Cohere vs Faraday Machines

Cohere: Built for Government, Not for You

Cohere is one of Canada's most prominent AI companies. Valued at $7 billion as of September 2025, backed by $240 million in federal funding, and now merging with Germany's Aleph Alpha at a combined $20 billion valuation — Cohere has made its positioning unmistakably clear. They build AI for governments and large enterprises, not for small and medium businesses.

Their client list tells the story: Oracle, Dell, SAP, Salesforce, McKinsey, Accenture. Their government contracts span Canada's Communications Security Establishment (CSE), Innovation Science and Economic Development Canada (ISED), and defense partnerships with Hanwha, Saab, Thales, and TKMS. In April 2026, the Canadian federal government deployed Cohere's North platform to 1,400 civil servants.

This is impressive work. But it leaves a question: where does that leave your business?

Command A+: Open Source, Not Frontier

In May 2026, Cohere released Command A+ — a 218 billion parameter sparse MoE model (25B active per token), released under the Apache 2.0 license. It's a legitimate contribution to the open-source ecosystem. Native citation grounding, 48-language support, and efficient W4A4 quantization that runs on just two H100 GPUs are real engineering achievements.

But open source doesn't mean frontier. Command A+ scores 37 on the Artificial Analysis Intelligence Index — roughly equivalent to Claude 4.5 Haiku, a model designed for speed over depth. Compare that to the models you can run today on Faraday Machines hardware:

On the benchmarks that matter most for business reasoning, the gap is even starker:

Here's the important part: Command A+'s Apache 2.0 license means you can run it on your own hardware. But why would you? Every model Faraday Machines ships — Kimi K2.6, Qwen 3.6, GLM-5.1, DeepSeek V4 — outperforms Command A+ by 14 to 17 points on the Intelligence Index. Settling for the 37th-ranked model because it's from a Canadian company doesn't make competitive sense when better models are available on Canadian-hosted hardware you control.

The Data Privacy Gap You Didn't Expect

Cohere markets itself as the privacy-conscious, sovereign AI alternative. Their enterprise data commitments page highlights private cloud deployment, zero data retention options, and 30-day auto-deletion. For large enterprises with dedicated security teams, these controls are meaningful. But the details tell a more complicated story:

The irony is sharp. Cohere positions itself as Canada's sovereign AI champion — yet the default deployment path routes your data through US servers, subject to US surveillance law. And their most privacy-protective features — private cloud, zero data retention, custom fine-tuning — are locked behind enterprise pricing that starts at $100,000 per year.

For an SMB, this means either paying enterprise prices for the privacy controls you need, or accepting a SaaS deployment where your data trains their models by default and traverses US infrastructure. Neither option puts you in control.

The SMB Gap: What Cohere Doesn't Offer

Cohere's product design reflects its customer base. The features that matter most to SMBs — easy deployment, self-serve pricing, ready-made applications — are precisely what Cohere doesn't prioritize. Here's what the gap looks like in practice:

Canadian Company, Canadian Contracts — But Not Canadian Data Sovereignty for SMBs

Cohere is Canadian. That's meaningful — and we respect what they've built. The federal government's $240 million investment in Cohere signals that Canada takes AI sovereignty seriously. The merger with Aleph Alpha creates a Canadian-German alliance that could reshape European defense and government AI procurement.

But sovereignty for governments is not sovereignty for your business. When a Toronto law firm routes client documents through Cohere's SaaS, that data hits US-Central Google Cloud infrastructure by default — subject to the same CLOUD Act surveillance authority we outlined in our Canadian AI sovereignty analysis. When a Vancouver e-commerce company fine-tunes a Cohere model on customer purchasing patterns, that data may train Cohere's next release — unless they remembered to toggle the opt-out setting.

The Canadian government can negotiate a bespoke deployment with dedicated infrastructure, custom SLAs, and a data processing agreement that binds Cohere to specific sovereignty commitments. You can't. SMBs get the SaaS product, with its default US hosting, default training opt-in, and enterprise-gated privacy controls.

Data sovereignty isn't a feature you unlock at higher pricing tiers. It's an architectural property. On Faraday Machines, your data physically never leaves your building. No US cloud, no opt-out toggles, no safety team reviews. The hardware enforces what Cohere can only promise in a contract you can't afford.

The Merger Changes Nothing for SMBs

Cohere's April 2026 merger with Aleph Alpha — backed by both the Canadian and German governments — reinforces their trajectory. The combined entity targets defense, energy, finance, healthcare, manufacturing, telecommunications, and the public sector. Schwarz Group (owner of Lidl) invested €500 million and will provide cloud infrastructure via STACKIT.

This is a company building AI for nation-states and the Fortune 500. The merger doesn't create new SMB features, self-serve pricing, or simplified deployment. It deepens their commitment to the sovereign AI market — a market defined by $100 million government contracts, defense procurement, and enterprise-scale private cloud deployments.

If anything, the merger widens the gap. Cohere-Aleph Alpha's combined resources will go toward winning European defense contracts and building custom models for SAP and Oracle — not toward making their platform accessible to a 50-person marketing agency in Calgary or a 200-employee manufacturer in Kitchener.

What SMBs Actually Need from AI

The conversation about AI for business often conflates what large enterprises need with what SMBs need. They're not the same:

The best AI for your business is the one that keeps your data sovereign, delivers frontier performance, and doesn't require an enterprise contract to get started. That's the gap Faraday Machines was built to fill.

References

These Organizations Run Open-Weight Models in Production

The models Faraday Machines ships — Kimi, DeepSeek, Qwen, GLM — power real workloads at real organizations. From Fortune 500 development teams to sovereign AI infrastructure.

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Composer built on Kimi K2.5

Alibaba

90,000+ Qwen deployments

BMW Group

On-premises AI production

Samsung

On-premises AI factory

NVIDIA

NIM platform · GLM-5.1

Goldman Sachs

Llama for banker assistance

Spotify

Llama for recommendations

Cisco

Llama & Mistral for security copilots

Dell Technologies

On-prem GenAI infrastructure

Accenture

Enterprise AI with Llama