AX Gemma 4 12B IT MLX QAT OptiQ 4-bit Assistant MTP
3
8 commits
1 linked in READMEs
updated Jul 23, 2026
Parameter count: approximately 11.96B logical target parameters (12B class).
4-bitis the target quantization precision, not a 4B model-size claim. The separately packaged assistant is an acceleration component and is not included in the target count.
This is a self-contained MLX package for Apple Silicon. It combines the pinned upstream QAT OptiQ target with its paired 4-bit Gemma assistant for AX Engine multi-token prediction (MTP) / speculative decoding.
Try this model locally with AX Engine.
AutomatosX did not train Gemma 4, produce the QAT checkpoint, create the
OptiQ quantization, or train the assistant. The target comes from
mlx-community/gemma-4-12B-it-qat-OptiQ-4bit
at revision 63912b888c04ba2c555f198685d10b05f54cf564. The assistant comes from
mlx-community/gemma-4-12B-it-qat-assistant-4bit
at revision 37ae18bbbc2c569d1c9ff6a5ca9359051f522df4.
AutomatosX packaged the pinned target and assistant together, normalized the
assistant model_type for the AX runtime, generated native manifests, and
added the exact-pairing contract. The target tokenizer is applied to the
assistant subtree so both sides use identical token IDs. The target and
assistant weights themselves are unchanged. The upstream OptiQ card is
preserved as UPSTREAM_README.md.
No new training or benchmark results are claimed by AutomatosX.
| Property | Value |
|---|---|
| Target format | MLX Safetensors |
| Official QAT base | google/gemma-4-12B-it-qat-q4_0-unquantized |
| Target quantization | OptiQ mixed 4/8-bit, group size 64 |
| OptiQ allocation | 171 components at 4-bit; 157 at 8-bit |
| Achieved target BPW | 5.2453 |
| Assistant precision | 4-bit affine, group size 64 |
| Pairing | Exact |
| Maximum draft depth | 2 |
| Configured context | 262,144 tokens |
| Intended hardware | Apple Silicon |
hf download AutomatosX/AX-Gemma-4-12B-IT-MLX-QAT-OptiQ-4bit-Assistant-MTP \
--local-dir ./AX-Gemma-4-12B-IT-MLX-QAT-OptiQ-4bit-Assistant-MTP
ax-engine doctor \
--mlx-model-artifacts-dir ./AX-Gemma-4-12B-IT-MLX-QAT-OptiQ-4bit-Assistant-MTP
ax-engine serve ./AX-Gemma-4-12B-IT-MLX-QAT-OptiQ-4bit-Assistant-MTP --port 31418
The download is approximately 8.7 GB. AX Engine reads
ax_gemma4_assistant_mtp.json, loads the drafter from assistant/, and uses
the target model to verify every accepted token. Do not use assistant/ by
itself as a general-purpose chat model.
The server exposes an OpenAI-compatible API. Consult the AX Engine repository for installation and API examples.
Validated on macOS arm64 with AX Engine 6.9.0 on 2026-07-20:
ready, with no model issuesexactSee ax_provenance.json for immutable source revisions, transformations, and
artifact hashes.
Quantization can change model quality, and speculative-decoding acceptance depends on the workload. Evaluate this package on your own tasks.
Apache License 2.0. See LICENSE, the
Gemma 4 license page, and
the official Google model cards for limitations and responsible-use guidance.
8 commits
AX Gemma 4 12B IT MLX QAT OptiQ 4-bit Assistant MTP
3
8 commits
1 linked in READMEs
updated Jul 23, 2026
Parameter count: approximately 11.96B logical target parameters (12B class).
4-bitis the target quantization precision, not a 4B model-size claim. The separately packaged assistant is an acceleration component and is not included in the target count.
This is a self-contained MLX package for Apple Silicon. It combines the pinned upstream QAT OptiQ target with its paired 4-bit Gemma assistant for AX Engine multi-token prediction (MTP) / speculative decoding.
Try this model locally with AX Engine.
AutomatosX did not train Gemma 4, produce the QAT checkpoint, create the
OptiQ quantization, or train the assistant. The target comes from
mlx-community/gemma-4-12B-it-qat-OptiQ-4bit
at revision 63912b888c04ba2c555f198685d10b05f54cf564. The assistant comes from
mlx-community/gemma-4-12B-it-qat-assistant-4bit
at revision 37ae18bbbc2c569d1c9ff6a5ca9359051f522df4.
AutomatosX packaged the pinned target and assistant together, normalized the
assistant model_type for the AX runtime, generated native manifests, and
added the exact-pairing contract. The target tokenizer is applied to the
assistant subtree so both sides use identical token IDs. The target and
assistant weights themselves are unchanged. The upstream OptiQ card is
preserved as UPSTREAM_README.md.
No new training or benchmark results are claimed by AutomatosX.
| Property | Value |
|---|---|
| Target format | MLX Safetensors |
| Official QAT base | google/gemma-4-12B-it-qat-q4_0-unquantized |
| Target quantization | OptiQ mixed 4/8-bit, group size 64 |
| OptiQ allocation | 171 components at 4-bit; 157 at 8-bit |
| Achieved target BPW | 5.2453 |
| Assistant precision | 4-bit affine, group size 64 |
| Pairing | Exact |
| Maximum draft depth | 2 |
| Configured context | 262,144 tokens |
| Intended hardware | Apple Silicon |
hf download AutomatosX/AX-Gemma-4-12B-IT-MLX-QAT-OptiQ-4bit-Assistant-MTP \
--local-dir ./AX-Gemma-4-12B-IT-MLX-QAT-OptiQ-4bit-Assistant-MTP
ax-engine doctor \
--mlx-model-artifacts-dir ./AX-Gemma-4-12B-IT-MLX-QAT-OptiQ-4bit-Assistant-MTP
ax-engine serve ./AX-Gemma-4-12B-IT-MLX-QAT-OptiQ-4bit-Assistant-MTP --port 31418
The download is approximately 8.7 GB. AX Engine reads
ax_gemma4_assistant_mtp.json, loads the drafter from assistant/, and uses
the target model to verify every accepted token. Do not use assistant/ by
itself as a general-purpose chat model.
The server exposes an OpenAI-compatible API. Consult the AX Engine repository for installation and API examples.
Validated on macOS arm64 with AX Engine 6.9.0 on 2026-07-20:
ready, with no model issuesexactSee ax_provenance.json for immutable source revisions, transformations, and
artifact hashes.
Quantization can change model quality, and speculative-decoding acceptance depends on the workload. Evaluate this package on your own tasks.
Apache License 2.0. See LICENSE, the
Gemma 4 license page, and
the official Google model cards for limitations and responsible-use guidance.
8 commits