Developer Tools●Mid
LLM Gateway – Simple API format converter for LLM providers
LiteLLM already does this with more providers, more features, and way more maturity.
Ship It
modinfo
203mo ago
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Makes local LLMs faster and more reliable by optimizing for your device
by tanavc·Jun 30, 2026·5 points·0 comments
AI Analysis
●●●BangerBig BrainSolve My Problem
Dynamic KV cache sizing beats Ollama's wasteful 4096-token default allocation.
Strengths
- •Right-sizes KV cache per request instead of Ollama's fixed 4096-token over-allocation
- •Four-tier RAM pressure system proactively downgrades precision before swap risk
- •Transparent proxy requires zero code changes to existing Ollama integrations
Weaknesses
- •Ollama-only, doesn't help LM Studio or llama.cpp users
- •Another proxy layer in the stack means another potential failure point
Category
Target Audience
Developers running local LLMs with Ollama
Similar To
Ollama · vLLM · llama.cpp
Post Description
Time to first token is 39% faster
Agent wall times decrease by 46%
No swaps
Tracks your resource usage in real-time and adjusts how the model runs so that it works perfectly on your device.
Implements KV cache sizing, prefix caching, live RAM pressure management, context trimming, KV quantization, and more.
Built a ton of features
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