What are the hardware requirements for Claude Oss 350M?

Claude Oss 350M requires approximately 1.4 GB of VRAM and supports a context window of 125K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Claude Oss 350M and how large is it?

Claude Oss 350M is developed by squ11z1, a model with 350m parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Claude Oss 350M perform on standard benchmarks?

Claude Oss 350M has the following published scores: LMSYS ELO 1413. Compare against reference models on this page or on the LLM Explorer leaderboards.

Claude Oss 350M by squ11z1 — VRAM 1.4GB, 125K context

Name: Claude Oss 350M
Author: squ11z1

Claude Oss 350M is an open-source language model by squ11z1. Features: 350m LLM, VRAM: 1.4GB, Context: 125K, License: other, Quantized, LLM Explorer Score: 0.4, ELO: 1413.

Base model:finetune:liquidai/l... Base model:liquidai/lfm2.5-350... Claude Claude-style Conversational En Endpoints compatible Gguf Lfm2 Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/squ11z1/claude-oss-350m

Claude Oss 350M Benchmarks

LMSys ELO 1413 vs 1272 (so35) 11.1%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Claude Oss 350M Parameters and Internals

LLM Name	Claude Oss 350M
Repository 🤗	https://huggingface.co/squ11z1/claude-oss-350m
Base Model(s)	LiquidAI/LFM2.5-350M LiquidAI/LFM2.5-350M
Model Size	350m
Required VRAM	1.4 GB
Updated	2026-07-06
Maintainer	squ11z1
Model Type	lfm2
Model Files	1.4 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	Lfm2ForCausalLM
License	other
Context Length	128000
Model Max Length	128000
Transformers Version	5.0.0rc1
Tokenizer Class	TokenizersBackend
Padding Token	<\|pad\|>
Vocabulary Size	65536

Rank the Claude Oss 350M capabilities

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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