What are the hardware requirements for SYNTHETIC 5 1010?

SYNTHETIC 5 1010 requires approximately 283.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed SYNTHETIC 5 1010 and how large is it?

SYNTHETIC 5 1010 is developed by Synin, a model with 763.2b 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 SYNTHETIC 5 1010?

SYNTHETIC 5 1010 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

SYNTHETIC 5 1010 by Synin — VRAM 283.5GB

Name: SYNTHETIC 5 1010
Author: Synin

SYNTHETIC 5 1010 is an open-source language model by Synin. Features: 763.2b LLM, VRAM: 283.5GB, License: mit, LLM Explorer Score: 0.27.

8-bit Conversational Deepseek v41 Endpoints compatible Fp8 Image-text-to-text Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Synin/SYNTHETIC-5-1010

SYNTHETIC 5 1010 Parameters and Internals

LLM Name	SYNTHETIC 5 1010
Repository 🤗	https://huggingface.co/Synin/SYNTHETIC-5-1010
Model Size	763.2b
Required VRAM	283.5 GB
Updated	2026-10-17
Maintainer	Synin
Model Type	deepseek_v41
Model Files	1.0 GB: 1-of-48 1.3 GB: 2-of-48 7.4 GB: 3-of-48 7.4 GB: 4-of-48 7.4 GB: 5-of-48 7.4 GB: 6-of-48 7.4 GB: 7-of-48 7.4 GB: 8-of-48 7.4 GB: 9-of-48 7.4 GB: 10-of-48 7.4 GB: 11-of-48 7.4 GB: 12-of-48 7.4 GB: 13-of-48 7.4 GB: 14-of-48 7.4 GB: 15-of-48 7.4 GB: 16-of-48 7.4 GB: 17-of-48 7.4 GB: 18-of-48 7.4 GB: 19-of-48 7.4 GB: 20-of-48 7.4 GB: 21-of-48 7.4 GB: 22-of-48 7.4 GB: 23-of-48 7.4 GB: 24-of-48 7.4 GB: 25-of-48 7.4 GB: 26-of-48 7.4 GB: 27-of-48 7.4 GB: 28-of-48 7.4 GB: 29-of-48 7.4 GB: 30-of-48 7.4 GB: 31-of-48 7.4 GB: 32-of-48 7.4 GB: 33-of-48 7.4 GB: 34-of-48 7.4 GB: 35-of-48 7.4 GB: 36-of-48 7.4 GB: 37-of-48 7.4 GB: 38-of-48 7.4 GB: 39-of-48 7.4 GB: 40-of-48
Model Architecture	DeepseekV41ForCausalLM
License	mit
Transformers Version	5.6.0

Rank the SYNTHETIC 5 1010 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 SYNTHETIC 5 1010

Best Alternatives	Context / RAM	Downloads	Likes
DeepSeek V4.1 Flash	0K / 290.9 GB	75774	1760
DeepSeek V4.1 Flash 1017	0K / 302.2 GB	42122	2137
DeepSeek V4.1 Flash NVFP4	0K / 315.6 GB	2413	82
...epSeek V4.1 Flash 1017 Heretic	0K / 283.5 GB	363	9
DeepSeek V4.1 Flash NVFP4	0K / 315.6 GB	180	1
...epSeek V4.1 Flash NVFP4 Nvidia	0K / 298.7 GB	295	5
...eepSeek V4.1 Flash Abliterated	0K / 302.2 GB	273	3
...eepSeek V4.1 Flash Abliterated	0K / 302.2 GB	57	2
DeepSeek V4.1 Flash NVFP4	0K / 314.3 GB	44	2
DeepSeek V4.1 Flash	0K / 290.9 GB	25	1

Note: green Score (e.g. "73.2") means that the model is better than Synin/SYNTHETIC-5-1010.