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Open-weight model

endo_rex_pathgen_qwen2_5-3b-vl-averaged-8bits

by Xinxi Lyu alrope/endo_rex_pathgen_qwen2_5-3b-vl-averaged-8bits

endo_rex_pathgen_qwen2_5-3b-vl-averaged-8bits is an open-weight model from Xinxi Lyu. It has 3.8B parameters and a 128,000-token context. At 16-bit it needs about 9 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.

Parameters3.8B
Context128,000
Weights7.5 GB
License—
AccessOpen weights
Monthly Downloads—

Runs On

What it takes to serve endo_rex_pathgen_qwen2_5-3b-vl-averaged-8bits (3.8B 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 7.5 GB 9.0 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 3.8 GB 4.5 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 1.9 GB 2.3 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.

endo_rex_pathgen_qwen2_5-3b-vl-averaged-8bits on every accelerator the SAVRN Index prices, at every precision

Model Card

The publisher has not written a card for this model.

Configuration

Architecture
Qwen2_5_VLForConditionalGeneration
Context length (tokens)
128,000
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
Model type
qwen2_5_vl

Identity and Version

Repository
alrope/endo_rex_pathgen_qwen2_5-3b-vl-averaged-8bits
Publisher
Xinxi Lyu
Task
Not stated by the source
Modality
Other
Library
Not stated by the source
Parameters
3.8B parameters
Languages
Not stated by the source
Revision
2d6c857c7f2ff915e82278d31f3bd5a0bac39f28
First published
2026-10-07
Last updated
2026-10-07

Files and Weights

15 files, 7.5 GB in total. The weights are 2 files totalling 7.5 GB in safetensors.

Weights2 files · 7.5 GB
Configuration7 files · 71.9 KB
Tokenizer4 files · 15.9 MB
Other1 file · 1.0 KB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
model-00001-of-00002.safetensorsWeights5.0 GB 704bf260c3be
model-00002-of-00002.safetensorsWeights2.5 GB 9fde7d083b11
added_tokens.jsonConfiguration605 B —
config.jsonConfiguration3.3 KB —
generation_config.jsonConfiguration121 B —
model.safetensors.index.jsonConfiguration65.5 KB —
preprocessor_config.jsonConfiguration829 B —
special_tokens_map.jsonConfiguration613 B —
video_preprocessor_config.jsonConfiguration955 B —
chat_template.jinjaOther1.0 KB —
.gitattributesRepository1.6 KB —
merges.txtTokenizer1.7 MB —
tokenizer.jsonTokenizer11.4 MB 9c5ae00e602b
tokenizer_config.jsonTokenizer4.8 KB —
vocab.jsonTokenizer2.8 MB —

License and Download

License
Not stated by the source
Access
Open weights, no gate
Download size
7.5 GB
Download from Xinxi Lyu

Released by Xinxi Lyu through its official repository on Hugging Face.

Memory Requirements

PrecisionWeights in memory
As published7.5 GB
16-bit7.5 GB
8-bit3.8 GB
4-bit1.9 GB

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

Questions About endo_rex_pathgen_qwen2_5-3b-vl-averaged-8bits

How much GPU memory does endo_rex_pathgen_qwen2_5-3b-vl-averaged-8bits need?

About 9 GB at 16-bit and 2.3 GB at 4-bit: the weights (3.8B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run endo_rex_pathgen_qwen2_5-3b-vl-averaged-8bits 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 endo_rex_pathgen_qwen2_5-3b-vl-averaged-8bits's context length?

128,000 tokens, from the maximum position embeddings in its published configuration.