diff --git a/.gitattributes b/.gitattributes
index a6344aac8c09253b3b630fb776ae94478aa0275b..af0905e028c53403d622387e8ba41666fd819978 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -33,3 +33,35 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
*.zip filter=lfs diff=lfs merge=lfs -text
*.zst filter=lfs diff=lfs merge=lfs -text
*tfevents* filter=lfs diff=lfs merge=lfs -text
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+de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507_timestamped/decoder_model_attentive.onnx_data filter=lfs diff=lfs merge=lfs -text
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+de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/onnx/audio_encoder_fp16.onnx_data filter=lfs diff=lfs merge=lfs -text
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+de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/onnx/audio_encoder_quantized.onnx_data filter=lfs diff=lfs merge=lfs -text
+de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/onnx/audio_encoder_uint8.onnx_data filter=lfs diff=lfs merge=lfs -text
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+de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/onnx/embed_tokens.onnx_data filter=lfs diff=lfs merge=lfs -text
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diff --git a/de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/.gitattributes b/de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/.gitattributes
new file mode 100644
index 0000000000000000000000000000000000000000..f8fcc1f7aa7268a01d8375c562dc195df6f0ae28
--- /dev/null
+++ b/de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/.gitattributes
@@ -0,0 +1,65 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
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+onnx/decoder_model_merged.onnx_data_1 filter=lfs diff=lfs merge=lfs -text
+onnx/decoder_model_merged.onnx_data_2 filter=lfs diff=lfs merge=lfs -text
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+tekken.json filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text
+onnx/audio_encoder.onnx_data filter=lfs diff=lfs merge=lfs -text
+onnx/audio_encoder.onnx_data_1 filter=lfs diff=lfs merge=lfs -text
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diff --git a/de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/README.md b/de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..a8e4046e3cb6280e8b0e65c1a2620db4bc1ccb4a
--- /dev/null
+++ b/de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/README.md
@@ -0,0 +1,178 @@
+---
+language:
+- en
+- fr
+- de
+- es
+- it
+- pt
+- nl
+- hi
+license: apache-2.0
+library_name: transformers.js
+base_model:
+- mistralai/Voxtral-Mini-3B-2507
+pipeline_tag: audio-text-to-text
+---
+
+# Voxtral Mini 1.0 (3B) - 2507
+
+Voxtral Mini is an enhancement of [Ministral 3B](https://mistral.ai/news/ministraux), incorporating state-of-the-art audio input capabilities while retaining best-in-class text performance. It excels at speech transcription, translation and audio understanding.
+
+This repository contains ONNX weights for the original model, [mistralai/Voxtral-Mini-3B-2507](https://huggingface.co/mistralai/Voxtral-Mini-3B-2507).
+
+Learn more about Voxtral in their blog post [here](https://mistral.ai/news/voxtral).
+
+## Key Features
+
+Voxtral builds upon Ministral-3B with powerful audio understanding capabilities.
+- **Dedicated transcription mode**: Voxtral can operate in a pure speech transcription mode to maximize performance. By default, Voxtral automatically predicts the source audio language and transcribes the text accordingly
+- **Long-form context**: With a 32k token context length, Voxtral handles audios up to 30 minutes for transcription, or 40 minutes for understanding
+- **Built-in Q&A and summarization**: Supports asking questions directly through audio. Analyze audio and generate structured summaries without the need for separate ASR and language models
+- **Natively multilingual**: Automatic language detection and state-of-the-art performance in the world’s most widely used languages (English, Spanish, French, Portuguese, Hindi, German, Dutch, Italian)
+- **Function-calling straight from voice**: Enables direct triggering of backend functions, workflows, or API calls based on spoken user intents
+- **Highly capable at text**: Retains the text understanding capabilities of its language model backbone, Ministral-3B
+
+## Benchmark Results
+
+### Audio
+
+Average word error rate (WER) over the FLEURS, Mozilla Common Voice and Multilingual LibriSpeech benchmarks:
