gemma3-khmer-fsds-v2 is an open-weight model from PHENG SOPANHA. It has 1B parameters and a 32,768-token context. At 16-bit it needs about 2.4 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 gemma3-khmer-fsds-v2 (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 | 2.0 GB | 2.4 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 1.0 GB | 1.2 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 0.5 GB | 0.6 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.
gemma3-khmer-fsds-v2 on every accelerator the SAVRN Index prices, at every precision
Model Card
The publisher has not written a card for this model.
Configuration
- Architecture
- Gemma3ForCausalLM
- Context length (tokens)
- 32,768
- Layers
- 26
- Hidden size
- 1,152
- Feed-forward size
- 6,912
- Attention heads
- 4
- Key/value heads
- 1
- Head dimension
- 256
- Vocabulary size
- 262,144
- Sliding window (tokens)
- 512
- Model type
- gemma3_text
Identity and Version
- Repository
- SopanhaZinII/gemma3-khmer-fsds-v2
- Publisher
- PHENG SOPANHA
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 1B parameters
- Languages
- Not stated by the source
- Revision
- 5972ef0d1879e8125ae0bbdfc38c6e73bba44d8c
- First published
- 2026-10-17
- Last updated
- 2026-10-17
Files and Weights
9 files, 2.0 GB in total. The weights are 1 file totalling 2.0 GB in safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model.safetensors | Weights | 2.0 GB | 1a99b55cfcc6 |
| chatbot_config.json | Configuration | 1.9 KB | — |
| config.json | Configuration | 1.8 KB | — |
| generation_config.json | Configuration | 210 B | — |
| passages.json | Configuration | 2.4 MB | — |
| chat_template.jinja | Other | 1.5 KB | — |
| .gitattributes | Repository | 1.6 KB | — |
| tokenizer.json | Tokenizer | 33.4 MB | a6c776bcef3f |
| tokenizer_config.json | Tokenizer | 848 B | — |
License and Download
- License
- Not stated by the source
- Access
- Open weights, no gate
- Download size
- 2.0 GB
Released by PHENG SOPANHA through its official repository on Hugging Face.
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 2.0 GB |
| 16-bit | 2.0 GB |
| 8-bit | 1.0 GB |
| 4-bit | 0.5 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About gemma3-khmer-fsds-v2
How much GPU memory does gemma3-khmer-fsds-v2 need?
About 2.4 GB at 16-bit and 0.6 GB at 4-bit: the weights (1B parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run gemma3-khmer-fsds-v2 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 gemma3-khmer-fsds-v2's context length?
32,768 tokens, from the maximum position embeddings in its published configuration.