A Tiny LLM model with just 10 Million parameters, this is probably one of the small LLM arounds, and it is functional. Tiny-LLM was trained on 32B tokens of the Fineweb dataset, with a context length of 1024 tokens. To start using these models, you can simply load them via the Hugging Face `transformers` library:

Text generation

Input Text→ Output Text

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BOND-reranker

AronowLab

A cross-encoder reranker model fine-tuned for biomedical ontology entity normalization, designed to work with the BOND (Biomedical Ontology Neural Disambiguation) system. This model is a cross-encoder reranker trained to improve the accuracy of entity normalization by re-ranking candidate ontology terms retrieved by BOND's initial retrieval stage. It takes a query-candidate pair and outputs a relevance score. The model was trained on biomedical entity normalization data covering multiple ontologies including:

Category pending

Input Not verified→ Output Not verified

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Embedding-gemma-300M-skills

AROY76

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Embeddings & similarity

Input Text→ Output Embedding

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EmoRoBERTa

arpanghoshal

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Basic profile indexed · More details to follow

Text analysis

Input Text→ Output Text

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qwen38-27b-hca-checkpoints

arpicato

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Category pending

Input Not verified→ Output Not verified

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COST EXPLORER

Great models. Clear costs.

Cost analysis

Adjust monthly token usage to compare estimated API costs.

Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
Compares base text-token rates within the same channel

Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.

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How should API prices be compared?+

Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.

Do open weights mean free commercial use?+

Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.

Is the top-ranked model the best for me?+

Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.

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