+
+
+
+### Text
+
+
+
+## Usage
+
+**Notes**:
+
+- `temperature=0.2` and `top_p=0.95` for chat completion (*e.g. Audio Understanding*) and `temperature=0.0` for transcription
+- Multiple audios per message and multiple user turns with audio are supported
+- System prompts are not yet supported
+
+
+### Transformers.js
+
+#### Online demo
+
+Try it out with our [online demo](https://huggingface.co/spaces/webml-community/Voxtral-WebGPU):
+
+
+
+
+#### Code snippets
+
+If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@huggingface/transformers) using:
+```bash
+npm i @huggingface/transformers
+```
+
+**Example**: Transcription
+
+```js
+import { VoxtralForConditionalGeneration, VoxtralProcessor, TextStreamer, read_audio } from "@huggingface/transformers";
+
+// Load the processor and model
+const model_id = "onnx-community/Voxtral-Mini-3B-2507-ONNX";
+const processor = await VoxtralProcessor.from_pretrained(model_id);
+const model = await VoxtralForConditionalGeneration.from_pretrained(
+ model_id,
+ {
+ dtype: {
+ embed_tokens: "fp16", // "fp32", "fp16", "q8", "q4"
+ audio_encoder: "q4", // "fp32", "fp16", "q8", "q4", "q4f16"
+ decoder_model_merged: "q4", // "q4", "q4f16"
+ },
+ device: "webgpu",
+ },
+);
+
+// Prepare the conversation
+const conversation = [
+ {
+ "role": "user",
+ "content": [
+ { "type": "audio" },
+ { "type": "text", "text": "lang:en [TRANSCRIBE]" },
+ ],
+ }
+];
+const text = processor.apply_chat_template(conversation, { tokenize: false });
+const audio = await read_audio("http://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/mlk.wav", 16000);
+const inputs = await processor(text, audio);
+
+// Generate the response
+const generated_ids = await model.generate({
+ ...inputs,
+ max_new_tokens: 256,
+ streamer: new TextStreamer(processor.tokenizer, { skip_special_tokens: true, skip_prompt: true }),
+});
+
+// Decode the generated tokens
+const new_tokens = generated_ids.slice(null, [inputs.input_ids.dims.at(-1), null]);
+const generated_texts = processor.batch_decode(
+ new_tokens,
+ { skip_special_tokens: true },
+);
+console.log(generated_texts[0]);
+// I have a dream that one day this nation will rise up and live out the true meaning of its creed.
+```
+
+
+**Example**: Audio understanding
+
+```js
+import { VoxtralForConditionalGeneration, VoxtralProcessor, TextStreamer, read_audio } from "@huggingface/transformers";
+
+// Load the processor and model
+const model_id = "onnx-community/Voxtral-Mini-3B-2507-ONNX";
+const processor = await VoxtralProcessor.from_pretrained(model_id);
+const model = await VoxtralForConditionalGeneration.from_pretrained(
+ model_id,
+ {
+ dtype: {
+ embed_tokens: "fp16", // "fp32", "fp16", "q8", "q4"
+ audio_encoder: "q4", // "fp32", "fp16", "q8", "q4", "q4f16"
+ decoder_model_merged: "q4", // "q4", "q4f16"
+ },
+ device: "webgpu",
+ },
+);
+
+// Prepare the conversation
+const conversation = [
+ {
+ "role": "user",
+ "content": [
+ { "type": "audio" },
+ { "type": "audio" },
+ { "type": "text", "text": "Describe these two audio clips in detail." },
+ ],
+ }
+];
+const text = processor.apply_chat_template(conversation, { tokenize: false });
+const audio = await Promise.all([
+ read_audio("https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav", 16000),
+ read_audio("https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/mlk.wav", 16000),
+]);
+const inputs = await processor(text, audio);
+
+// Generate the response
+const generated_ids = await model.generate({
+ ...inputs,
+ max_new_tokens: 256,
+ streamer: new TextStreamer(processor.tokenizer, { skip_special_tokens: true, skip_prompt: true }),
+});
+
+// Decode the generated tokens
+const new_tokens = generated_ids.slice(null, [inputs.input_ids.dims.at(-1), null]);
+const generated_texts = processor.batch_decode(
+ new_tokens,
+ { skip_special_tokens: true },
+);
+console.log(generated_texts[0]);
+// The first audio clip is a speech by a leader, likely a politician or a public figure, addressing a large audience. The speaker begins by encouraging the listeners to ask not what their country can do for them, but what they can do for their country. This is a call to action and a reminder of the individual's responsibility to contribute to the nation's well-being. The second audio clip is a passionate speech by a different leader, possibly a civil rights activist or a community organizer. This speaker expresses a dream of a nation that will rise up and live out the true meaning of its creed, suggesting a vision of a more just and equitable society.
