What are the hardware requirements for Zebra Qwen3 7MLA21GDN NoT SFT 1M Combined FCE?

Zebra Qwen3 7MLA21GDN NoT SFT 1M Combined FCE requires approximately 4.6 GB of VRAM and supports a context window of 40K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Zebra Qwen3 7MLA21GDN NoT SFT 1M Combined FCE and how large is it?

Zebra Qwen3 7MLA21GDN NoT SFT 1M Combined FCE is developed by amd, a model with 1.7b 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 Zebra Qwen3 7MLA21GDN NoT SFT 1M Combined FCE?

Zebra Qwen3 7MLA21GDN NoT SFT 1M Combined FCE is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Zebra Qwen3 7MLA21GDN NoT SFT 1M Combined FCE by amd — VRAM 4.6GB, 40K context

Name: Zebra Qwen3 7MLA21GDN NoT SFT 1M Combined FCE
Author: amd

Zebra Qwen3 7MLA21GDN NoT SFT 1M Combined FCE is an open-source language model by amd. Features: 1.7b LLM, VRAM: 4.6GB, Context: 40K, License: apache-2.0, LLM Explorer Score: 0.24.

Alignment-handbook Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-1.7b Conversational Dataset:amd/openmathinstruct-2... Dataset:amd/openr1-math-220k Dataset:amd/zebra llama chatqa... Dataset:amd/zebra llama openth... Dataset:junxiongwang/sftdatase... Endpoints compatible Generated from trainer Llama Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/amd/zebra_qwen3_7MLA21GDN_noT_SFT_1M_combined_fCE

Zebra Qwen3 7MLA21GDN NoT SFT 1M Combined FCE Parameters and Internals

LLM Name	Zebra Qwen3 7MLA21GDN NoT SFT 1M Combined FCE
Repository 🤗	https://huggingface.co/amd/zebra_qwen3_7MLA21GDN_noT_SFT_1M_combined_fCE
Base Model(s)	Qwen/Qwen3-1.7B Qwen/Qwen3-1.7B
Model Size	1.7b
Required VRAM	4.6 GB
Updated	2026-08-08
Maintainer	amd
Model Type	llama
Model Files	4.6 GB
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	40960
Model Max Length	40960
Transformers Version	4.52.4
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|im_end\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Zebra Qwen3 7MLA21GDN NoT SFT 1M Combined FCE 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 Zebra Qwen3 7MLA21GDN NoT SFT 1M Combined FCE

Best Alternatives	Context / RAM	Downloads	Likes
Lucy 128K	128K / 3.4 GB	123	112
Polaris 1.7B Preview	128K / 3.4 GB	73	8
DictaLM 3.0 1.7B Instruct	60K / 3.4 GB	2842	1
Qwen3 1.7B	40K / 4 GB	5633291	500
CORe Pico 4	40K / 3.4 GB	895	2
CORe Pico V3	40K / 3.4 GB	720	0
...en3 1.7B Teacher Note Severity	40K / 3.4 GB	386	0
KBevo Qwen3 1.7B SFT	40K / 3.4 GB	462	0
Qwen3 1.7B ONNX Web	40K / GB	178	1
RIFA FLASH 1.7B	40K / 3.4 GB	583	0

Note: green Score (e.g. "73.2") means that the model is better than amd/zebra_qwen3_7MLA21GDN_noT_SFT_1M_combined_fCE.