Open-weight model
tourn-bb36cb9c-instructtext-hyper-v5b
by Firza Hadzami firzahdzm/tourn-bb36cb9c-instructtext-hyper-v5b
tourn-bb36cb9c-instructtext-hyper-v5b is an open-weight model from Firza Hadzami. It has 7.2B parameters and a 32,768-token context. At 16-bit it needs about 17.4 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-bb36cb9c-instructtext-hyper-v5b (7.2B 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 | 14.5 GB | 17.4 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 7.2 GB | 8.7 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 3.6 GB | 4.3 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
- MistralForCausalLM
- Context length (tokens)
- 32,768
- Layers
- 32
- Hidden size
- 4,096
- Feed-forward size
- 14,336
- Attention heads
- 32
- Key/value heads
- 8
- Head dimension
- 128
- Vocabulary size
- 32,002
- Sliding window (tokens)
- 4,096
- RoPE base
- 10000
- Stored precision
- bfloat16
- Model type
- mistral
Identity and Version
- Repository
- firzahdzm/tourn-bb36cb9c-instructtext-hyper-v5b
- Publisher
- Firza Hadzami
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 7.2B parameters
- Languages
- Not stated by the source
- Revision
- 4ff2bfbe89323341e605d818beb36f0d911cc345
- First published
- 2026-10-05
- Last updated
- 2026-10-05
Files and Weights
13 files, 14.5 GB in total. The weights are 3 files totalling 14.5 GB in safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model-00001-of-00003.safetensors | Weights | 4.9 GB | 2f0fe86239fb |
| model-00002-of-00003.safetensors | Weights | 5.0 GB | 5c16a1fe7401 |
| model-00003-of-00003.safetensors | Weights | 4.5 GB | 2d03a47a9024 |
| added_tokens.json | Configuration | 51 B | — |
| config.json | Configuration | 638 B | — |
| generation_config.json | Configuration | 38 B | — |
| model.safetensors.index.json | Configuration | 23.9 KB | — |
| special_tokens_map.json | Configuration | 558 B | — |
| loss.txt | Other | 22 B | — |
| .gitattributes | Repository | 1.5 KB | — |
| tokenizer.json | Tokenizer | 3.5 MB | — |
| tokenizer.model | Tokenizer | 493.4 KB | dadfd56d7667 |
| tokenizer_config.json | Tokenizer | 1.7 KB | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 14.5 GB
Released by Firza Hadzami through its official repository on Hugging Face.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 14.5 GB |
| 16-bit | 14.5 GB |
| 8-bit | 7.2 GB |
| 4-bit | 3.6 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About tourn-bb36cb9c-instructtext-hyper-v5b
How much GPU memory does tourn-bb36cb9c-instructtext-hyper-v5b need?
About 17.4 GB at 16-bit and 4.3 GB at 4-bit: the weights (7.2B parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run tourn-bb36cb9c-instructtext-hyper-v5b 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-bb36cb9c-instructtext-hyper-v5b's context length?
32,768 tokens, from the maximum position embeddings in its published configuration.