What are the hardware requirements for Llm Jp 4 8B Thinking 8bit?

Llm Jp 4 8B Thinking 8bit requires approximately 9.2 GB of VRAM and supports a context window of 64K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llm Jp 4 8B Thinking 8bit and how large is it?

Llm Jp 4 8B Thinking 8bit is developed by mlx-community, a model with 8b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Llm Jp 4 8B Thinking 8bit?

Llm Jp 4 8B Thinking 8bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llm Jp 4 8B Thinking 8bit by mlx-community — VRAM 9.2GB, 64K context

Name: Llm Jp 4 8B Thinking 8bit
Author: mlx-community

Llm Jp 4 8B Thinking 8bit is an open-source language model by mlx-community. Features: 8b LLM, VRAM: 9.2GB, Context: 64K, License: apache-2.0, Quantized, LLM Explorer Score: 0.23.

8-bit 8bit Base model:llm-jp/llm-jp-4-8b-... Base model:quantized:llm-jp/ll... Conversational En Ja Llama Mlx Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlx-community/llm-jp-4-8b-thinking-8bit

Llm Jp 4 8B Thinking 8bit Parameters and Internals

LLM Name	Llm Jp 4 8B Thinking 8bit
Repository 🤗	https://huggingface.co/mlx-community/llm-jp-4-8b-thinking-8bit
Base Model(s)	Llm Jp 4 8B Thinking llm-jp/llm-jp-4-8b-thinking
Model Size	8b
Required VRAM	9.2 GB
Updated	2026-08-10
Maintainer	mlx-community
Model Type	llama
Model Files	5.4 GB: 1-of-2 3.8 GB: 2-of-2
Supported Languages	en ja
Quantization Type	8bit
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	65536
Model Max Length	65536
Transformers Version	4.51.0
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Vocabulary Size	196608
Torch Data Type	bfloat16

Rank the Llm Jp 4 8B Thinking 8bit capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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 Llm Jp 4 8B Thinking 8bit

Best Alternatives	Context / RAM	Downloads	Likes
...B Instruct Gradient 1048K 4bit	1024K / 4.5 GB	10	2
...B Instruct Gradient 1048K 8bit	1024K / 8.6 GB	11	1
...truct Gradient 1048K Bpw6 EXL2	1024K / 6.7 GB	2	2
...truct Gradient 1048K Bpw5 EXL2	1024K / 5.8 GB	5	0
Llama 3 8B Instruct 1048K 4bit	1024K / 4.5 GB	525	25
Llama 3 8B Instruct 1048K 8bit	1024K / 8.6 GB	213	17
... Gradient 1048K 8.0bpw H8 EXL2	1024K / 8.6 GB	2	3
...ct Gradient 1048K Bpw2.25 EXL2	1024K / 3.4 GB	5	1
Llama 3 8B Instruct 262K 2bit	256K / 2.5 GB	11	1
...B Instruct 262k V2 EXL2 5.0bpw	256K / 5.8 GB	5	1