LM Studio is an exceptional tool for running local LLMs, but it has a specific quirk: the "Thinking" (reasoning) toggle often only appears for models downloaded directly through the LM Studio interface. If you use external GGUFs from providers like Unsloth or Bartowski, this capability is frequently hidden.
Here is how to manually activate the Thinking switch for any reasoning model.
### Method 1: The Native Way (Easiest)
The simplest way to ensure the toggle appears is to download models directly within LM Studio. Before downloading, verify that the **Thinking Icon** (the green brain symbol) is present next to the model's name. If this icon is visible, the toggle will work automatically in your chat window.
### Method 2: The Manual Workaround (For External Models)
If you prefer to manage your own model files or use specific quants from external providers, you must "spoof" the model's identity so LM Studio recognizes it as a reasoning model. This requires creating a metadata registry in the LM Studio cache.
I am providing Gemma-4-31B as an example.
#### 1. Directory Setup
You need to create a folder hierarchy within the LM Studio hub. Navigate to:
`...User\.cache\lm-studio\hub\models\`
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Create a provider folder (e.g., `google`). **Note:** This must be in all lowercase.
Inside that folder, create a model-specific folder (e.g., `gemma-4-31b-q6`).
* **Full Path Example:** `...\.cache\lm-studio\hub\models\google\gemma-4-31b-q6\`
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#### 2. Configuration Files
Inside your model folder, you must create two files: `manifest.json` and `model.yaml`.
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Please note that the most important lines to change are:
- The model (the same as the model folder you created)
- And Model Key (the relative path to the model). The path is where you downloaded you model and the one LM Studio is actually using.
**File 1: `manifest.json`**
Replace `"PATH_TO_MODEL"` with the actual relative path to where your GGUF file is stored. For instance, in my case, I have the models located at Google/(Unsloth)_Gemma-4-31B-it-GGUF-Q6_K_XL, where Google is a subfolder in the model folder.
{ "type": "model", "owner": "google", "name": "gemma-4-31b-q6", "dependencies": [ { "type": "model", "purpose": "baseModel", "modelKeys": [ "PATH_TO_MODEL" ], "sources": [ { "type": "huggingface", "user": "Unsloth", "repo": "gemma-4-31B-it-GGUF" } ] } ], "revision": 1 }
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**File 2: `model.yaml`**
This file tells LM Studio how to parse the reasoning tokens (the "thought" blocks). Replace `"PATH_TO_MODEL"` here as well.
# model.yaml defines cross-platform AI model configurations model: google/gemma-4-31b-q6 base: - key: PATH_TO_MODEL sources: - type: huggingface user: Unsloth repo: gemma-4-31B-it-GGUF config: operation: fields: - key: llm.prediction.temperature value: 1.0 - key: llm.prediction.topPSampling value: checked: true value: 0.95 - key: llm.prediction.topKSampling value: 64 - key: llm.prediction.reasoning.parsing value: enabled: true startString: "<thought>" endString: "</thought>" customFields: - key: enableThinking displayName: Enable Thinking description: Controls whether the model will think before replying type: boolean defaultValue: true effects: - type: setJinjaVariable variable: enable_thinking metadataOverrides: domain: llm architectures: - gemma4 compatibilityTypes: - gguf paramsStrings: - 31B minMemoryUsageBytes: 17000000000 contextLengths: - 262144 vision: true reasoning: true trainedForToolUse: true
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Configuration Files for GPT-OSS and Qwen 3.5
For OpenAI Models, follow the same steps but use the following manifest and model.yaml as an example:
1- GPT-OSS File 1: manifest.json
{ "type": "model", "owner": "openai", "name": "gpt-oss-120b", "dependencies": [ { "type": "model", "purpose": "baseModel", "modelKeys": [ "lmstudio-community/gpt-oss-120b-GGUF", "lmstudio-community/gpt-oss-120b-mlx-8bit" ], "sources": [ { "type": "huggingface", "user": "lmstudio-community", "repo": "gpt-oss-120b-GGUF" }, { "type": "huggingface", "user": "lmstudio-community", "repo": "gpt-oss-120b-mlx-8bit" } ] } ], "revision": 3 }
2- GPT-OSS File 2: model.yaml
# model.yaml is an open standard for defining cross-platform, composable AI models # Learn more at https://modelyaml.org model: openai/gpt-oss-120b base: - key: lmstudio-community/gpt-oss-120b-GGUF sources: - type: huggingface user: lmstudio-community repo: gpt-oss-120b-GGUF - key: lmstudio-community/gpt-oss-120b-mlx-8bit sources: - type: huggingface user: lmstudio-community repo: gpt-oss-120b-mlx-8bit customFields: - key: reasoningEffort displayName: Reasoning Effort description: Controls how much reasoning the model should perform. type: select defaultValue: low options: - value: low label: Low - value: medium label: Medium - value: high label: High effects: - type: setJinjaVariable variable: reasoning_effort metadataOverrides: domain: llm architectures: - gpt-oss compatibilityTypes: - gguf - safetensors paramsStrings: - 120B minMemoryUsageBytes: 65000000000 contextLengths: - 131072 vision: false reasoning: true trainedForToolUse: true config: operation: fields: - key: llm.prediction.temperature value: 0.8 - key: llm.prediction.topKSampling value: 40 - key: llm.prediction.topPSampling value: checked: true value: 0.8 - key: llm.prediction.repeatPenalty value: checked: true value: 1.1 - key: llm.prediction.minPSampling value: checked: true value: 0.05
3- Qwen3.5 File 1: manifest.json
{ "type": "model", "owner": "qwen", "name": "qwen3.5-27b-q8", "dependencies": [ { "type": "model", "purpose": "baseModel", "modelKeys": [ "Qwen/(Unsloth)_Qwen3.5-27B-GGUF-Q8_0" ], "sources": [ { "type": "huggingface", "user": "unsloth", "repo": "Qwen3.5-27B" } ] } ], "revision": 1 }
4- Qwen3.5 File 2: model.yaml
# model.yaml is an open standard for defining cross-platform, composable AI models # Learn more at https://modelyaml.org model: qwen/qwen3.5-27b-q8 base: - key: Qwen/(Unsloth)_Qwen3.5-27B-GGUF-Q8_0 sources: - type: huggingface user: unsloth repo: Qwen3.5-27B metadataOverrides: domain: llm architectures: - qwen27 compatibilityTypes: - gguf paramsStrings: - 27B minMemoryUsageBytes: 21000000000 contextLengths: - 262144 vision: true reasoning: true trainedForToolUse: true config: operation: fields: - key: llm.prediction.temperature value: 0.8 - key: llm.prediction.topKSampling value: 20 - key: llm.prediction.topPSampling value: checked: true value: 0.95 - key: llm.prediction.minPSampling value: checked: false value: 0 customFields: - key: enableThinking displayName: Enable Thinking description: Controls whether the model will think before replying type: boolean defaultValue: false effects: - type: setJinjaVariable variable: enable_thinking
I hope this helps.
Let me know if you faced any issues.
P.S. This guide works fine for LM Studio 0.4.9.
