What are the hardware requirements for Deepmath V1?

Deepmath V1 requires approximately 8.1 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Deepmath V1 and how large is it?

Deepmath V1 is developed by Intel, a model with 4b 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 Deepmath V1?

Deepmath V1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Deepmath V1 by Intel — VRAM 8.1GB, 256K context

Name: Deepmath V1
Author: Intel

Deepmath V1 is an open-source language model by Intel. Features: 4b LLM, VRAM: 8.1GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.22.

Agent Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-4b-think... Conversational Dataset:nvidia/openmathreasoni... En Endpoints compatible Grpo Math Qwen Qwen3 Reasoning Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Intel/deepmath-v1

Deepmath V1 Parameters and Internals

LLM Name	Deepmath V1
Repository 🤗	https://huggingface.co/Intel/deepmath-v1
Base Model(s)	Qwen3 4B Thinking 2507 Qwen/Qwen3-4B-Thinking-2507
Model Size	4b
Required VRAM	8.1 GB
Updated	2026-08-05
Maintainer	Intel
Model Type	qwen3
Model Files	5.0 GB: 1-of-2 3.1 GB: 2-of-2
Supported Languages	en
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	262144
Model Max Length	262144
Transformers Version	4.52.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Deepmath V1 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 Deepmath V1

Best Alternatives	Context / RAM	Downloads	Likes
FastContext 1.0 4B SFT	256K / 8.1 GB	5735	357
GRPO 4 70	256K / 8.1 GB	7	0
Qwen3 4B Instruct 2507	256K / 8.1 GB	3109972	911
Fable Traces	256K / 8.1 GB	468	210
Lightning 4B	256K / 8.1 GB	13	6
FastContext 1.0 4B RL	256K / 8.1 GB	4559	61
Qwen3 4B Thinking 2507	256K / 8.1 GB	291023	606
Qwen3 4B Instruct 2507 FP8	256K / 5.2 GB	1100744	78
Typhoon2.5 Qwen3 4B	256K / 8 GB	489877	6
Neuron 4B Instruct	256K / 8.1 GB	313	1

Note: green Score (e.g. "73.2") means that the model is better than Intel/deepmath-v1.