Runs On
What it takes to serve math_memorization_seen (3.1B 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 | 6.2 GB | 7.4 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 3.1 GB | 3.7 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 1.5 GB | 1.9 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 Sep 18, 2026.
Model Card
The publisher has not written a card for this model.
Configuration
- Architecture
- Qwen2ForCausalLM
- Context length (tokens)
- 32,768
- Layers
- 36
- Hidden size
- 2,048
- Feed-forward size
- 11,008
- Attention heads
- 16
- Key/value heads
- 2
- Vocabulary size
- 151,936
- Model type
- qwen2
Identity and Version
- Repository
- talzoomanzoo/math_memorization_seen
- Publisher
- Minju Gwak
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 3.1B parameters
- Languages
- Not stated by the source
- Revision
- 4838efaeb8977b798d15ad0a4b7b57bf93c38cb5
- First published
- 2026-09-18
- Last updated
- 2026-09-18
Files and Weights
7 files, 6.2 GB in total. The weights are 1 file totalling 6.2 GB in safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.safetensors | Weights | 6.2 GB | 84602f3d0678 |
| config.json | Configuration | 1.6 KB | — |
| generation_config.json | Configuration | 243 B | — |
| chat_template.jinja | Other | 2.5 KB | — |
| .gitattributes | Repository | 1.6 KB | — |
| tokenizer.json | Tokenizer | 11.4 MB | 3fd169731d2c |
| tokenizer_config.json | Tokenizer | 693 B | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 6.2 GB
Released by Minju Gwak through its official repository on Hugging Face.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 6.2 GB |
| 16-bit | 6.2 GB |
| 8-bit | 3.1 GB |
| 4-bit | 1.5 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About math_memorization_seen
How much GPU memory does math_memorization_seen need?
About 7.4 GB at 16-bit and 1.9 GB at 4-bit: the weights (3.1B parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run math_memorization_seen 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.
What is math_memorization_seen's context length?
32,768 tokens, from the maximum position embeddings in its published configuration.