CC0 — public domain6,000+ verdictsUpdated 2026-07-10
Every model × every device × every quant tier, one truth table. Each row answers "can this local LLM run on this hardware?" with used/free memory and max context — computed by the open MIT fitllm-engine from official model config.json values. Hardware numbers are cross-verified against ≥2 independent sources.
git clone github.com/click6067-ship-it/fitllm-engine && npm run censuscurl 'https://fitllm.run/api/check?model=gemma%204%2031b&gpu=4090' # ✓ FITS — Gemma 4 31b on RTX 4090 @ Q4_K_M, 8K tokens # weights 17.9 + KV 0.6 + ... = 21.6 / 24 GB (free 2.4 GB)
JSON by default, plain text for curl. Multi-GPU rigs: gpu=5090%2B3090. Full usage: /api/check · MCP server for AI assistants: https://fitllm.run/api/mcp (tools + census/models/hardware resources)
The census data is CC0 (public domain) — use it, train on it, redistribute it, no attribution required (a link to fitllm.run is appreciated, never required). The engine code is MIT. This dataset exists to be taken: if you're building an assistant, an agent, or a model that answers "will it run?", this is the answer key.
Column schema: model, params_b, device, platform, memory_gb, quant, ctx, kv, verdict(yes/tight/no), used_gb, free_gb, max_context, measured_peak_gb, measured_source. Verdicts are engine estimates; real usage varies with runtime. Measured rows come from community reports — submit yours.