Atlassian co-founder and CEO Mike Cannon-Brookes said in an interview published October 12, 2026, “We don’t use any Chinese models in production. We’re very clear about that.” It is a direct statement from the CEO, not a published model inventory: the interview does not define “Chinese model,” list the models covered, or provide independent evidence of Atlassian’s production deployments.
What Cannon-Brookes said
The statement came in an interview with 20VC host Harry Stebbings, in a discussion titled “Enterprise Trust Shapes Model Choices.” Stebbings said he was concerned that enterprises might not want to work with “largely Chinese open models” and asked how Atlassian viewed that issue. Cannon-Brookes replied that the company makes model choices in response to customers.
As an Amazon Associate I earn from qualifying purchases.
He said: “We want to be very customer-led in our decision-making, and there is certainly some customer pushback in some places to, quote-unquote, Chinese models. There is no customer pushback to open models.” The distinction matters: in his account, some customers object to models described as Chinese, but that does not amount to a general objection to open models.
Recommended Free Tools
The transcript does not establish how widespread that customer pushback is, which customers raised it, or whether it has led to particular deployment decisions. The claim that Atlassian uses no Chinese models in production should therefore be read as Cannon-Brookes’s account, not as an independently verified company-wide finding. Read the interview transcript.
#1 Best Overall
- Built for Local AI Development: AMD Ryzen AI Halo is designed for local AI development and inference, featuring 128GB unified memory and support for up to 200B parameter models to build and run intensive AI workloads locally.
- 128GB Unified Memory: Features 128GB LPDDR5x unified memory at 8000 MT/s with 256 GB/s memory bandwidth, providing a shared memory pool across the CPU, GPU, and NPU to support larger AI models.
- AMD Ryzen AI Max+ 395 Processor: Features 16 cores, 32 threads, and Zen 5 architecture, paired with AMD Radeon 8060S integrated graphics featuring 40 RDNA 3.5 compute units and an AMD XDNA 2 NPU with up to 50 TOPS.
- Linux AI Developer Platform: Purpose-built for Linux-based AI development with full AMD ROCm software support and preloaded tools, models, and workflows optimized for local AI development.
- Compact, Connected Design: Includes a 2TB M.2 SSD, 10GbE LAN, Wi-Fi 7, Bluetooth 5.4, USB-C connectivity, and HDMI 2.1b.
Open models are not the same as models of a particular origin
Cannon-Brookes named Nemotron and Mistral as examples of open models used in different parts of Atlassian’s platform. He did not describe their deployment details or say that they account for all of the company’s model use. His broader explanation was that Atlassian aims to choose models for customer outcomes rather than to commit to one model or category.
“Our job, again, is to apply AI on behalf of our customers. It’s not to pick a model. It’s to use the best model for the best job, blending all the models for the best price for the customer and to get the outcome they want, right? Applying the AI is our job,” he said.
Rank #2
- EVOLUTION AMD RYZEN AI MAX+ 395 MINI PC - GMKtec EVO-X2 is the next evolution in AI mini PC Ryzen Strix Halo series. Thanks to AMD Simultaneous Multithreading (SMT) the core-count is effectively doubled, to 32 threads. Ryzen AI Max+ 395 has 64 MB of L3 cache and can boost up to 5.1 GHz, depending on the workload. The Ryzen AI Max+ 395 is currently rated as the "most powerful x86 APU" on the market for AI computing.
- AI NPU with XDNA 2 ARCHITECTURE - Powered by 16 “Zen 5” CPU cores, 50+ peak AI TOPS XDNA 2 NPU and a truly massive integrated GPU driven by 40 AMD RDNA 3.5 CUs, the Ryzen AI MAX+ 395 is a transformative upgrade and delivers a significant performance boost over the competition. The Ryzen AI Max+ 395 excels in consumer AI workloads like the llama.cpp-powered application: LM Studio. Shaping up to be the must-have app for client LLM workloads, LM Studio allows users to locally run the latest language model without any technical knowledge required and unleash their creativity and productivity.
