Cohere vs Faraday Machines

Cohere is a Canadian AI company building for large enterprises and government — with $100K+ contracts, defense partnerships, and a model that scored 37 on the Artificial Analysis Intelligence Index at launch (pre-v4.3). Faraday Machines gives SMBs open-weight AI on-premises — DeepSeek V4.1 Flash, GLM-5.3-Flash, Qwen3.8-27B, MiMo-V2.6-Flash and MiniMax M3, with Kimi K3 and GLM-5.3 on larger setups.

Key takeaways

  • Cohere’s private deployment, model customization, dedicated support and SLAs require an annual enterprise commitment of $100K or more, out of reach for most small and mid-sized businesses.
  • Cohere Command A+ scored 37 on the Artificial Analysis Intelligence Index at its May 2026 launch (pre-v4.3); on v4.3.2, Artificial Analysis lists it at an estimated 13.
  • Cohere’s default SaaS hosting runs on Google Cloud in US-Central, and on its SaaS platform, training on customer prompts is opt-out rather than opt-in.
  • Faraday Machines sells on-premises AI to small and mid-sized businesses from $299 US a month on a 36-month plan, including hardware and support, running models such as DeepSeek V4.1 Flash and GLM-5.3-Flash.
  • Cohere merged with Germany’s Aleph Alpha in April 2026, a deal that deepens its focus on governments, defense and large enterprises rather than small businesses.

October 2026 update

This page was published on May 29, 2026. The Intelligence Index scores in it (Command A+ 37, Kimi K2.6 54 and so on) come from the Artificial Analysis index as it stood in May–June 2026, before v4.3. Since then:

  • Artificial Analysis rescaled its index with v4.3 (announced September 7, 2026). Every model's score dropped, so May scores can't be compared with current ones.
  • On v4.3.2, Artificial Analysis lists Command A+ at 13, marked as an estimate pending independent evaluation. Command A+ is still Cohere's latest model: its changelog calls it the last in the Command A family, and no successor has shipped.
  • Faraday Machines now ships DeepSeek V4.1 Flash, GLM-5.3-Flash (42 on v4.3), Qwen3.8-27B, MiMo-V2.6-Flash (38) and MiniMax M3. Kimi K3 (44) and GLM-5.3 (45) are available on larger setups.

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?

$100K+
Annual commitment required for Cohere's key enterprise features — private deployment, model customization, dedicated support, and SLAs
37
Cohere Command A+'s score on the Artificial Analysis Intelligence Index at launch (May 2026, pre-v4.3), on par with Claude 4.5 Haiku at the time. On v4.3.2, AA lists an estimated 13
$240M
In Canadian federal funding for Cohere to train AI models domestically — your tax dollars, but not your product

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. At launch, Command A+ scored 37 on the Artificial Analysis Intelligence Index (pre-v4.3) — roughly equivalent to Claude 4.5 Haiku, a model designed for speed over depth. Compare that to the models Faraday Machines shipped in May 2026, scored on the same pre-v4.3 index:

54
Kimi K2.6 — Pre-v4.3 Intelligence Index score; at the time #8 overall and the #1 open-weights reasoning model. 17 points ahead of Command A+.
52
DeepSeek V4 Pro — Pre-v4.3 Intelligence Index score; then the #2 open-weights model. 15 points ahead. Also led on GDPval-AA agentic tasks (1554 vs Command A+'s 85).
51
GLM-5.1 — Pre-v4.3 Intelligence Index score. 14 points ahead of Command A+, with the best cost-efficiency on the benchmark at the time and strong agentic performance.
37
Command A+ — Pre-v4.3 Intelligence Index score. Tied with Claude 4.5 Haiku. Trailed every model Faraday Machines shipped in May 2026 by 14–17 points.

On the benchmarks that matter most for business reasoning, the gap at launch was even starker:

Agentic Work: 85% vs 1,554

Command A+ scores 85% on τ²-Bench Telecom (agentic tasks). DeepSeek V4 Pro scores 1,554 on GDPval-AA — the benchmark measuring real-world agentic task performance. These aren't comparable scales, but both measure multi-step reasoning and tool use. Command A+ is functional; the models Faraday shipped at the time were competitive with leading proprietary offerings.

Hard Science: ~11% on HLE

On Humanity's Last Exam — testing expert-level reasoning across domains — Command A+ scores approximately 11%. Kimi K2.6 and DeepSeek V4 Pro scored significantly higher at the time, giving you reasoning capability that Command A+ simply couldn't match.

