# whisper-large-v3-basque by Andoni Sudupe: Open-Weight Model
Source: https://savrn.com/models/whisper-large-v3-basque
Markdown alternate of the page above; the site index is https://savrn.com/llms.txt

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## Runs On

What it takes to serve whisper-large-v3-basque (1.6B 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 | 3.2 GB | 3.9 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |
| 8-bit | 1.6 GB | 1.9 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 |
| 4-bit | 0.8 GB | 1.0 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/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](https://savrn.com/ai-index/pricing/gpus), read Oct 7, 2026.

[whisper-large-v3-basque on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/whisper-large-v3-basque/gpus)

## Model Card

By Andoni Sudupe, published under apache-2.0, revision 51f752b4fc3d.

This model is a fine-tuned version of [openai/whisper-large-v3](https://savrn.com/models/whisper-large-v3) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2181 - Wer: 14.7372

### Model description

More information needed

### Intended uses & limitations

More information needed

### Training and evaluation data

More information needed

### Training procedure

#### Training hyperparameters

The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 256 - eval_batch_size: 32 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - total_train_batch_size: 512 - total_eval_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 5000 - mixed_precision_training: Native AMP

#### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer |
| --- | --- | --- | --- | --- |
| 0.1741 | 0.42 | 500 | 0.2910 | 23.2171 |
| 0.1388 | 0.84 | 1000 | 0.2418 | 18.3800 |
| 0.1084 | 1.26 | 1500 | 0.2245 | 16.7258 |
| 0.1041 | 1.68 | 2000 | 0.2155 | 15.6607 |
| 0.0793 | 2.1 | 2500 | 0.2108 | 15.0738 |
| 0.0794 | 2.52 | 3000 | 0.2102 | 15.1867 |
| 0.0774 | 2.94 | 3500 | 0.2072 | 14.7105 |
| 0.0607 | 3.36 | 4000 | 0.2142 | 14.7454 |
| 0.0608 | 3.78 | 4500 | 0.2117 | 14.6900 |
| 0.0506 | 4.2 | 5000 | 0.2181 | 14.7372 |

[Read the full model card (170 words)](https://savrn.com/models/whisper-large-v3-basque/card)

## Configuration

Architecture

WhisperForConditionalGeneration

Layers

32

Vocabulary size

51,866

Stored precision

float16

Model type

whisper

## Identity and Version

Repository

Ansu/whisper-large-v3-basque

Publisher

Andoni Sudupe

Task

Not stated by the source

Modality

Other

Library

Not stated by the source

Parameters

1.6B parameters

Languages

Not stated by the source

Revision

51f752b4fc3d0e74ee23de20331c2d0de5be7104

First published

2026-08-29

Last updated

2026-09-30

## Files and Weights

14 files, 3.2 GB in total. The weights are 2 files totalling 3.2 GB in bin, safetensors.

Weights2 files · 3.2 GB

Configuration6 files · 95.1 KB

Tokenizer4 files · 4.1 MB

Documentation1 file · 2.1 KB

Repository1 file · 1.5 KB

Every file

| File | Type | Size | SHA-256 |
| --- | --- | --- | --- |
| model.safetensors | Weights | 3.2 GB | 43654bf0bd75 |
| training_args.bin | Weights | 6.9 KB | baeef663a1d4 |
| added_tokens.json | Configuration | 34.6 KB | — |
| config.json | Configuration | 1.3 KB | — |
| generation_config.json | Configuration | 3.9 KB | — |
| normalizer.json | Configuration | 52.7 KB | — |
| preprocessor_config.json | Configuration | 340 B | — |
| special_tokens_map.json | Configuration | 2.2 KB | — |
| README.md | Documentation | 2.1 KB | — |
| .gitattributes | Repository | 1.5 KB | — |
| merges.txt | Tokenizer | 493.9 KB | — |
| tokenizer.json | Tokenizer | 2.5 MB | — |
| tokenizer_config.json | Tokenizer | 282.8 KB | — |
| vocab.json | Tokenizer | 835.5 KB | — |

## License and Download

License

apache-2.0

Access

Open weights, no gate

Download size

3.2 GB

[Download from Andoni Sudupe](https://huggingface.co/Ansu/whisper-large-v3-basque)

Released by Andoni Sudupe through its official repository on Hugging Face. [Read the license](https://www.apache.org/licenses/LICENSE-2.0).

## Built From

- Derived from [openai/whisper-large-v3](https://savrn.com/models/whisper-large-v3)

## Memory Requirements

| Precision | Weights in memory |
| --- | --- |
| As published | 3.2 GB |
| 16-bit | 3.2 GB |
| 8-bit | 1.6 GB |
| 4-bit | 0.8 GB |

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

## Questions About whisper-large-v3-basque

### How much GPU memory does whisper-large-v3-basque need?

About 3.9 GB at 16-bit and 1 GB at 4-bit: the weights (1.6B parameters) plus a working margin. A long context needs more.

### What is the cheapest GPU to run whisper-large-v3-basque 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 whisper-large-v3-basque commercially?

Yes. whisper-large-v3-basque 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.

## Andoni Sudupe

[All models and datasets](https://savrn.com/model-publishers/ansu)

## Versions

- [51f752b4fc3d](https://savrn.com/models/whisper-large-v3-basque/versions/51f752b4fc3d) · current 2026-09-30

## Explore More

- [All models under apache-2.0](https://savrn.com/models/licenses/apache-2-0)
- [Model comparisons](https://savrn.com/models/comparisons)
- [The model directory](https://savrn.com/models)
- [Open model prices by host](https://savrn.com/ai-index/pricing/open-models)

## Source

- Repository metadata, read 2026-09-30.
- [Hugging Face record](https://huggingface.co/Ansu/whisper-large-v3-basque)
- [How the hub is built](https://savrn.com/model-hub/methodology)