What are the hardware requirements for SILMA 9B Instruct V1.0?

SILMA 9B Instruct V1.0 requires approximately 18.6 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed SILMA 9B Instruct V1.0 and how large is it?

SILMA 9B Instruct V1.0 is developed by silma-ai, a model with 9b 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 SILMA 9B Instruct V1.0?

SILMA 9B Instruct V1.0 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

SILMA 9B Instruct V1.0 by silma-ai — VRAM 18.6GB, 8K context

Name: SILMA 9B Instruct V1.0
Author: silma-ai

SILMA 9B Instruct V1.0 is an open-source language model by silma-ai. Features: 9b LLM, VRAM: 18.6GB, Context: 8K, License: gemma, Instruction-Based, LLM Explorer Score: 0.24.

Ar Conversational Deploy:azure En Endpoints compatible Gemma2 Instruct Model-index Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/silma-ai/SILMA-9B-Instruct-v1.0

SILMA 9B Instruct V1.0 Parameters and Internals

Model Type

text generation, conversational

Use Cases

Areas:

Content Creation and Communication, Research and Education

Applications:

Text Generation, Chatbots and Conversational AI, Text Summarization

Additional Notes

The model can be run up to 6x faster using torch compile features.

Supported Languages

Arabic (native), English (native)

Responsible Ai Considerations

Fairness:

LLMs trained on large-scale, real-world text data can reflect socio-cultural biases embedded in the training material.

Transparency:

This model card summarizes details on the models' architecture, capabilities, limitations, and evaluation processes.

Accountability:

Guidelines are provided for responsible use with the model.

Mitigation Strategies:

Mechanisms and guidelines for content safety are essential. Developers are encouraged to exercise caution and implement appropriate content safety safeguards.

Input Output

Input Format:

Text string, such as a question, a prompt, or a document to be summarized.

Accepted Modalities:

text

Output Format:

Generated Arabic or English text in response.

Release Notes

Version:

SILMA-9B-Instruct-v1.0

Notes:

Initial model release with open-weight access for deployment across various use-cases

LLM Name	SILMA 9B Instruct V1.0
Repository 🤗	https://huggingface.co/silma-ai/SILMA-9B-Instruct-v1.0
Model Size	9b
Required VRAM	18.6 GB
Updated	2026-07-12
Maintainer	silma-ai
Model Type	gemma2
Instruction-Based	Yes
Model Files	3.9 GB: 1-of-5 4.0 GB: 2-of-5 4.0 GB: 3-of-5 4.0 GB: 4-of-5 2.7 GB: 5-of-5
Supported Languages	ar en
Model Architecture	Gemma2ForCausalLM
License	gemma
Context Length	8192
Model Max Length	8192
Transformers Version	4.43.4
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the SILMA 9B Instruct V1.0 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 SILMA 9B Instruct V1.0

Best Alternatives	Context / RAM	Downloads	Likes
...2 9B Cpt Sahabatai V1 Instruct	8K / 18.6 GB	1369	47
Gigantes V2 Gemma2 9B It	8K / 18.6 GB	5	1
Gemma Evo 10B	8K / 20.4 GB	26	5
Gigantes V3 Gemma2 9B It	8K / 18.6 GB	6	0
Gigantes V1 Gemma2 9B It	8K / 18.6 GB	10	2
Magnum V4 9B	8K / 18.6 GB	88	20
Odin 9B	8K / 18.6 GB	26	5
...B IT Simpo Infinity Preference	8K / 18.6 GB	108	19
GaMS 9B Instruct	8K / 18.6 GB	1583	2
Turkish Gemma 9B V0.1	8K / 18.6 GB	480	40

Note: green Score (e.g. "73.2") means that the model is better than silma-ai/SILMA-9B-Instruct-v1.0.