Hallucination: 86% vs 94-96%

Command A+ achieves 86% on the AA-Omniscience Non-Hallucination benchmark. DeepSeek V4 Pro scores 94% and DeepSeek V4 Flash scores 96%. When accuracy matters for your business, every percentage point of hallucination reduction counts.

Coding: 25% vs Frontier

Command A+ scores 25% on Terminal-Bench Hard (agentic coding). DeepSeek V4 scores 93.5% on LiveCodeBench. If your team uses AI for development work, Command A+ wasn't in the same league as what Faraday Machines could run for you at publication.

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? At publication, every model Faraday Machines shipped — Kimi K2.6, Qwen 3.6, GLM-5.1, DeepSeek V4 — outperformed Command A+ by 14 to 17 points on the pre-v4.3 Intelligence Index. Settling for a model that scored 37 because it's from a Canadian company doesn't make competitive sense when better models are available on Canadian-hosted hardware you control.

Since then, the picture has moved again. Artificial Analysis rescaled its index with v4.3, and on v4.3.2 it lists Command A+ at 13 — an estimate, pending independent evaluation, so treat any gap to it with caution. The open models Faraday ships today include GLM-5.3-Flash at 42 and MiMo-V2.6-Flash at 38 on v4.3, with Kimi K3 (44) and GLM-5.3 (45) available on larger setups. Faraday's lineup has turned over completely since May. Cohere's has not: Command A+ is still its latest model, and Cohere calls it the last of the Command A family.

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:

Training Is Opt-Out, Not Opt-In

On Cohere's SaaS platform, your prompts and generations may be used for model training by default. Enterprise customers must actively toggle off training in dashboard settings. If you miss that setting, your proprietary data feeds their next model.

No Independently Verified Certifications

ThirdProof's 2026 vendor risk assessment flagged Cohere as Tier 3 (Moderate Risk). Their SOC 2 is vendor-attested only — no public registry exists for independent verification. No FedRAMP, no HIPAA certification for SaaS products, no independently verified ISO 27001.

Safety Team Can Review Your Data

Even when opted out of training, Cohere's safety team may review your flagged prompts and generations. Their privacy policy reserves the right to retain data for abuse detection and policy enforcement — your proprietary information, reviewed by humans you don't employ.

US-Based Default Infrastructure

Cohere's default SaaS hosting runs on Google Cloud in US-Central. Your data traverses US infrastructure under the CLOUD Act by default. Private deployment on AWS or Azure requires enterprise commitments and implementation effort that most SMBs can't provide.

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:

Cohere compared with Faraday Machines
Consideration Cohere Faraday Machines
Pricing Enterprise contracts start at $100K+/year Transparent pricing, no enterprise lock-in
Private deployment Private deployment requires enterprise sales On-premises by default — data never leaves your network
Self-serve setup No self-serve on-premises option Plug in and run — no DevOps team required
Integration Requires internal AI/developer team for integration Pre-configured AI applications ready to use
Data residency Default SaaS routes data through US cloud Canadian data stays in Canada, under Canadian law
Model training Training opt-out is a toggle you have to find No data training — architecture prevents it
Ecosystem Smaller ecosystem, fewer integrations Choose from frontier open-weight models
HIPAA compliance No HIPAA compliance for SaaS products —
Target customer Built for organizations with dedicated security teams Built for businesses without dedicated AI teams
Model lineup — Run DeepSeek V4.1 Flash, GLM-5.3-Flash, Qwen3.8-27B, MiMo-V2.6-Flash and MiniMax M3 — Kimi K3 and GLM-5.3 on larger setups

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:

Privacy Without Complexity

You shouldn't need a dedicated security team and a $100K contract to keep your data private. On-premises AI makes privacy the default state, not a premium feature you pay extra for.

The Best Open Models, Not Just the Local One

Choosing a model because it's from a Canadian company puts patriotism ahead of competitiveness. Command A+ scored 37 on the pre-v4.3 index at launch, and Artificial Analysis now estimates it at 13 on v4.3.2. GLM-5.3-Flash scores 42 on v4.3 and fits a single Faraday Scale machine at 4-bit, with DeepSeek V4.1 Flash, Qwen3.8-27B, MiMo-V2.6-Flash and MiniMax M3 also on the menu.

No Vendor Lock-In

Cohere's private deployment locks you into their platform, their API, and their model roadmap. On Faraday Machines, you choose which models to run — and swap them whenever a better one comes along. No migration, no renegotiation, no dependency.

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.

Frequently Asked Questions

How much does Cohere cost for a small business?