+```
\ No newline at end of file
diff --git a/de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/chat_template.jinja b/de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/chat_template.jinja
new file mode 100644
index 0000000000000000000000000000000000000000..fb6c0234f1d67ada2beef214a0bca8e0c95778ba
--- /dev/null
+++ b/de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/chat_template.jinja
@@ -0,0 +1,28 @@
+{{- bos_token -}}
+{%- for message in messages -%}
+ {%- if (message["role"] == "user") == (loop.index % 2 == 0) -%}
+ {{- raise_exception("After the optional system message, conversation roles must alternate user/assistant/user/assistant/...") -}}
+ {%- endif -%}
+ {%- if message["role"] == "user" -%}
+ {{- "[INST]" -}}
+ {%- if message["content"] is string -%}
+ {{- message["content"] -}}
+ {%- else -%}
+ {%- for item in message["content"] -%}
+ {%- if item["type"] == "audio" -%}
+ {{- "[AUDIO]" -}}
+ {%- elif item["type"] == "text" -%}
+ {{- item["text"] -}}
+ {%- endif -%}
+ {%- endfor -%}
+ {%- endif -%}
+ {{- "[/INST]" -}}
+ {%- elif message["role"] == "assistant" -%}
+ {%- if message["content"] is not string -%}
+ {{- raise_exception("Assistant message content should be a string.") -}}
+ {%- endif -%}
+ {{- message["content"] + eos_token -}}
+ {%- else -%}
+ {{- raise_exception("Only user and assistant roles are supported!") -}}
+ {%- endif -%}
+{%- endfor -%}
\ No newline at end of file
diff --git a/de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/config.json b/de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/config.json
new file mode 100644
index 0000000000000000000000000000000000000000..979aecf6bbb46a7c058a4a7f95938a8f8945813c
--- /dev/null
+++ b/de,en,es,fr,hi,it,nl,pt/Voxtral-Mini-3B-2507-ONNX/config.json
@@ -0,0 +1,81 @@
+{
+ "architectures": [
+ "VoxtralForConditionalGeneration"
+ ],
+ "audio_config": {
+ "activation_dropout": 0.0,
+ "activation_function": "gelu",
+ "attention_dropout": 0.0,
+ "dropout": 0.0,
+ "head_dim": 64,
+ "hidden_size": 1280,
+ "initializer_range": 0.02,
+ "intermediate_size": 5120,
+ "layerdrop": 0.0,
+ "max_source_positions": 1500,
+ "model_type": "voxtral_encoder",
+ "num_attention_heads": 20,
+ "num_hidden_layers": 32,
+ "num_key_value_heads": 20,
+ "num_mel_bins": 128,
+ "scale_embedding": false,
+ "vocab_size": 51866
+ },
+ "audio_token_id": 24,
+ "hidden_size": 3072,
+ "model_type": "voxtral",
+ "projector_hidden_act": "gelu",
+ "text_config": {
+ "attention_bias": false,
+ "attention_dropout": 0.0,
+ "head_dim": 128,
+ "hidden_act": "silu",
+ "hidden_size": 3072,
+ "initializer_range": 0.02,
+ "intermediate_size": 8192,
+ "max_position_embeddings": 131072,
+ "mlp_bias": false,
+ "model_type": "llama",
+ "num_attention_heads": 32,
+ "num_hidden_layers": 30,
+ "num_key_value_heads": 8,
+ "pretraining_tp": 1,
+ "rms_norm_eps": 1e-05,
+ "rope_scaling": null,
+ "rope_theta": 100000000.0,
+ "sliding_window": null,
+ "use_cache": true,
+ "vocab_size": 131072
+ },
+ "torch_dtype": "bfloat16",
+ "transformers_version": "4.54.0.dev0",
+
+ "transformers.js_config": {
+ "dtype": {
+ "embed_tokens": "fp16"
+ },
+ "kv_cache_dtype": {
+ "q4f16": "float16",
+ "fp16": "float16"
+ },
+ "use_external_data_format": {
+ "audio_encoder.onnx": 2,
+ "audio_encoder_fp16.onnx": 1,
+ "audio_encoder_int8.onnx": 1,
+ "audio_encoder_uint8.onnx": 1,
+ "audio_encoder_quantized.onnx": 1,
+ "audio_encoder_q4.onnx": 1,
+ "audio_encoder_q4f16.onnx": 1,
+ "audio_encoder_bnb4.onnx": 1,
+ "decoder_model_merged.onnx": 8,
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