--- license: apache-2.0 base_model: Nanbeige/Nanbeige4.2-3B base_model_relation: quantized pipeline_tag: text-generation library_name: coreai tags: - coreai - apple-silicon - recurrent-transformer - text-generation - quantized - int8 --- # Nanbeige4.2-3B — Core AI INT8 **INT8 weight-quantized Core AI LanguageBundle** converted from [`Nanbeige/Nanbeige4.2-3B`](https://huggingface.co/Nanbeige/Nanbeige4.2-3B), pinned to source revision [`5ff54fb7ed86ce8e216d78bff5417ab9981de3d4`](https://huggingface.co/Nanbeige/Nanbeige4.2-3B/tree/5ff54fb7ed86ce8e216d78bff5417ab9981de3d4). This is a Core AI `.aimodel` bundle for Apple silicon. It is not a Transformers, GGUF, or MLX checkpoint. Ported by [Vadim Smirnov (@ukint-vs)](https://github.com/ukint-vs). Source, reproducible conversion recipe, parity gates, and the optimization report are tracked in [john-rocky/coreai-model-zoo#5](https://github.com/john-rocky/coreai-model-zoo/issues/5). ## Format | Property | Value | |---|---| | Published variant | **INT8 only** | | Body weights | int8, per-block 32 (`int8hu`) | | Untied LM head | symmetric absmax int8, per-block 32 (`--head-sym`) | | Activations / KV cache | fp16 | | Decode input | static sequence length 1 (`--static-ids`) | | Bundle size | approximately 4.59 GiB | | Verified context | 4,096 tokens | The int4 and mixed int4/int8 candidates failed the reasoning quality gate and are intentionally not published. ## Architecture Nanbeige4.2 is a looped Llama: **22 physical transformer blocks execute twice**, with RMS normalization after each pass and independent KV history. The bundle therefore has **44 executed/cache layers while storing and quantizing one copy of the 22 physical blocks**. ## Bundle The complete LanguageBundle is at: ```text gpu-pipelined/ nanbeige4_2_3b_decode_int8hu_block32_sym_s1/ metadata.json nanbeige4_2_3b_decode_int8hu_block32_sym_s1.aimodel/ tokenizer/ ``` The embedded tokenizer includes the vendor `chat_template.jinja` with thinking enabled and disabled modes. The `.aimodel` producer is `coreai-core 1.0.0b2`. ## Verification - Official checkpoint vs Core AI authoring: float32 full and cached logits pass `rtol=1e-4`, `atol=1e-4`; identical 32-token greedy continuation. - Quantized Core AI engine: token-exact vs fp32 on 24-token Paris, 16-token freezing-point, and 64-token decimal-reasoning gates. - M4 Max Release benchmark, prompt 128 / generation 256 / 3 runs: **47.37 prefill / 46.35 decode tok/s**. - 4,096-token boundary: **29.83 prefill / 32.80 decode tok/s**, 9.17 GiB peak RSS, zero swaps. - iPhone `h18p` device acceptance is pending; no iPhone performance claim is made. ## License The source model and converted weights are distributed under Apache-2.0. Conversion code in `coreai-model-zoo` is BSD-3-Clause.