---
license: other
license_name: bcz-proprietary
license_link: https://huggingface.co/sprappcom/kat-coder-v25-dev-pqm/blob/main/NOTICE
language:
  - en
tags:
  - moe
  - code
  - tool-calling
  - gated-deltanet
  - pqm
  - prism-engine
  - q4_k
base_model: Kwaipilot/KAT-Coder-V2.5-Dev
---

# kat-coder-v25-dev-pqm

Standalone **[Kwaipilot/KAT-Coder-V2.5-Dev](https://huggingface.co/Kwaipilot/KAT-Coder-V2.5-Dev)**
(clean upstream code / tool-calling model, Qwen3.6-35B-A3B MoE) exported to `.pqm`
for the `prism-engine` inference server. **GGUF-free standalone boot** — this single
`.pqm` container is self-contained and boots directly on `prism-engine`, with no
GGUF, safetensors, or transformers checkpoint alongside it.

## License & attribution

This repository distributes a **composite work** under a dual arrangement:

- **Proprietary layer — © 2026 BCZ Singapore Pte Ltd. All rights reserved.**
  The `.pqm` container format and packaging, and the `prism-engine` inference server
  (Rust/CUDA) are proprietary and are **not** licensed under Apache-2.0.
- **Base model weights — Apache-2.0.** The underlying weights are an **unmodified**
  (repacked-only) derivative of a single Apache-2.0 upstream:

  | Component | Source | Copyright | License | Modification |
  |---|---|---|---|---|
  | 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 |

  `KAT-Coder-V2.5-Dev` (the open Apache-2.0 weights, itself Qwen3.6-35B-A3B-based) — **not**
  the separate closed API-only "KAT-Coder" product. These base weights remain licensed under
  **Apache-2.0**. The full Apache-2.0 license text and per-component attribution are in the
  [`NOTICE`](https://huggingface.co/sprappcom/kat-coder-v25-dev-pqm/blob/main/NOTICE) file
  in this repo.

This is **not** an original, trained-from-scratch foundation model — it is a
quantized repack of the Apache-2.0 upstream named above. Use of the base weights is
governed by Apache-2.0; use of the proprietary `.pqm` packaging and `prism-engine`
requires a separate license from BCZ Singapore Pte Ltd.

## Requirements — read before downloading

- **Inference engine:** `.pqm` is a proprietary container, **not** readable by vLLM,
  llama.cpp, Ollama, or transformers. Runs only on `prism-engine` (proprietary
  Rust/CUDA server, **not included in this repo**). Contact sprappcom for engine access.
- **Tokenizer sidecar:** `.pqm` does **not** embed a tokenizer. Use the `kat_v25.tok`
  shipped in this repo via `PRISMX_TOKENIZER`.
- **Hardware:** A100 (sm_80) / Ada-Ampere (sm_86/sm_89) validated. Full residency ~20 GB
  VRAM, or run with CPU-RAM expert offload on smaller cards.

## Architecture

- Qwen3.6-35B-A3B MoE, hidden_size=2048, 40 layers (30 Gated DeltaNet + 10 full attention)
- 256 routed experts + 1 shared expert, top-8 routing
- vocab_size=248320

## Quantization

| Tensor group | Type |
|---|---|
| token embedding, attn_qkv/attn_output/attn_gate, routed experts (ffn_*_exps) | Q4_K |
| shared expert (ffn_*_shexp), output.weight | Q6_K |
| norms, SSM gates | F32 |

~4.56 BPW. Container ~39.9 GB (routed experts stored raw for CPU-offload support).

## Usage

```bash
export PRISMX_PQM_STANDALONE=1
export PRISMX_PQM=/path/to/kat_v25.pqm
export PRISMX_TOKENIZER=/path/to/kat_v25.tok
prism_server 0.0.0.0:8080 \
  --n-cpu-moe 28 \
  --max-prefill-chunk 8 \
  --moe-cache-experts 2048 \
  --max-batch 1
```

Standalone mode always binds `0.0.0.0:8080`. OpenAI-compatible `/v1/completions` and
`/v1/chat/completions`. Use `temperature >= 0.15` (greedy decoding can collapse).

## Verification

Boot-verified GGUF-free on A100 (sm_80) with `prism_server`
(`PRISMX_PQM_STANDALONE=1 --n-cpu-moe 28 --max-prefill-chunk 8 --moe-cache-experts 2048
--max-batch 1`, tokenizer `kat_v25.tok` from this repo): coherent English code and
tool-calling completions, no NaN/garbage output.

## Known limitations

- **Text-only.** This `.pqm` carries no vision weights; image input is available on the
  separate AWQ variant, not this file.
- Intermittent sub-word token drop/duplication on some code/arithmetic prompts is a
  known open issue; validate structured output downstream.

## Integrity

| File | Bytes | SHA-256 |
|---|---|---|
| `kat_v25.pqm` | 39870623744 | `0050a596155bee84d162148a3e9248099f2dc838c41dca1391eb5a33ef693b15` |
| `kat_v25.tok` | 8949400 | md5 `907b88ec3a1f5aed0e234472eb441520` |

Check: `sha256sum kat_v25.pqm` must print the hash above.