SAVRN
Search Contact SAVRN

Open-weight model · Text to speech

orpheus-3b-0.1-ft

by Unsloth AI unsloth/orpheus-3b-0.1-ft

03/18/2025 – We are releasing our 3B Orpheus TTS model with additional finetunes. Code is available on GitHub: CanopyAI/Orpheus-TTS Orpheus TTS is a state-of-the-art, Llama-based Speech-LLM designed for high-quality, empathetic text-to-speech generation.

Parameters3.3B
Context131,072
Weights6.6 GB
Licenseapache-2.0
AccessOpen weights
Monthly Downloads70.1k

Runs On

What it takes to serve orpheus-3b-0.1-ft (3.3B 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 6.6 GB 7.9 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
8-bit 3.3 GB 4.0 GB 1x MI300X (192 GB)
Vultr
$1.85 1x H100 $1.99 · 1x MI325X $2.00
4-bit 1.7 GB 2.0 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 Sep 18, 2026.

Model Card

By Unsloth AI, published under apache-2.0, revision eae2b6e5e429.

03/18/2025 – We are releasing our 3B Orpheus TTS model with additional finetunes. Code is available on GitHub: CanopyAI/Orpheus-TTS Orpheus TTS is a state-of-the-art, Llama-based Speech-LLM designed for high-quality, empathetic text-to-speech generation. This model has been finetuned to deliver human-level speech synthesis, achieving exceptional clarity, expressiveness, and real-time streaming performances. Check out our Colab (link to Colab) or GitHub (link to GitHub) on how to run easy inference on our finetuned models. Do not use our models for impersonation without consent, misinformation or deception (including fake news or fraudulent calls), or any illegal or harmful activity. By…

Read Unsloth AI's full model card

Orpheus 3B 0.1 Finetuned

03/18/2025 – We are releasing our 3B Orpheus TTS model with additional finetunes. Code is available on GitHub: CanopyAI/Orpheus-TTS


Orpheus TTS is a state-of-the-art, Llama-based Speech-LLM designed for high-quality, empathetic text-to-speech generation. This model has been finetuned to deliver human-level speech synthesis, achieving exceptional clarity, expressiveness, and real-time streaming performances.

Model Details

Model Capabilities

  • Human-Like Speech: Natural intonation, emotion, and rhythm that is superior to SOTA closed source models
  • Zero-Shot Voice Cloning: Clone voices without prior fine-tuning
  • Guided Emotion and Intonation: Control speech and emotion characteristics with simple tags
  • Low Latency: ~200ms streaming latency for realtime applications, reducible to ~100ms with input streaming

Model Sources

Usage

Check out our Colab (link to Colab) or GitHub (link to GitHub) on how to run easy inference on our finetuned models.

Model Misuse

Do not use our models for impersonation without consent, misinformation or deception (including fake news or fraudulent calls), or any illegal or harmful activity. By using this model, you agree to follow all applicable laws and ethical guidelines. We disclaim responsibility for any use.

Configuration

Architecture
LlamaForCausalLM
Context length (tokens)
131,072
Layers
28
Hidden size
3,072
Feed-forward size
8,192
Attention heads
24
Key/value heads
8
Head dimension
128
Vocabulary size
156,940
RoPE base
500000
Stored precision
bfloat16
Model type
llama

Identity and Version

Repository
unsloth/orpheus-3b-0.1-ft
Publisher
Unsloth AI
Task
Text to speech
Modality
Audio
Library
transformers
Parameters
3.3B parameters
Languages
en
Revision
eae2b6e5e429c81b95ac42a883ac64f126583d43
First published
2025-03-24
Last updated
2025-07-09

Files and Weights

11 files, 6.6 GB in total. The weights are 2 files totalling 6.6 GB in safetensors.

Weights2 files · 6.6 GB
Configuration4 files · 22.5 KB
Tokenizer2 files · 28.3 MB
Documentation1 file · 2.1 KB
Other1 file · 3.8 KB
Repository1 file · 1.6 KB
Every file
FileTypeSizeSHA-256
model-00001-of-00002.safetensorsWeights5.0 GB 1064bbba044a
model-00002-of-00002.safetensorsWeights1.6 GB 6fac70f10fa2
config.jsonConfiguration890 B
generation_config.jsonConfiguration230 B
model.safetensors.index.jsonConfiguration20.9 KB
special_tokens_map.jsonConfiguration508 B
README.mdDocumentation2.1 KB
chat_template.jinjaOther3.8 KB
.gitattributesRepository1.6 KB
tokenizer.jsonTokenizer22.8 MB fc3fecb199b4
tokenizer_config.jsonTokenizer5.4 MB

License and Download

License
apache-2.0
Access
Open weights, no gate
Download size
6.6 GB
Download from Unsloth AI

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

Built From

Memory Requirements

PrecisionWeights in memory
As published6.6 GB
16-bit6.6 GB
8-bit3.3 GB
4-bit1.7 GB

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

Questions About orpheus-3b-0.1-ft

How much GPU memory does orpheus-3b-0.1-ft need?

