Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models. Built upon extensive training, Qwen3 delivers groundbreaking advancements in reasoning, instruction-following, agent capabilities, and multilingual support, with the following key features: - Uniquely support of seamless switching between thinking mode (for complex logical reasoning, math, and coding) and non-thinking mode (for efficient, general-purpose dialogue) within single model, ensuring optimal performance across various scenarios. - Significantly enhancement in its reasoning capabilities, surpassing previous QwQ (in thinking mode) and…
Open-weight model · Text generation
hpc-assistant-qwen3-4b
by Vaibhav Kailash Mangroliya VaibhavKKM/hpc-assistant-qwen3-4b
hpc-assistant-qwen3-4b is an open-weight model for text generation from Vaibhav Kailash Mangroliya, released under Creative Commons Attribution-NonCommercial-ShareAlike 4.0. It has 4B parameters and a 262,144-token context. At 16-bit it needs about 9.7 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index. It draws 113 downloads a month.
A fine-tuned Qwen/Qwen3-4B-Instruct-2507 that answers HPC questions: Slurm job scripts, GPUs, modules, storage, and access to EuroHPC systems and the European AI Factories. It works best with retrieved documentation excerpts in the prompt.
Parameters4B
Context262,144
Weights14.8 GB
Licensecc-by-nc-sa-4.0
AccessOpen weights
Monthly Downloads113
Runs On
What it takes to serve hpc-assistant-qwen3-4b (4B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.
| Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits |
|---|---|---|---|---|---|
| 16-bit | 8.0 GB | 9.7 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 4.0 GB | 4.8 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 2.0 GB | 2.4 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the SAVRN Index, read Oct 24, 2026.
hpc-assistant-qwen3-4b on every accelerator the SAVRN Index prices, at every precision
Model Card
A fine-tuned Qwen/Qwen3-4B-Instruct-2507 that answers HPC questions: Slurm job scripts, GPUs, modules, storage, and access to EuroHPC systems and the European AI Factories. It works best with retrieved documentation excerpts in the prompt. This release is a full merged model (bf16 safetensors), built in four stages: 1. Logit distillation (round 12a). The student learns the full next-token distribution of Qwen3-Next-80B-A3B-Instruct (top-20 probabilities at every answer token) on 46,717 verified question–answer pairs. LoRA rank 32. Merged. 2. On-policy distillation from Qwen3-Next (round 12e). The stage-1 model answers the training questions itself; 14,514 of its own answers are scored token…
Excerpt from the card by Vaibhav Kailash Mangroliya, licensed cc-by-nc-sa-4.0.
Configuration
- Architecture
- Qwen3ForCausalLM
- Context length (tokens)
- 262,144
- Layers
- 36
- Hidden size
- 2,560
- Feed-forward size
- 9,728
- Attention heads
- 32
- Key/value heads
- 8
- Head dimension
- 128
- Vocabulary size
- 151,936
- Model type
- qwen3
Identity and Version
- Repository
- VaibhavKKM/hpc-assistant-qwen3-4b
- Publisher
- Vaibhav Kailash Mangroliya
- Task
- Text generation
- Modality
- Text
- Library
- transformers
- Parameters
- 4B parameters
- Languages
- en
- Revision
- 932128ed8a924ec03a77ae53ace76b3303026398
- First published
- 2026-10-18
- Last updated
- 2026-10-23
Files and Weights
20 files, 14.8 GB in total. The weights are 3 files totalling 14.8 GB in gguf, safetensors.
Weights3 files · 14.8 GB
Configuration11 files · 10.0 KB
Tokenizer2 files · 11.4 MB
Documentation1 file · 9.4 KB
Other2 files · 4.6 KB
Repository1 file · 1.7 KB
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| gguf/hpc-assistant-qwen3-4b-Q4_K_M.gguf | Weights | 2.5 GB | 9f44afc15ad2 |
| gguf/hpc-assistant-qwen3-4b-Q8_0.gguf | Weights | 4.3 GB | c2f69b759703 |
| model.safetensors | Weights | 8.0 GB | 20d68ceeb888 |
| SOUP.json | Configuration | 1.3 KB | — |
| config.json | Configuration | 1.6 KB | — |
| eval_PAIRED_gemma_judge.json | Configuration | 1.1 KB | — |
| eval_PAIRED_majority.json | Configuration | 1.1 KB | — |
| eval_PAIRED_qwen_judge.json | Configuration | 1.1 KB | — |
| eval_PAIRED_vs_previous.json | Configuration | 1.1 KB | — |
| eval_confirmation_gemma.json | Configuration | 575 B | — |
| eval_confirmation_gpt-oss.json | Configuration | 578 B | — |
| eval_confirmation_majority.json | Configuration | 579 B | — |
| eval_confirmation_qwen.json | Configuration | 577 B | — |
| generation_config.json | Configuration | 213 B | — |
| README.md | Documentation | 9.4 KB | — |
| chat_template.jinja | Other | 2.6 KB | — |
| gguf/Modelfile | Other | 1.9 KB | — |
| .gitattributes | Repository | 1.7 KB | — |
| tokenizer.json | Tokenizer | 11.4 MB | be75606093db |
| tokenizer_config.json | Tokenizer | 693 B | — |
License and Download
- License
- cc-by-nc-sa-4.0
- Access
- Open weights, no gate
- Download size
- 14.8 GB
Download from Vaibhav Kailash Mangroliya
Released by Vaibhav Kailash Mangroliya through its official repository on Hugging Face.
Built From
- Derived from Qwen/Qwen3-4B-Instruct-2507
- Quantized from Qwen/Qwen3-4B-Instruct-2507
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 14.8 GB |
| 16-bit | 8.0 GB |
| 8-bit | 4.0 GB |
| 4-bit | 2.0 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About hpc-assistant-qwen3-4b
How much GPU memory does hpc-assistant-qwen3-4b need?
About 9.7 GB at 16-bit and 2.4 GB at 4-bit: the weights (4B parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run hpc-assistant-qwen3-4b on?
At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists.
Can I use hpc-assistant-qwen3-4b commercially?
Not without separate permission. hpc-assistant-qwen3-4b is released under Creative Commons Attribution-NonCommercial-ShareAlike 4.0. CC BY-NC-SA 4.0 permits non-commercial sharing and adapting with credit, and requires adaptations to use the same license. Commercial use needs separate permission.
What is hpc-assistant-qwen3-4b's context length?
262,144 tokens, from the maximum position embeddings in its published configuration.
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