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+ ---
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+ license: other
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+ license_name: bcz-proprietary
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+ license_link: https://huggingface.co/sprappcom/kat-coder-v25-dev-pqm/blob/main/NOTICE
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+ language:
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+ - en
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+ tags:
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+ - moe
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+ - code
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+ - tool-calling
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+ - gated-deltanet
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+ - pqm
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+ - prism-engine
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+ - q4_k
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+ base_model: Kwaipilot/KAT-Coder-V2.5-Dev
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+ ---
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+
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+ # kat-coder-v25-dev-pqm
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+
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+ Standalone **[Kwaipilot/KAT-Coder-V2.5-Dev](https://huggingface.co/Kwaipilot/KAT-Coder-V2.5-Dev)**
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+ (clean upstream code / tool-calling model, Qwen3.6-35B-A3B MoE) exported to `.pqm`
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+ for the `prism-engine` inference server. **GGUF-free standalone boot** — this single
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+ `.pqm` container is self-contained and boots directly on `prism-engine`, with no
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+ GGUF, safetensors, or transformers checkpoint alongside it.
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+
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+ ## License & attribution
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+
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+ This repository distributes a **composite work** under a dual arrangement:
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+
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+ - **Proprietary layer — © 2026 BCZ Singapore Pte Ltd. All rights reserved.**
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+ The `.pqm` container format and packaging, and the `prism-engine` inference server
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+ (Rust/CUDA) are proprietary and are **not** licensed under Apache-2.0.
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+ - **Base model weights — Apache-2.0.** The underlying weights are an **unmodified**
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+ (repacked-only) derivative of a single Apache-2.0 upstream:
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+
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+ | Component | Source | Copyright | License | Modification |
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+ |---|---|---|---|---|
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+ | Full model (backbone + experts) | [Kwaipilot/KAT-Coder-V2.5-Dev](https://huggingface.co/Kwaipilot/KAT-Coder-V2.5-Dev) | © 2026 Kwaipilot / Kuaishou | Apache-2.0 | weights repacked to `.pqm` (mixed Q4_K/Q6_K/F32); no fine-tune, no merge |
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+
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+ `KAT-Coder-V2.5-Dev` (the open Apache-2.0 weights, itself Qwen3.6-35B-A3B-based) — **not**
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+ the separate closed API-only "KAT-Coder" product. These base weights remain licensed under
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+ **Apache-2.0**. The full Apache-2.0 license text and per-component attribution are in the
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+ [`NOTICE`](https://huggingface.co/sprappcom/kat-coder-v25-dev-pqm/blob/main/NOTICE) file
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+ in this repo.
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+
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+ This is **not** an original, trained-from-scratch foundation model — it is a
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+ quantized repack of the Apache-2.0 upstream named above. Use of the base weights is
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+ governed by Apache-2.0; use of the proprietary `.pqm` packaging and `prism-engine`
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+ requires a separate license from BCZ Singapore Pte Ltd.
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+
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+ ## Requirements — read before downloading
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+
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+ - **Inference engine:** `.pqm` is a proprietary container, **not** readable by vLLM,
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+ llama.cpp, Ollama, or transformers. Runs only on `prism-engine` (proprietary
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+ Rust/CUDA server, **not included in this repo**). Contact sprappcom for engine access.
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+ - **Tokenizer sidecar:** `.pqm` does **not** embed a tokenizer. Use the `kat_v25.tok`
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+ shipped in this repo via `PRISMX_TOKENIZER`.
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+ - **Hardware:** A100 (sm_80) / Ada-Ampere (sm_86/sm_89) validated. Full residency ~20 GB
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+ VRAM, or run with CPU-RAM expert offload on smaller cards.
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+
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+ ## Architecture
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+
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+ - Qwen3.6-35B-A3B MoE, hidden_size=2048, 40 layers (30 Gated DeltaNet + 10 full attention)
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+ - 256 routed experts + 1 shared expert, top-8 routing
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+ - vocab_size=248320
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+
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+ ## Quantization
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+
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+ | Tensor group | Type |
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+ |---|---|
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+ | token embedding, attn_qkv/attn_output/attn_gate, routed experts (ffn_*_exps) | Q4_K |
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+ | shared expert (ffn_*_shexp), output.weight | Q6_K |
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+ | norms, SSM gates | F32 |
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+
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+ ~4.56 BPW. Container ~39.9 GB (routed experts stored raw for CPU-offload support).
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+
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+ ## Usage
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+
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+ ```bash
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+ export PRISMX_PQM_STANDALONE=1
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+ export PRISMX_PQM=/path/to/kat_v25.pqm
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+ export PRISMX_TOKENIZER=/path/to/kat_v25.tok
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+ prism_server 0.0.0.0:8080 \
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+ --n-cpu-moe 28 \
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+ --max-prefill-chunk 8 \
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+ --moe-cache-experts 2048 \
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+ --max-batch 1
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+ ```
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+
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+ Standalone mode always binds `0.0.0.0:8080`. OpenAI-compatible `/v1/completions` and
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+ `/v1/chat/completions`. Use `temperature >= 0.15` (greedy decoding can collapse).
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+
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+ ## Verification
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+
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+ Boot-verified GGUF-free on A100 (sm_80) with `prism_server`
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+ (`PRISMX_PQM_STANDALONE=1 --n-cpu-moe 28 --max-prefill-chunk 8 --moe-cache-experts 2048
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+ --max-batch 1`, tokenizer `kat_v25.tok` from this repo): coherent English code and
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+ tool-calling completions, no NaN/garbage output.
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+
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+ ## Known limitations
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+
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+ - **Text-only.** This `.pqm` carries no vision weights; image input is available on the
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+ separate AWQ variant, not this file.
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+ - Intermittent sub-word token drop/duplication on some code/arithmetic prompts is a
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+ known open issue; validate structured output downstream.
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+
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+ ## Integrity
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+
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+ | File | Bytes | SHA-256 |
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+ |---|---|---|
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+ | `kat_v25.pqm` | 39870623744 | `0050a596155bee84d162148a3e9248099f2dc838c41dca1391eb5a33ef693b15` |
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+ | `kat_v25.tok` | 8949400 | md5 `907b88ec3a1f5aed0e234472eb441520` |
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+
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+ Check: `sha256sum kat_v25.pqm` must print the hash above.