About 7.9 GB at 16-bit and 2 GB at 4-bit: the weights (3.3B parameters) plus a working margin. A long context needs more.

What is the cheapest GPU to run orpheus-3b-0.1-ft 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 orpheus-3b-0.1-ft commercially?

Yes. orpheus-3b-0.1-ft 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.

What is orpheus-3b-0.1-ft's context length?

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

Similar Models

Model · Text to speech

svara-tts-v1

Kenpath Labs

svara-TTS is a developer-first multilingual TTS model for 19 languages (18 Indic + Indian English). Built on an Orpheus-style discrete audio token approach, it targets clarity, expressiveness, and low-latency on commodity GPUs/CPUs. It supports light-weight emotion/style control (e.g.,,,, ) and simple speaker identities (Language (Gender)), with zero-shot adaptation paths. Try it live on the Demo Space, or on Colab Deployment scripts and inference repo will be available soon. Watch our Github for updates - Place style/emotion tags at the end of the sentence: आज... सच में अच्छी खबर है — शाम को मिलते हैं! - Use punctuation to hint prosody (ellipses, commas, exclamation). - For technical or…

Open weights apache-2.0 3.3B parameters 131,072 tokens transformers

Model · Text to speech

orpheus-3b-0.1-ft

Canopy Labs

03/18/2025 – We are releasing our 3B Orpheus TTS model with additional finetunes. Code is available on GitHub: CanopyAI/Orpheus-TTS Orpheus TTS is a state-of-the-art, Llama-based Speech-LLM designed for high-quality, empathetic text-to-speech generation. This model has been finetuned to deliver human-level speech synthesis, achieving exceptional clarity, expressiveness, and real-time streaming performances. Check out our Colab (link to Colab) or GitHub (link to GitHub) on how to run easy inference on our finetuned models. Do not use our models for impersonation without consent, misinformation or deception (including fake news or fraudulent calls), or any illegal or harmful activity. By…

Access requested at publisher apache-2.0 3.8B parameters transformers

Model · Text to speech

VibeVoice-1.5B

Microsoft

VibeVoice is a novel framework designed for generating expressive, long-form, multi-speaker conversational audio, such as podcasts, from text. It addresses significant challenges in traditional Text-to-Speech (TTS) systems, particularly in scalability, speaker consistency, and natural turn-taking. A core innovation of VibeVoice is its use of continuous speech tokenizers (Acoustic and Semantic) operating at an ultra-low frame rate of 7.5 Hz. These tokenizers efficiently preserve audio fidelity while significantly boosting computational efficiency for processing long sequences. VibeVoice employs a next-token diffusion framework, leveraging a Large Language Model (LLM) to understand textual…

Open weights mit 2.7B parameters transformers

VibeVoice is a novel framework designed for generating expressive, long-form, multi-speaker conversational audio, such as podcasts, from text. It addresses significant challenges in traditional Text-to-Speech (TTS) systems, particularly in scalability, speaker consistency, and natural turn-taking. A core innovation of VibeVoice is its use of continuous speech tokenizers (Acoustic and Semantic) operating at an ultra-low frame rate of 7.5 Hz. These tokenizers efficiently preserve audio fidelity while significantly boosting computational efficiency for processing long sequences. VibeVoice employs a next-token diffusion framework, leveraging a Large Language Model (LLM) to understand textual…

Open weights mit 2.7B parameters 65,536 tokens transformers

https://github.com/vibevoice-community/VibeVoice VibeVoice is a novel framework designed for generating expressive, long-form, multi-speaker conversational audio, such as podcasts, from text. It addresses significant challenges in traditional Text-to-Speech (TTS) systems, particularly in scalability, speaker consistency, and natural turn-taking. A core innovation of VibeVoice is its use of continuous speech tokenizers (Acoustic and Semantic) operating at an ultra-low frame rate of 7.5 Hz. These tokenizers efficiently preserve audio fidelity while significantly boosting computational efficiency for processing long sequences. VibeVoice employs a next-token diffusion framework, leveraging a…

Open weights mit 2.7B parameters transformers

Model · Text to speech

VoxCPM2

OpenBMB

VoxCPM2 is a tokenizer-free, diffusion autoregressive Text-to-Speech model — 2B parameters, 30 languages, 48kHz audio output, trained on over 2 million hours of multilingual speech data. - 30-Language Multilingual — No language tag needed; input text in any supported language directly - Voice Design — Generate a novel voice from a natural-language description alone (gender, age, tone, emotion, pace…); no reference audio required - Controllable Cloning — Clone any voice from a short clip, with optional style guidance to steer emotion, pace, and expression while preserving timbre - Ultimate Cloning — Provide reference audio + its transcript for audio-continuation cloning; every vocal nuance…

Open weights apache-2.0 2.3B parameters voxcpm