Open-weight model
tourn-522e0294-instructtext-hyper-s2epre
by Firza Hadzami firzahdzm/tourn-522e0294-instructtext-hyper-s2epre
tourn-522e0294-instructtext-hyper-s2epre is an open-weight model from Firza Hadzami. It has 3.1B parameters and a 32,768-token context. At 16-bit it needs about 7.4 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.
Runs On
What it takes to serve tourn-522e0294-instructtext-hyper-s2epre (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 Oct 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
- Sliding window (tokens)
- 32,768
- RoPE base
- 1e+06
- Stored precision
- bfloat16
- Model type
- qwen2
Identity and Version
- Repository
- firzahdzm/tourn-522e0294-instructtext-hyper-s2epre
- Publisher
- Firza Hadzami
- 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
- 57b8b9b515f58fc42a324f5519c73f9d09331a69
- First published
- 2026-10-12
- Last updated
- 2026-10-12
Files and Weights
13 files, 6.2 GB in total. The weights are 2 files totalling 6.2 GB in safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model-00001-of-00002.safetensors | Weights | 5.0 GB | 1b1a7cbe797c |
| model-00002-of-00002.safetensors | Weights | 1.2 GB | 22f0dfc3d989 |
| added_tokens.json | Configuration | 605 B | — |
| config.json | Configuration | 737 B | — |
| generation_config.json | Configuration | 38 B | — |
| model.safetensors.index.json | Configuration | 35.6 KB | — |
| special_tokens_map.json | Configuration | 617 B | — |
| loss.txt | Other | 22 B | — |
| .gitattributes | Repository | 1.6 KB | — |
| merges.txt | Tokenizer | 1.7 MB | — |
| tokenizer.json | Tokenizer | 11.4 MB | 9c5ae00e602b |
| tokenizer_config.json | Tokenizer | 4.7 KB | — |
| vocab.json | Tokenizer | 2.8 MB | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 6.2 GB
Released by Firza Hadzami 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 tourn-522e0294-instructtext-hyper-s2epre
How much GPU memory does tourn-522e0294-instructtext-hyper-s2epre 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 tourn-522e0294-instructtext-hyper-s2epre 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 tourn-522e0294-instructtext-hyper-s2epre's context length?
32,768 tokens, from the maximum position embeddings in its published configuration.