Cohere’s key enterprise features, including private deployment, model customization, dedicated support and SLAs, require an annual commitment of $100K or more. Smaller businesses typically get the SaaS product, hosted on Google Cloud in US-Central by default. Faraday Machines sells on-premises AI on 36-month plans at $299 US a month (Starter), $599 (Growth) and $999 (Scale), including hardware, updates, maintenance and support for the full term.

Is Cohere’s data hosted in Canada?

Not by default. Although Cohere is a Canadian company, its default SaaS hosting runs on Google Cloud in US-Central, so data sent through it traverses US infrastructure subject to the CLOUD Act. Private deployment on AWS or Azure requires an enterprise commitment. With Faraday Machines, the AI runs on hardware in your own office, so your data never leaves the building.

Does Cohere train on my data?

It can, unless you opt out. On Cohere’s SaaS platform, prompts and generations may be used for model training by default, and customers must switch training off in dashboard settings. Even with training disabled, Cohere’s privacy policy lets its safety team review flagged prompts and generations. On-premises AI from Faraday Machines processes data only on hardware in your office, so it never reaches a vendor’s training pipeline.

Is Cohere Command A+ as good as other open-source models?

Not on Artificial Analysis’s benchmarks. Cohere Command A+ scored 37 on the Intelligence Index at its May 2026 launch, 14 to 17 points behind the open models Faraday Machines shipped then. On the rescaled v4.3.2 index, Artificial Analysis lists it at an estimated 13, pending independent evaluation, while GLM-5.3-Flash scores 42. Command A+ is Apache 2.0 licensed and offers native citation grounding and 48 languages.

References

[1] Artificial Analysis. (2026). "Cohere launches open weights model Command A+." Available at: artificialanalysis.ai

[2] VentureBeat. (2026). "Cohere cracks lossless quantization and native citations with Command A+." Available at: venturebeat.com

[3] TechCrunch. (2026). "Why Cohere is merging with Aleph Alpha." Available at: techcrunch.com

[4] Government of Canada. (2025). "Canada partners with Cohere to accelerate world-leading artificial intelligence." Available at: canada.ca

[5] ThirdProof. (2026). "Is Cohere Safe? Vendor Risk Report." Available at: thirdproof.ai

[6] Cohere. (2025). "Enterprise Data Commitments." Available at: cohere.com

[7] FourWeekMBA. (2026). "The $5.5B Anti-OpenAI: How Cohere's Enterprise Strategy Just Proved Everyone Wrong." Available at: fourweekmba.com

[8] The Logic. (2026). "Cohere lands significant AI deal with federal innovation department." Available at: thelogic.co

[9] Artificial Analysis. (2026). "Intelligence Index Leaderboard." Available at: artificialanalysis.ai

[10] Artificial Analysis. (2026). "DeepSeek is back among the leading open weights models with V4 Pro and V4 Flash." Available at: artificialanalysis.ai

[11] The AI World. (2026). "Cohere-Aleph Alpha Merge at $20B Valuation." Available at: theaiworld.org

[12] Cohere. (2026). "Command A+ changelog." Available at: docs.cohere.com

[13] Artificial Analysis. (2026). "Cohere models." Available at: artificialanalysis.ai

[14] Artificial Analysis. (2026). "Artificial Analysis Intelligence Index v4.3." Available at: artificialanalysis.ai

[15] Artificial Analysis. (2026). "GLM-5.3-Flash." Available at: artificialanalysis.ai

These Organizations Run Open-Weight Models in Production

The model families Faraday Machines runs — DeepSeek, Qwen, GLM, Kimi, MiniMax and MiMo — power real workloads at real organizations. From Fortune 500 development teams to sovereign AI infrastructure.

Cursor
Cursor
Composer built on Kimi K2.5
Alibaba
Alibaba
90,000+ Qwen deployments
BMW Group
BMW Group
On-premises AI production
Samsung
Samsung
On-premises AI factory
NVIDIA
NVIDIA
NIM platform · GLM-5.1
Goldman Sachs
Goldman Sachs
Llama for banker assistance
Spotify
Spotify
Llama for recommendations
Cisco
Cisco
Llama & Mistral for security copilots
Dell Technologies
Dell Technologies
On-prem GenAI infrastructure
Accenture
Accenture
Enterprise AI with Llama

Get Frontier AI Without the Enterprise Price Tag

Run DeepSeek V4.1 Flash, GLM-5.3-Flash, Qwen3.8-27B, MiMo-V2.6-Flash and MiniMax M3 on Faraday Machines — on-premises, sovereign, and without a $100K contract. Your data stays on your hardware, under Canadian law.

Schedule Consultation
Already using Cohere? See how Faraday Machines adds the edge advantage →
Free security assessment and deployment guidance