llmfit
Hundreds of models & providers. One command to find what runs on your hardware.
Understand the llmfit plan command. This guide details how to estimate LLM hardware feasibility and identify necessary upgrades for optimal performance on your system.
How the llmfit Benchmark Command Works: Automated LLM Inference TestingLearn how the llmfit bench command automates LLM inference testing. Measure throughput, detect servers, and submit results to the community repository.
Which LLM Runtimes Does llmfit Support? A Complete Guide to Local AI BackendsDiscover which LLM runtimes llmfit supports including Ollama MLX llama cpp Docker LM Studio vLLM and RamaLama with its unified ModelProvider trait for seamless local AI backend integration.
How to Override Memory Bandwidth or Efficiency Settings in llmfitOverride llmfit memory bandwidth and efficiency settings using hardware profiles, TUI, environment variables, or CLI flags for custom TPS estimates on your hardware.
How the llmfit Fit Algorithm Chooses a Runtime: Hardware-Aware Execution in RustDiscover how the llmfit fit algorithm chooses a runtime. It ranks hardware against model needs, filters by backend, and picks the first GPU-first option for efficient execution.
min_vram_gb vs min_ram_gb in llmfit: GPU VRAM vs CPU RAM Requirements ExplainedUnderstand min_vram_gb vs min_ram_gb in llmfit. Learn the difference between GPU VRAM and CPU RAM requirements for LLM inference based on model size. Optimize your setup now.
How llmfit Handles Unified Memory on Apple Silicon for LLM InferenceDiscover how llmfit leverages unified memory on Apple Silicon for faster LLM inference. Optimize performance by treating system RAM as a shared pool.
How llmfit Determines the FitLevel of a Model: Memory-Aware Analysis in RustDiscover how llmfit determines model FitLevel by analyzing memory requirements against available hardware and runtime constraints. Learn more about this Rust library.
RunMode Options in llmfit: 5 Execution Strategies for LLM InferenceExplore llmfit RunMode options: Gpu, TensorParallel, MoeOffload, CpuOffload, and CpuOnly. Optimize LLM inference by distributing model weights across GPU VRAM, system RAM, and CPU.
ModelFit Analysis Methods in llmfit: 5 Ways to Evaluate LLM Hardware FitExplore the 5 analysis methods in llmfit ModelFit to evaluate LLM hardware fit. Calculate memory, optimize runtime, and score compatibility for your LLM.
How llmfit Estimates LLM Throughput: Roofline Modeling and Efficiency FactorsDiscover how llmfit estimates LLM throughput using roofline modeling and efficiency factors. Learn about TPS prediction, GPU memory bandwidth, and runtime mode adjustments for optimal performance.
How the llmfit Analysis Pipeline Workflow Ranks LLMs for Your HardwareDiscover the llmfit analysis pipeline workflow. It ranks language models for your hardware by analyzing system capabilities, filtering models, and estimating performance. Get the best LLMs for your setup.
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