Personal Assistant Use Case
Recommendations for models that excel at memory, context retention, and personalized interactions.
💡 Note: For personal assistant tasks—such as recalling preferences, maintaining conversation history, managing schedules, or adapting tone over time—instruct-tuned models with strong long-context handling are preferred over thinking-tuned variants. These models prioritize coherence, empathy, and user-specific adaptation over raw analytical power.
Use the selector below to find the best assistant-like model for your hardware:
Recommended model:Gemma 3 12B (Q4_K_XL) (includes Vision) Use in LMStudio
Parameters: 12B | Quantization: Q4_K_XL | Model Memory Impact: 9.3 GB
Context Overhead: 1.27GB (based on 16,384 token context)
Note: The size of context in GB is an estimate that shows the "worst case". It may be smaller in actual use, but is assumed to be higher for safely assessing upper bounds.
Note: The size of context in GB is an estimate that shows the "worst case". It may be smaller in actual use, but is assumed to be higher for safely assessing upper bounds.
| Total | Context | Model | Leftover | |
|---|---|---|---|---|
| RAM | 16.00GB | 0.00GB | 4.26GB | 3.74GB |
| VRAM | 8.00GB | 1.27GB | 5.04GB | 0.20GB |