Canada's open-weight model lab. We train, quantize, and deploy sovereign AI on Canadian Blackwell silicon — for the regulated industries that can't run on someone else's API.
Public capital is flowing through every layer of the Canadian AI stack — data centres, compute subsidies, defence platforms, sovereign cloud. The one layer that's empty is the one where the IP actually lives.
Canada is investing $2 billion in sovereign AI. The country has no model lab.
Every dollar today flows through closed APIs, telco-hosted metal, or thin wrapper layers. Cohere just open-weighted Command A+ — a Canadian foundation worth building on. The layer above it — vertical-specialized, audited, customer-owned — is still unoccupied.
We're not a wrapper. Not a hosting platform. Not a fine-tuning API. We take frontier open base models and produce shippable, quantized, sovereign deployments — with the IP and audit evidence customers actually own.
Post-training on open base models. SFT, DPO, GRPO, RLAIF. Customer data stays sovereign throughout the run.
Production W4A16, NVFP4, MXFP4 recipes — with MTP draft heads preserved so speculative decoding survives end-to-end. Patches land upstream in vLLM and llm-compressor.
Air-gapped, on-prem, sovereign cloud. With audit trails, eval evidence, and model risk documentation packaged with the build.
We're starting wide. The verticals will narrow themselves as contracts land — not as we pretend to know. Each one has a clear buyer set, a clear corpus, and a clear wedge against frontier general models.
Hallucination floors below frontier models on Canadian case law.
On-prem deployable, PHIPA/PIPEDA-clean, evidence-cited outputs.
Air-gapped, classified-ready, doctrine-aware, Five Eyes interoperable.
OSFI-aligned, MRM-documented, audit-ready, on Canadian soil.
Sovereign AI in Canada has shifted from policy paper to active deployment in under twelve months. The first lab to ship audited, vertical, open-weight models with defence contracts behind them owns the category.
Frontier-tier open models — 600B+ parameter MoEs, long-context dense models — need real Blackwell silicon to train and serve at production scale. We operate it here.
What we've put on Hugging Face under open licenses — and what we're calibrating next. Plus an invitation: if there's a model your team needs quantized in the open, we'd like to hear about it.
The first NVFP4-FP8 quant of DeepSeek-V4-Pro with the MTP draft head preserved for vLLM speculative decoding. A byte-deterministic conversion of V4-Pro's native MXFP4+FP8 source to NVFP4 on 8× B300 SXM6 — shipped alongside the upstream vLLM patch that makes the flashinfer_trtllm NVFP4 MoE backend load it, merged the same day.
A W4A16 + FP8_BLOCK quant of DeepSeek-V4-Flash that keeps the MTP draft head at BF16 — the first build on this base where speculative decoding survives end-to-end through GPTQ calibration, transformers save, and vLLM load on Hopper. The reproduction repo documents three upstream silent-drop bugs and the fixup pipeline that routes around them.
Datacenter-Blackwell NVFP4 build of DeepSeek-V4-Flash with the MTP draft head retained on-disk, so vLLM serves it with --speculative-config method=mtp end-to-end. Same quant math as the comparable peer; the structural difference is that MTP survives calibration instead of being stripped at load time.
A W4A16 + FP8_BLOCK quant of DeepSeek-V4-Flash with a vLLM serving recipe. Runs on Hopper (H200) and two Blackwell SKUs (DGX Spark, RTX PRO 6000), built alongside the upstream patches it depends on. Open weights, no token required.
Each lands on Hugging Face under the base model's license when it's ready. Status updates: partnerships@cql.ca.
We ship one or two community quants per cycle. We're looking for:
First-look review within two weeks. Selected requests get a public reproduction repo and a model card under canada-quant/.
If your organization needs a model it can audit, deploy on-prem, and keep under Canadian jurisdiction — we should talk. We respond to every serious inquiry within 48 hours.
Or email partnerships@cql.ca · press@cql.ca directly.