- AMD RADEON 8090S iGPU GAMING PC - The AMD Radeon RX 8060S offers all 40 CUs with up to 2.9 GHz graphics clock and uses the new RDNA 3.5 architecture. The powerful iGPU is positioned between an RTX 4060 and 4070 laptop GPU and therefore enables gaming in FHD at maximum details in most demanding games. The 8060S can also utilize the full 64GB pool, which is perfect for running LLMs such as Deepseek 32B, which runs comfortably on this machine.
- EIGHT CHANNEL LPDDR5X - LPDDR5X is a new ground breaking memory small form factor installed on-board. With blazing speeds up to to 8000MT/s, it runs 1.5x faster than the DDR5 SODIMMs; 90% better performance over DDR5 SODIMMs in video conferencing and photo editing; 30% better performance in productivity apps; 4% better performance in digital content workloads.
- QUAD SCREEN 8K DISPLAY SUPPORT - EVO-X2 AI Mini PC support 4-screen 4K/8K output via HDMI 2.1 (8K@60Hz), DisplayPort 1.4 (4K@60Hz), and dual USB 4 40Gbps Transfer speed (supporting PD3.0/DP1.4/DATA). Ideal for gaming, video editing, and multitasking, it provides expansive and crisp multi-display support.
The interview also leaves “Chinese model” undefined. Cannon-Brookes distinguished questions about where a model was trained or the nationality of its developers from questions about strategic control: “That is a different issue from whether we should use a model that was trained in China or by Chinese nationals or by someone—these are very different questions, if you know what I mean.” He did not offer a classification rule for deciding which models fall under the label.
What Atlassian’s Forge announcement does—and does not—show
Atlassian’s July 29, 2026 announcement said its Forge LLMs API had become generally available. The company said the API runs on Amazon Bedrock and that app data stays within Atlassian’s cloud boundary. It also described Claude model tiers available through Bedrock at that time. This is useful context about a developer API, but it does not establish that Bedrock is the sole provider for Atlassian’s own production products or verify the CEO’s broader statement.
Rank #3
- Intel Core Ultra 9 285 Processor: Newly developed cores deliver ultra-smooth and responsive gameplay. AI accelerators prepare users for the next era of gaming on an AI PC.
- Simplistic Design: Enjoy the latest generation of Windows 11 Home for your everyday needs. *MSI recommends Windows 11 Pro for business use.
- NVIDIA GeForce RTX 5070 Ti GPU
- Cool While Gaming: In conjunction with an RGB CPU Air Cooler, the Aegis RS features four system cooling fans; three in the front and one in the rear to pull in cool air and push heat out of the PC.
- Turn on the Bright Lights: With the built-in RGB lighting, take your gaming experience to the next level by pressing the MSI LED button to cycle through lighting options. Customize lighting even further with MSI Center software.
Atlassian reported that more than 100 apps using Forge LLMs had launched in production since Preview, including 20 public Marketplace apps, and that more than 350 additional apps were in development. Those are company-reported Forge adoption figures as of July 29, 2026; they are not counts of Atlassian’s full production model inventory. Read Atlassian’s Forge LLMs announcement.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What enterprise buyers can take from the statement
The interview signals that customer sensitivity to model origin is part of Atlassian’s stated model-selection considerations, alongside price and performance. It does not answer how Atlassian or a buyer should classify a model, or provide a comparison of specific models. Organizations assessing AI services can make the question more concrete by checking:
- Provenance: What does “origin” mean for the organization’s policy—where a model was developed, trained, hosted, or controlled?
- Inference and operation: Where does inference run, and which provider operates the service?
- Data boundary: What customer data leaves the product or platform boundary, and under what terms?
- Contractual limits: Do customer agreements or internal rules restrict particular providers, regions, or model types?
- Use-case fit: How do quality, latency, and cost compare for the specific task?
- Delivery model: Is the option open-weight, fine-tuned, or available only as a hosted API?
These are diligence questions, not conclusions about any model’s safety or suitability. The CEO’s interview does not evaluate individual models against them.
Quick wins for a faster PC:
Repair Windows errors before they cause bigger problemsFix Now →Scan for outdated or missing drivers - takes under a minuteDriver Scan →Clear out junk files and repair common Windows errorsFree Scan →Quick Recap
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
