5.6GB model, 10GB problem—here's the fix #localllm #ollama #devtips
Understanding Model Cache and Context Limits
The Importance of Model Size and Context
- The 9B model fits the laptop, but context for sessions may not align. A model file is 5.6 GB, with an additional quarter GB added for a short chat.
- Real session sizes can exceed 50,000 tokens, with longer sessions reaching up to 128,000 tokens. This impacts performance due to cache size requirements.
Cache Management and Performance
- Each token in the model's configuration requires approximately 32 KB of KV cache; thus, at 128,000 tokens, it totals around 4 GB.
- A dense model necessitates at least 16 GB of RAM for optimal performance during benchmarks that run at 256,000 tokens.
Misconceptions About Model Memory
- The model supports up to 262,000 tokens; however, Ollama's default setting limits this to just 4,096 tokens. Users often misattribute memory issues to the model itself.
Optimizing Memory Usage
- To enhance efficiency: enable flash attention and adjust an environment variable to store cache at Q8 format—this reduces memory usage from 4 GB to just 2 GB.
- It's crucial to size the context according to available RAM or quantize the cache effectively for better performance.