Emomni-v1 is an open-weight model from Jotakak, released under Apache License 2.0. It has 8.3B parameters. At 16-bit it needs about 20 GB of GPU memory, which fits on 1x MI300X from $1.85 an hour, at the lowest prices in the SAVRN Index. It draws 8 downloads a month.
Complete Emomni checkpoint with global LoRA merged into the model weights. The checkpoint includes its tokenizer, chat template, Whisper feature extractor, and generation configuration. No separate LoRA adapter is required.
Runs On
What it takes to serve Emomni-v1 (8.3B 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 | 16.7 GB | 20.0 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 8-bit | 8.3 GB | 10.0 GB | 1x MI300X (192 GB) Vultr |
$1.85 | 1x H100 $1.99 · 1x MI325X $2.00 |
| 4-bit | 4.2 GB | 5.0 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 Oct 23, 2026.
Emomni-v1 on every accelerator the SAVRN Index prices, at every precision
Model Card
By Jotakak, published under apache-2.0, revision 873a067f5b74.
Complete Emomni checkpoint with global LoRA merged into the model weights. The checkpoint includes its tokenizer, chat template, Whisper feature extractor, and generation configuration. No separate LoRA adapter is required. This release replaces the earlier audio-scoped LoRA checkpoint with the global-LoRA checkpoint; it is not an equivalent merge of the earlier audio-scoped model. Use the Emomni-v1 code: The custom model is loaded by src.modelingemomni.EmomniModel, rather than the generic AutoModelForCausalLM loader. The original export verified all 837 saved tensors and matching text/audio greedy outputs after reloading. These checks verify checkpoint serialization; they are not a new…
Read Jotakak's full model card
Emomni-v1 Base — merged BF16
Complete Emomni checkpoint with global LoRA merged into the model weights. The checkpoint includes its tokenizer, chat template, Whisper feature extractor, and generation configuration. No separate LoRA adapter is required.
This release replaces the earlier audio-scoped LoRA checkpoint with the global-LoRA checkpoint; it is not an equivalent merge of the earlier audio-scoped model.
Use the Emomni-v1 code:
bash scripts/run_serve.sh --model Jotakak/Emomni-v1
The custom model is loaded by src.modeling_emomni.EmomniModel, rather than
the generic AutoModelForCausalLM loader.
The original export verified all 837 saved tensors and matching text/audio greedy outputs after reloading. These checks verify checkpoint serialization; they are not a new quality benchmark.
Configuration
- Architecture
- EmomniModel
- Model type
- emomni-v1
Identity and Version
- Repository
- Jotakak/Emomni-v1
- Publisher
- Jotakak
- Task
- Not stated by the source
- Modality
- Other
- Library
- Not stated by the source
- Parameters
- 8.3B parameters
- Languages
- Not stated by the source
- Revision
- 873a067f5b74e0e7b3d75ee0f80564f4bed99415
- First published
- 2026-03-03
- Last updated
- 2026-10-11
Files and Weights
18 files, 16.7 GB in total. The weights are 5 files totalling 16.7 GB in safetensors.
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| model-00001-of-00005.safetensors | Weights | 4.0 GB | d559f5eced2b |
| model-00002-of-00005.safetensors | Weights | 3.9 GB | 1cb473f62030 |
| model-00003-of-00005.safetensors | Weights | 3.9 GB | fd6960aea570 |
| model-00004-of-00005.safetensors | Weights | 3.7 GB | c33bf2654061 |
| model-00005-of-00005.safetensors | Weights | 1.3 GB | ca8b2d3163ca |
| added_tokens.json | Configuration | 605 B | 58b54bbe36fc |
| config.json | Configuration | 6.0 KB | 0fbe0dfe5687 |
| generation_config.json | Configuration | 270 B | fe87f722821a |
| model.safetensors.index.json | Configuration | 74.6 KB | 1a8e838bd3cb |
| preprocessor_config.json | Configuration | 357 B | 654cf18d3e16 |
| special_tokens_map.json | Configuration | 613 B | 76862e765266 |
| README.md | Documentation | 965 B | — |
| chat_template.jinja | Other | 2.5 KB | — |
| .gitattributes | Repository | 1.6 KB | — |
| merges.txt | Tokenizer | 1.7 MB | — |
| tokenizer.json | Tokenizer | 11.4 MB | 9c5ae00e602b |
| tokenizer_config.json | Tokenizer | 4.7 KB | 0a04a9d7d4a6 |
| vocab.json | Tokenizer | 2.8 MB | ca10d7e9fb3e |
License and Download
- License
- apache-2.0
- Access
- Open weights, no gate
- Download size
- 16.7 GB
Released by Jotakak through its official repository on Hugging Face. Read the license.
Built From
- Derived from Qwen/Qwen2.5-7B-Instruct
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 16.7 GB |
| 16-bit | 16.7 GB |
| 8-bit | 8.3 GB |
| 4-bit | 4.2 GB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Built on This Model
- Quantized fromEmomni-v1-bnb-4bit
- Derived fromEmomni-v1-bnb-4bit
Questions About Emomni-v1
How much GPU memory does Emomni-v1 need?
About 20 GB at 16-bit and 5 GB at 4-bit: the weights (8.3B parameters) plus a working margin. A long context needs more.
What is the cheapest GPU to run Emomni-v1 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 Emomni-v1 commercially?
Yes. Emomni-v1 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.