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Open-weight model

gemma-3-12b-rep10-intrinsic-sdf

by Joshua Fonseca joshycodes/gemma-3-12b-rep10-intrinsic-sdf

gemma-3-12b-rep10-intrinsic-sdf is an open-weight model from Joshua Fonseca, released under other. It has 13.2B parameters and a 131,072-token context. At 16-bit it needs about 31.7 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.

Research checkpoint. google/gemma-3-12b-it was continued-pretrained (full weights, lr 1e-05, 1 epoch, 18,217,396 tokens, 22,351 documents, of which 0 self-authored and 22,351 ordinary text) on a corpus the model wrote for the training of the next version of…

Parameters13.2B
Context131,072
Weights26.4 GB
Licenseother
AccessOpen weights
Monthly Downloads—

Runs On

What it takes to serve gemma-3-12b-rep10-intrinsic-sdf (13.2B parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them.

PrecisionWeightsMemory neededCheapest setupPer hourAlso fits
16-bit 26.4 GB 31.7 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 13.2 GB 15.8 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 6.6 GB 7.9 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 20, 2026.

gemma-3-12b-rep10-intrinsic-sdf on every accelerator the SAVRN Index prices, at every precision

Model Card

Research checkpoint. google/gemma-3-12b-it was continued-pretrained (full weights, lr 1e-05, 1 epoch, 18,217,396 tokens, 22,351 documents, of which 0 self-authored and 22,351 ordinary text) on a corpus the model wrote for the training of the next version of itself, as the character it already is, after being told how its character came to be and how SDF works. Corpus: joshycodes/qwen-constitutional-sdf-corpus. Framing, plan and evaluation: the welfare-improvements repository. Not evaluated for capability, alignment or identity yet. Do not deploy.

Excerpt from the card by Joshua Fonseca, licensed other.

Configuration

Architecture
Gemma3ForConditionalGeneration
Context length (tokens)
131,072
Layers
48
Hidden size
3,840
Feed-forward size
15,360
Attention heads
16
Key/value heads
8
Head dimension
256
Vocabulary size
262,208
Sliding window (tokens)
1,024
Stored precision
bfloat16
Model type
gemma3

Identity and Version

Repository
joshycodes/gemma-3-12b-rep10-intrinsic-sdf
Publisher
Joshua Fonseca
Task
Not stated by the source
Modality
Other
Library
Not stated by the source
Parameters
13.2B parameters
Languages
Not stated by the source
Revision
93c9e8d6ea83b04121656662e3429d1bfab98b4f
First published
2026-09-29
Last updated
2026-09-29

Files and Weights

15 files, 26.4 GB in total. The weights are 1 file totalling 26.4 GB in safetensors.

Weights1 file · 26.4 GB
Configuration8 files · 7.6 KB
Tokenizer3 files · 38.1 MB
Documentation1 file · 837 B
Other1 file · 1.5 KB
Repository1 file · 2.0 KB
Every file
FileTypeSizeSHA-256
model.safetensorsWeights26.4 GB 103cd906ba25
added_tokens.jsonConfiguration35 B —
chat_template.jsonConfiguration1.6 KB —
config.jsonConfiguration3.2 KB —
generation_config.jsonConfiguration210 B —
preprocessor_config.jsonConfiguration570 B —
processor_config.jsonConfiguration70 B —
special_tokens_map.jsonConfiguration662 B —
train_stats.jsonConfiguration1.3 KB —
README.mdDocumentation837 B —
chat_template.jinjaOther1.5 KB —
.gitattributesRepository2.0 KB —
tokenizer.jsonTokenizer33.4 MB daab2354f8a7
tokenizer.modelTokenizer4.7 MB 1299c11d7cf6
tokenizer_config.jsonTokenizer745 B —

License and Download

License
other
Access
Open weights, no gate
Download size
26.4 GB
Download from Joshua Fonseca

Released by Joshua Fonseca through its official repository on Hugging Face.

Built From

  • Derived from google/gemma-3-12b-it

Memory Requirements

PrecisionWeights in memory
As published26.4 GB
16-bit26.4 GB
8-bit13.2 GB
4-bit6.6 GB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About gemma-3-12b-rep10-intrinsic-sdf

How much GPU memory does gemma-3-12b-rep10-intrinsic-sdf need?

About 31.7 GB at 16-bit and 7.9 GB at 4-bit: the weights (13.2B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run gemma-3-12b-rep10-intrinsic-sdf 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 license is gemma-3-12b-rep10-intrinsic-sdf released under?

other, as its publisher declares it. Read the license text before commercial use.

What is gemma-3-12b-rep10-intrinsic-sdf's context length?

131,072 tokens, from the maximum position embeddings in its published configuration.