded effort is honoured by DeepSeek V4 Pro (deepseek-v4-pro) and V4 Flash (deepseek-v4-flash), which map low/medium to high and xhigh to max. The model list is loaded live from your account's /models endpoint, so new releases appear without a package update. DeepSeek also swaps improved builds in behind the same model id, as it did with V4 Flash 0731, so those arrive on their own too.

Retired names: deepseek-chat and deepseek-reasoner stopped resolving on 2026-07-24. If a saved workflow still selects one, change it to deepseek-v4-flash or deepseek-v4-pro.

Install

Community Nodes UI: Settings → Community nodes → Install:

n8n-nodes-deepseek-thinking

Self hosted, from source:

git clone https://github.com/pirazor/n8n-nodes-deepseek-thinking.git
cd n8n-nodes-deepseek-thinking && npm install && npm run build
cp -r . ~/.n8n/custom/n8n-nodes-deepseek-thinking   # then restart n8n

Usage

Add DeepSeek Chat Model (Thinking), select your existing DeepSeek credential, pick a model and Thinking Level, then connect it to an AI Agent's Model input.

Reuses n8n's built-in deepSeekApi credential, so there is nothing new to configure. Temperature, topP, maxTokens, penalties, timeout, retries and JSON response format all work as before.

Tip: thinking costs latency and tokens. Setting None on classification and extraction steps is often the biggest speedup in an agent pipeline.

Notes

• Works inside an AI Agent with tools. In thinking mode DeepSeek returns a reasoning_content field and requires it back on every later request that carries tools. LangChain drops it, so the second leg of a tool calling loop fails with 400 The reasoning_content in the thinking mode must be passed back to the API. This node carries it across turns, matching on tool call id.

• Runs are reported to n8n, so the sub node shows its input, output and token usage in the execution panel like the built in models do.

• JSON response format and thinking are incompatible on some models. Use None if a model rejects the pair.

• If the node does not appear in an Agent's Model dropdown, set N8N_COMMUNITY_PACKAGES_ALLOW_TOOL_USAGE=true and restart n8n.

License

MIT © 2026 Dr. Enes Karaaslan, Connected Wise LLC

Not affiliated with or endorsed by DeepSeek or n8n GmbH.