Highlights

Keras has a new model distillation API!

You now have access to an easy-to-use API for distilling large models into small models while minimizing performance drop on a reference dataset -- compatible with all existing Keras models. You can specify a range of different distillation losses, or create your own losses. The API supports multiple concurrent distillation losses at the same time.

Example:

# Load a model to distill
teacher = ...
# This is the model we want to distill it into
student = ...

# Configure the process
distiller = Distiller(
    teacher=teacher,
    student=student,
    distillation_losses=LogitsDistillation(temperature=3.0),
)
distiller.compile(
    optimizer='adam',
    loss='sparse_categorical_crossentropy',
    metrics=['accuracy']
)

# Train the distilled model
distiller.fit(x_train, y_train, epochs=10)

Keras supports GPTQ quantization!

GPTQ is now built into the Keras API. GPTQ is a post-training, weights-only quantization method that compresses a model to int4 layer by layer. For each layer, it uses a second-order method to update weights while minimizing the error on a calibration dataset.

Learn how to use it in this guide.

Example:

model = keras_hub.models.Gemma3CausalLM.from_preset("gemma3_1b")
gptq_config = keras.quantizers.GPTQConfig(
    dataset=calibration_dataset,
    tokenizer=model.preprocessor.tokenizer,
    weight_bits=4,
    group_size=128,
    num_samples=256,
    sequence_length=256,
    hessian_damping=0.01,
    symmetric=False,
    activation_order=False,
)
model.quantize("gptq", config=gptq_config)
outputs = model.generate(prompt, max_length=30)

Better support for Grain datasets!

• Add Grain support to keras.utils.image_dataset_from_directory and keras.utils.text_dataset_from_directory. Specify format="grain" to return a Grain dataset instead of a TF dataset.
• Make almost all Keras preprocessing layers compatible with Grain datasets.

New features

• Add keras.layers.ReversibleEmbedding layer: an embedding layer that can also also project backwards to the input space. Use it with the reverse argument in call().
• Add argument opset_version in model.export(). Argument specific to format="onnx"; specifies the ONNX opset version.
• Add keras.ops.isin op.
• Add keras.ops.isneginf, keras.ops.isposinf ops.
• Add keras.ops.isreal op.
• Add keras.ops.cholesky_inverse op and add upper argument in keras.ops.cholesky.
• Add keras.ops.image.scale_and_translate op.
• Add keras.ops.hypot op.
• Add keras.ops.gcd op.
• Add keras.ops.kron op.
• Add keras.ops.logaddexp2 op.
• Add keras.ops.view op.
• Add keras.ops.unfold op.
• Add keras.ops.jvp op.
• Add keras.ops.trapezoid op.
• Add support for over 20 news ops with the OpenVINO backend.

Breaking changes

• Layers StringLookup & IntegerLookup now save vocabulary loaded from file. Previously, when instantiating these layers from a vocabulary filepath, only the filepath would be saved when saving the layer. Now, the entire vocabulary is materialized and saved as part of the .keras archive.

Security fixes

• Fix two vulnerabilities related to adversarial saved files loaded with safe_mode: CVE-2025-12058 and CVE-2025-12060.

New Contributors

• @WIgor made their first contribution in https://github.com/keras-team/keras/pull/21432
• @ILCSFNO made their first contribution in https://github.com/keras-team/keras/pull/21563
• @samthakur587 made their first contribution in https://github.com/keras-team/keras/pull/21524
• @buildwithsuhana made their first contribution in https://github.com/keras-team/keras/pull/21554
• @MCCbena made their first contribution in https://github.com/keras-team/keras/pull/21569
• @amitsrivastava78 made their first contribution in https://github.com/keras-team/keras/pull/21551
• @Ma-gi-cian made their first contribution in https://github.com/keras-team/keras/pull/21614
• @arunthakur009 made their first contribution in https://github.com/keras-team/keras/pull/21600
• @vpratz made their first contribution in https://github.com/keras-team/keras/pull/21615
• @miguelteixeiragomes made their first contribution in https://github.com/keras-team/keras/pull/21650
• @Flakes342 made their first contribution in https://github.com/keras-team/keras/pull/21646
• @TRNWWZ made their first contribution in https://github.com/keras-team/keras/pull/21671
• @danielenricocahall made their first contribution in https://github.com/keras-team/keras/pull/21738
• @utsab345 made their first contribution in https://github.com/keras-team/keras/pull/21721
• @wenyi-guo made their first contribution in https://github.com/keras-team/keras/pull/21763
• @SamKnightGit made their first contribution in https://github.com/keras-team/keras/pull/21782

Full Changelog: https://github.com/keras-team/keras/compare/v3.11.0...v3.12.0