What are the hardware requirements for Stablelm Tuned Alpha 7B 16bit?

Stablelm Tuned Alpha 7B 16bit requires approximately 16 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Stablelm Tuned Alpha 7B 16bit and how large is it?

Stablelm Tuned Alpha 7B 16bit is developed by vvsotnikov, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Stablelm Tuned Alpha 7B 16bit perform on standard benchmarks?

Stablelm Tuned Alpha 7B 16bit has the following published scores: MMLU 24.41, LMSYS ELO 952. Compare against reference models on this page or on the LLM Explorer leaderboards.

Stablelm Tuned Alpha 7B 16bit by vvsotnikov — VRAM 16GB, 4K context

Name: Stablelm Tuned Alpha 7B 16bit
Author: vvsotnikov

Stablelm Tuned Alpha 7B 16bit is an open-source language model by vvsotnikov. Features: 7b LLM, VRAM: 16GB, Context: 4K, License: cc-by-nc-sa-4.0, Quantized, LLM Explorer Score: 0.2, ELO: 952, Arc: 31.9, HellaSwag: 53.6, MMLU: 24.4, GSM8K: 0.8.

16bit Dataset:dahoas/full-hh-rlhf Dataset:dmayhem93/chatcombined Dataset:huggingfaceh4/databric... Dataset:jeffwan/sharegpt vicun... Dataset:nomic-ai/gpt4all promp... Dataset:tatsu-lab/alpaca En Endpoints compatible Gpt neox Pytorch Quantized Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/vvsotnikov/stablelm-tuned-alpha-7b-16bit

Stablelm Tuned Alpha 7B 16bit Benchmarks

LMSys ELO 952 vs 1272 (so35) -25.2%

^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)

Stablelm Tuned Alpha 7B 16bit Parameters and Internals

Model Type

causal-lm

Additional Notes

This version is optimized for speed and memory usage, compressed to 16-bit with no functional changes from the original model.

LLM Name	Stablelm Tuned Alpha 7B 16bit
Repository 🤗	https://huggingface.co/vvsotnikov/stablelm-tuned-alpha-7b-16bit
Base Model(s)	Stablelm Tuned Alpha 7B stabilityai/stablelm-tuned-alpha-7b
Model Size	7b
Required VRAM	16 GB
Updated	2026-08-05
Maintainer	vvsotnikov
Model Type	gpt_neox
Model Files	10.1 GB: 1-of-2 5.9 GB: 2-of-2
Supported Languages	en
Quantization Type	16bit
Model Architecture	GPTNeoXForCausalLM
License	cc-by-nc-sa-4.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.28.1
Tokenizer Class	GPTNeoXTokenizer
Vocabulary Size	50432
Torch Data Type	float16

Rank the Stablelm Tuned Alpha 7B 16bit 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

Best Alternatives to Stablelm Tuned Alpha 7B 16bit

Best Alternatives	Context / RAM	Downloads	Likes
...lm Tuned Alpha 7B Sharded 8bit	4K / 8.6 GB	15	2
Open Calm 7B 8bit	2K / 7.4 GB	9	10
Dolly V2 7B Sharded 8bit	2K / 7.4 GB	9	1
Dolly V2 7B 8bit	2K / 7.4 GB	7	0
Literature 7B 16384	16K / 36 GB	9	16
RedPajama 7B 16384	16K / 36 GB	8	4
Stablelm Tuned Alpha 7B	4K / 31.9 GB	713	361
Stablelm Base Alpha 7B	4K / 31.9 GB	884	208
Stablelm 7B Sft V7 Epoch 3	4K / 32.4 GB	64	67
StableLManticore 7B	4K / 16 GB	10	1

Note: green Score (e.g. "73.2") means that the model is better than vvsotnikov/stablelm-tuned-alpha-7b-16bit.