What are the hardware requirements for Qwen2.5 14B Instruct 1M GRPO Reasoning?

Qwen2.5 14B Instruct 1M GRPO Reasoning requires approximately 29.7 GB of VRAM and supports a context window of 986K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen2.5 14B Instruct 1M GRPO Reasoning and how large is it?

Qwen2.5 14B Instruct 1M GRPO Reasoning is developed by notbdq, a model with 14b 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 Qwen2.5 14B Instruct 1M GRPO Reasoning?

Qwen2.5 14B Instruct 1M GRPO Reasoning is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 14B Instruct 1M GRPO Reasoning by notbdq — VRAM 29.7GB, 986K context

Name: Qwen2.5 14B Instruct 1M GRPO Reasoning
Author: notbdq

Qwen2.5 14B Instruct 1M GRPO Reasoning is an open-source language model by notbdq. Features: 14b LLM, VRAM: 29.7GB, Context: 986K, Instruction-Based, LLM Explorer Score: 0.28.

Conversational Deploy:azure Endpoints compatible Instruct Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/notbdq/Qwen2.5-14B-Instruct-1M-GRPO-Reasoning

Qwen2.5 14B Instruct 1M GRPO Reasoning Parameters and Internals

LLM Name	Qwen2.5 14B Instruct 1M GRPO Reasoning
Repository 🤗	https://huggingface.co/notbdq/Qwen2.5-14B-Instruct-1M-GRPO-Reasoning
Model Size	14b
Required VRAM	29.7 GB
Updated	2026-07-30
Maintainer	notbdq
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-6 5.0 GB: 2-of-6 5.0 GB: 3-of-6 5.0 GB: 4-of-6 5.0 GB: 5-of-6 4.7 GB: 6-of-6
Model Architecture	Qwen2ForCausalLM
Context Length	1010000
Model Max Length	1010000
Transformers Version	4.48.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen2.5 14B Instruct 1M GRPO Reasoning 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 Qwen2.5 14B Instruct 1M GRPO Reasoning

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 14B Instruct 1M	986K / 29.6 GB	10388	342
T3Q Qwen2.5 14B V1.0 E3	986K / 29.7 GB	852	28
...hts Qwen2.5 14B Coder Creative	986K / 29.3 GB	267	0
ZYH LLM Qwen2.5 14B V4	986K / 29.7 GB	27	8
Qwen2.5 14B 1M YOYO V3	986K / 29.7 GB	254	4
Qwen2.5 14B YOYO V4	986K / 29.7 GB	20	5
Qwen2.5 14B YOYO Latest V2	986K / 29.7 GB	129	0
ZYH LLM Qwen2.5 14B V3	986K / 29.7 GB	23	8
Impish QWEN 14B 1M	986K / 29.7 GB	56	26
Q2.5 14B Instruct 1M Harmony	986K / 29.7 GB	3	1

Note: green Score (e.g. "73.2") means that the model is better than notbdq/Qwen2.5-14B-Instruct-1M-GRPO-Reasoning.