Skip to page content
SAVRN
Search Plan a project

Open-weight model · Text to speech

Sol

by Meana itriedcoding/Sol

Sol is an open-weight model for text to speech from Meana, released under Apache License 2.0. It has 144M parameters. At 16-bit it needs about 0.3 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index.

Parameters144M
Context—
Weights—
Licenseapache-2.0
AccessOpen weights
Monthly Downloads—

Runs On

What it takes to serve Sol (144M 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 0.3 GB 0.3 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 0.1 GB 0.2 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 0.1 GB 0.1 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 22, 2026.

Sol on every accelerator the SAVRN Index prices, at every precision

Model Card

Identity and Version

Repository
itriedcoding/Sol
Publisher
Meana
Task
Text to speech
Modality
Audio
Library
transformers
Parameters
144M parameters
Languages
en
Revision
0d8044a8daa0b700df28dd1144aa973d315573a2
First published
2026-10-19
Last updated
2026-10-19

License and Download

License
apache-2.0
Access
Open weights, no gate
Download from Meana

Released by Meana through its official repository on Hugging Face. Read the license.

Built From

Memory Requirements

PrecisionWeights in memory
16-bit0.3 GB
8-bit0.1 GB
4-bit0.1 GB

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

Questions About Sol

How much GPU memory does Sol need?

About 0.3 GB at 16-bit and 0.1 GB at 4-bit: the weights (144M parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run Sol 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.

Can I use Sol commercially?

Yes. Sol is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. It requires keeping the license and copyright notices and any NOTICE file, stating significant changes, and it includes an express patent grant from contributors.

Similar Models

Model · Text to speech

VieNeu-TTS-v3-Turbo

Pham Nguyen Ngoc Bao

VieNeu-TTS v3 Turbo is the next generation of Vietnamese TTS — 48 kHz high-fidelity speech, 23 built-in preset voices across three regions (North / Central / South), instant voice cloning, real-time streaming with an OpenAI-compatible API (16 concurrent streams on one RTX 3060), inline emotion cues, and seamless bilingual (En–Vi) code-switching. The reference implementation is the vieneu Python SDK (v3.7.1). Its minimal install is torch-free: on CPU everything runs on ONNX Runtime (PyTorch is never imported), and on a CUDA machine it auto-switches to the PyTorch engine with automatic batching and a continuous-batching stream scheduler — same API, no code change. The VieNeu-TTS v3 Turbo…

Open weights apache-2.0 131M parameters 1,024 tokens

Model · Text to speech

Soprano-1.1-80M

Eugene Kwek

2026.01.14 - Soprano-1.1-80M released! 95% fewer hallucinations and a 63% preference rate over Soprano-80M. 2026.01.13 - Soprano-Factory released! You can now train/fine-tune your own Soprano models. 2025.12.22 - Soprano-80M released! Code | Demo Soprano is an ultra‑lightweight, on-device text‑to‑speech (TTS) model designed for expressive, high‑fidelity speech synthesis at unprecedented speed. Soprano was designed with the following features: - Up to 2000x real-time generation on GPU and 20x real-time on CPU - Lossless streaming with one plus one, etc) If Soprano produces unsatisfactory results, you can easily regenerate it for a new, potentially better generation. You may also change the…

Open weights apache-2.0 80M parameters 1,024 tokens transformers

Model · Text to speech

nano

Nabad

MOSS-TTS-Nano is an open-source multilingual tiny speech generation model from MOSI.AI and the OpenMOSS team. With only 0.1B parameters, it is designed for realtime speech generation, can run directly on CPU without a GPU, and keeps the deployment stack simple enough for local demos, web serving, and lightweight product integration. 2026.4.10: We release MOSS-TTS-Nano. A demo Space is available at OpenMOSS-Team/MOSS-TTS-Nano. You can also view the demo and more details at openmoss.github.io/MOSS-TTS-Nano-Demo/. MOSS-TTS-Nano focuses on the part of TTS deployment that matters most in practice: small footprint, low latency, good enough quality for realtime products, and simple local setup. It…

Open weights apache-2.0 54M parameters 32,768 tokens

Model · Text to speech

mms-tts-hin

AI at Meta

mms - vits pipelinetag: text-to-speech This repository contains the Hindi (hin) language text-to-speech (TTS) model checkpoint. This model is part of Facebook's Massively Multilingual Speech project, aiming to provide speech technology across a diverse range of languages. You can find more details about the supported languages and their ISO 639-3 codes in the MMS Language Coverage Overview, and see all MMS-TTS checkpoints on the Hugging Face Hub: facebook/mms-tts. MMS-TTS is available in the Transformers library from version 4.33 onwards. VITS (Variational Inference with adversarial learning for end-to-end Text-to-Speech) is an end-to-end speech synthesis model that predicts a speech…

Open weights cc-by-nc-4.0 36M parameters transformers

Model · Text to speech

mms-tts-eng

AI at Meta

mms - vits pipelinetag: text-to-speech This repository contains the English (eng) language text-to-speech (TTS) model checkpoint. This model is part of Facebook's Massively Multilingual Speech project, aiming to provide speech technology across a diverse range of languages. You can find more details about the supported languages and their ISO 639-3 codes in the MMS Language Coverage Overview, and see all MMS-TTS checkpoints on the Hugging Face Hub: facebook/mms-tts. MMS-TTS is available in the Transformers library from version 4.33 onwards. VITS (Variational Inference with adversarial learning for end-to-end Text-to-Speech) is an end-to-end speech synthesis model that predicts a speech…

Open weights cc-by-nc-4.0 36M parameters transformers

Model · Text to speech

mms-tts-bam

AI at Meta

mms - vits pipelinetag: text-to-speech This repository contains the Bamanankan (bam) language text-to-speech (TTS) model checkpoint. This model is part of Facebook's Massively Multilingual Speech project, aiming to provide speech technology across a diverse range of languages. You can find more details about the supported languages and their ISO 639-3 codes in the MMS Language Coverage Overview, and see all MMS-TTS checkpoints on the Hugging Face Hub: facebook/mms-tts. MMS-TTS is available in the Transformers library from version 4.33 onwards. VITS (Variational Inference with adversarial learning for end-to-end Text-to-Speech) is an end-to-end speech synthesis model that predicts a speech…

Open weights cc-by-nc-4.0 36M parameters transformers