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[KK] Load DS4.1 and Kimi-K3 lossless X4T checkpoints - #949
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Register exact_mxfp4 loading for compressed expert scales while retaining native dense and draft precision and file-backed Engram tables. Reuse serialized scale scratch and reject unsupported parallel execution modes. Preserve EXL3 prepared-weight validation and validate the SwiGLU clamp. Validation: 122 X4T, EXL3, and loader-registry tests pass with B12X #446. New code passes mypy; the five existing model.py findings reproduce on the KK base. Full-model serving evidence is linked in the companion B12X PR. Co-authored-by: OpenAI Codex <noreply@openai.com> Signed-off-by: Martin Vit <martin@voipmonitor.org>
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Preserve BF16 dense weights, select SiTU expert activation, recognize nested checkpoint metadata and bound CPU shard-copy threads. Shared scale scratch remains serialized; PP and ubatching are rejected. Port the implementation qualified on TP16 without changing native MXFP4 arithmetic. Co-authored-by: OpenAI Codex <noreply@openai.com> Signed-off-by: Martin Vit <martin@voipmonitor.org>
Co-authored-by: OpenAI Codex <noreply@openai.com>
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Closing as not needed: no shipped docker model uses the DS4.1/Kimi-K3 X4T loaders. DeepSeek-V4.1 is served from its lossless MXFP4-CSF checkpoint. It can be reopened if X4T checkpoints become a target again. |
Behavior
Load DeepSeek V4.1 and Kimi-K3 lossless X4T checkpoints through B12X. X4T compresses MXFP4 scale grids without changing the weight nibbles or W4A16 arithmetic; it is not two-bit Trellis quantization.
Requires B12X #446.
--load-format exact_mxfp4. Use--quantization exact_mxfp4for DS4.1 or--quantization kimi_x4tfor Kimi-K3.Set
quantization_config.format_version=1andcheckpoint_rootto the absolute mounted X4T directory. Kimi uses the same metadata in its nested text configuration. Native MXFP4 and EXL3 checkpoint paths are unchanged.Compatibility
SM120/SM121, BF16 expert activations. Reader geometry: DS4.1 TP1/2/4/8; Kimi TP1/2/4/8/12/16. Qualified full-model topologies: DS4.1 TP4 and Kimi TP16. Other topologies are implemented geometry, not serving qualifications.
PP, ubatching, EP, DP and expert remapping are unsupported. Shared scratch requires serialized execution on one CUDA stream. No native CUDA extension, speculative algorithm or KV representation is added.
Validation
tests/quantization/test_ds41_exact_mxfp4.pyandtests/quantization/test_exl3.py. Coverage includes nested Kimi metadata, BF16 dense preservation, SiTU selection, thread restoration, compressed expert filtering, DS4.1 Engram and EXL3 invariants. The earlier DS4.1-only qualification also included loader-registry tests (122 total).0x400prevents an unthrottled performance qualification. CUTLASS 4.6.2 was used for the full-model run; no 4.7.1 full-model claim is made.Full-model KLD and 1M-token generation are not qualified. AI assistance: OpenAI Codex. Review requested for checkpoint identity, serialized scratch ownership and Kimi activation selection.