What are the hardware requirements for Pythia 12B Sft V8 Rlhf 2K Steps?

Pythia 12B Sft V8 Rlhf 2K Steps requires approximately 23.8 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Pythia 12B Sft V8 Rlhf 2K Steps and how large is it?

Pythia 12B Sft V8 Rlhf 2K Steps is developed by OpenAssistant, a model with 12b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Pythia 12B Sft V8 Rlhf 2K Steps perform on standard benchmarks?

Pythia 12B Sft V8 Rlhf 2K Steps has the following published scores: MMLU 26.12. Compare against reference models on this page or on the LLM Explorer leaderboards.

Pythia 12B Sft V8 Rlhf 2K Steps by OpenAssistant — VRAM 23.8GB, 2K context

Name: Pythia 12B Sft V8 Rlhf 2K Steps
Author: OpenAssistant

Pythia 12B Sft V8 Rlhf 2K Steps is an open-source language model by OpenAssistant. Features: 12b LLM, VRAM: 23.8GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.12, Arc: 43.4, HellaSwag: 70.1, MMLU: 26.1, GSM8K: 9.6.

Endpoints compatible Gpt neox Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/OpenAssistant/pythia-12b-sft-v8-rlhf-2k-steps

Pythia 12B Sft V8 Rlhf 2K Steps Benchmarks

ARC: 43.43 vs 96.7 (so35)^-55.1%

HellaSwag: 70.08 vs 95.3 (gpt4)^-26.5%

MMLU: 26.12 vs 88.3 (so35)^-70.4%

GSM8K: 9.55 vs 96.4 (so35)^-90.1%

LLME Score: 0.11569

^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)

Pythia 12B Sft V8 Rlhf 2K Steps (OpenAssistant/pythia-12b-sft-v8-rlhf-2k-steps)

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Pythia 12B Sft V8 Rlhf 2K Steps Parameters and Internals

LLM Name	Pythia 12B Sft V8 Rlhf 2K Steps
Repository 🤗	https://huggingface.co/OpenAssistant/pythia-12b-sft-v8-rlhf-2k-steps
Model Size	12b
Required VRAM	23.8 GB
Updated	2026-05-05
Maintainer	OpenAssistant
Model Type	gpt_neox
Model Files	10.0 GB: 1-of-3 9.9 GB: 2-of-3 3.9 GB: 3-of-3
Model Architecture	GPTNeoXForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.28.1
Tokenizer Class	GPTNeoXTokenizer
Vocabulary Size	50282
Torch Data Type	float16

Best Alternatives to Pythia 12B Sft V8 Rlhf 2K Steps

Best Alternatives	Context / RAM	Downloads	Likes
Dolly V2 12B	2K / 23.8 GB	3283	1955
...sst Sft 4 Pythia 12B Epoch 3.5	2K / 23.8 GB	2058	368
Oasst Rl 1 Pythia 12B	2K / 23.8 GB	9	4
Pythia 12B	2K / 23.8 GB	20051	145
Oasst Sft 1 Pythia 12B	2K / 23.8 GB	1231	278
H2ogpt Gm Oasst1 En 1024 12B	2K / 23.8 GB	1883	5
Pythia 12B Deduped	2K / 23.8 GB	3382	52
Pythia 12B Sft V8 7K Steps	2K / 23.8 GB	1106	22
H2ogpt Oasst1 512 12B	2K / 23.9 GB	1129	29
Pythia 12B Sft V8.2.5K Steps	2K / 23.8 GB	1028	0

Note: green Score (e.g. "73.2") means that the model is better than OpenAssistant/pythia-12b-sft-v8-rlhf-2k-steps.

Rank the Pythia 12B Sft V8 Rlhf 2K Steps 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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Release v20260328a

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Pythia 12B Sft V8 Rlhf 2K Steps by OpenAssistant

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Pythia 12B Sft V8 Rlhf 2K Steps Benchmarks

Pythia 12B Sft V8 Rlhf 2K Steps Parameters and Internals

Best Alternatives to Pythia 12B Sft V8 Rlhf 2K Steps

Rank the Pythia 12B Sft V8 Rlhf 2K Steps Capabilities

What open-source LLMs or SLMs are you in search of? 53999 in total.