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EMPIRICAL EVALUATIONS & SOTA REPRODUCIBILITY

Edge AI model benchmarks

Rigorous, reproducible head-to-head comparisons evaluating inference speed, memory footprint, token fertility, and hardware efficiency against leading open-source models.

Indic NLP · Edge LLMsVerified Data

Bharat-Tiny-LLM v3 vs. LLaMA 3 8B: Indic & Hindi Benchmark →

Direct empirical comparison between Eulogik’s Bharat-Tiny-LLM v3 (1.7B) powered by the Brahmi Tokenizer and Meta’s LLaMA 3 8B on Hindi NLP, token compression, and CPU runtime execution.

Bharat-Tiny-LLM1.7 Billion
LLaMA 38.0 Billion
View Full Benchmark Evaluation →
Vision · Document AIVerified Data

TinyDoc-VLM-256M vs. Donut: CPU Document AI Benchmark →

Evaluation of document understanding throughput, memory overhead, and OCR accuracy between TinyDoc-VLM-256M and Donut across CPU enterprise servers.

TinyDoc-VLM256 Million
Donut VLM140 Million
View Full Benchmark Evaluation →
Text Classification · TinyMLVerified Data

pico-type vs. FastText: 200KB Byte Classifier vs Word Vectors →

Empirical comparison between Eulogik’s pico-type-v02 (200KB ONNX byte-level classifier) and Meta’s FastText on binary size, inference latency, and multi-head routing capability.

pico-type1.5 Million
FastTextN/A (Embedding Matrix)
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Model your organizational cost reduction

Use our interactive TCO engine to calculate your exact dollar savings by running Eulogik edge models instead of cloud APIs.