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Model Details
Model Provider
ProCogia
Model Tree
moonshotai/Kimi-K2.7-Code
Input Modalities
Output Modalities
Supported Functionality
Kimi K2.7 Code was chosen as the Enterprise base for three reasons:
| PolyKode Community | PolyKode Enterprise-Base (this repo) | PolyKode Enterprise | |
|---|---|---|---|
| Base weights | Qwen3-32B | Kimi K2.7 Code | Kimi K2.7 Code + proprietary adapters |
| PolyKode SFT / RLVR training | ❌ | ❌ | ✅ Included |
| Execution-parity harness | ❌ | ❌ | ✅ Full harness |
| SAS 9.4 / Viya certification | ❌ | ❌ | ✅ Included |
| SAS-exact numerical contract | ❌ | ❌ | ✅ Enforced |
| Audit trails | ❌ | ❌ | ✅ Generated per translation |
| Deployment | Self-serve HF | Self-serve HF | ZeroBoxx on-prem / sovereign cloud / dedicated endpoint |
| Support | Community | Community | Named engineering + product contact |
| License | Apache 2.0 | Modified MIT | ProCogia Enterprise EULA |
| Repo | PolyKode-Community | This repo | PolyKode-Enterprise |
If you are experimenting with PolyKode workflows or benchmarking, use Community (Qwen3-32B, Apache 2.0) or this Base (Kimi K2.7 Code, Modified MIT). If you need execution-parity certification, audit trails, and SLAs, engage on Enterprise.
This repository contains the unmodified upstream weights. All architectural, training, and evaluation details are the responsibility of Moonshot AI; refer to moonshotai/Kimi-K2.7-Code for the authoritative technical description.
Good fits:
Not intended for:
python
from transformers import AutoModelForCausalLM, AutoTokenizermodel_name = "ProCogia/PolyKode-Enterprise-Base"tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)model = AutoModelForCausalLM.from_pretrained(model_name,torch_dtype="auto",device_map="auto",trust_remote_code=True,)
For serving at scale we recommend vLLM or SGLang with appropriate tensor-parallel and expert-parallel settings for a ~1T-parameter MoE architecture. Contact ProCogia for a reference deployment for ZeroBoxx.
This model is a byte-identical republication of moonshotai/Kimi-K2.7-Code by Moonshot AI, released under the Modified MIT License. Only the repository branding, model card, and metadata differ; no weight modifications have been made in this release.
LICENSE)We are grateful to the Moonshot AI team for open-sourcing Kimi K2.7 Code under a permissive commercial license, making this Enterprise-Base distribution possible.
Licensed under the Modified MIT License. See LICENSE in this repository for the full text.
Key terms:
The UI attribution requirement inherits to downstream users of this repository. If your deployment plausibly meets the thresholds above, plan for that UI treatment; contact your legal team if unsure.
If you use PolyKode Enterprise-Base in research, cite both the upstream Kimi work and PolyKode:
bibtex
@misc{kimi_k27_code,title = {Kimi K2.7 Code},author = {Moonshot AI},year = {2026},url = {https://huggingface.co/moonshotai/Kimi-K2.7-Code}}@misc{polykode2026enterprisebase,title = {PolyKode Enterprise-Base: coding-agent base checkpoint for regulated code translation},author = {ProCogia},year = {2026},url = {https://huggingface.co/ProCogia/PolyKode-Enterprise-Base}}
ProCogia · Founded 2013 · Headquartered in Vancouver, British Columbia · SOC 2 Type 1 attested · This release is byte-identical to moonshotai/Kimi-K2.7-Code. Upstream license is preserved; the UI-attribution threshold clause applies to all downstream users.