In a bold move poised to reshape the AI infrastructure landscape, Meta announced a landmark partnership with Cerebras Systems to supercharge its new Llama API—offering developers inference speeds up to 18 times faster than traditional GPU-based platforms.
Unveiled at Meta’s inaugural LlamaCon developer conference in Menlo Park, the collaboration signals Meta’s official entry into the competitive AI inference services market—an arena dominated by OpenAI, Google, and Anthropic—where developers purchase tokens by the millions to power their AI-driven applications.
“Meta has selected Cerebras to collaborate to deliver the ultra-fast inference that they need to serve developers through their new Llama API,” said Julie Shin Choi, Chief Marketing Officer at Cerebras. “We’re thrilled to announce our first CSP hyperscaler partnership.”
Meta’s Shift from Open Source to AI Infrastructure Powerhouse
This announcement represents a strategic pivot for Meta. While its Llama models have seen over a billion downloads as open-source offerings, the company had yet to offer a cloud-based platform to serve these models—until now. With the Llama API, Meta transforms its widely adopted models into a commercial AI service.
“Meta is now in the business of selling tokens,” said James Wang, a senior executive at Cerebras. “And it’s great for the broader AI ecosystem in the U.S.”
The Llama API will initially launch with the Llama 3.3 8B model, providing developers with tools for fine-tuning, training, and evaluation. Meta has emphasized strong data privacy, stating it won’t use customer data to train its models. Unlike competitors, developers will retain the flexibility to migrate their custom models to other hosts.
Cerebras Delivers Lightning-Fast Inference
At the heart of this leap in performance is Cerebras’ wafer-scale engine, designed specifically for AI workloads. Benchmarks presented by Artificial Analysis show that Cerebras processes Llama 4 at an astounding 2,648 tokens per second—leaving other providers far behind. For comparison, Groq manages 600 tokens per second, SambaNova hits 747, and traditional GPU-based solutions from major cloud players struggle to exceed 130 tokens per second.
“100 tokens per second might be fine for basic chat,” Wang noted. “But for agents, reasoning, and real-time applications, it’s too slow.”
This massive speed improvement enables new classes of applications—from real-time agents and voice interfaces to interactive code generation and complex reasoning chains that once took minutes but can now run in seconds.
Powered by Cerebras' North American Data Center Network
Cerebras will support Meta’s Llama API across its network of data centers in North America—including locations in Dallas, Oklahoma, Minnesota, Montreal, and California. Choi described the partnership as a classic hyperscaler arrangement, with Meta reserving significant compute capacity across Cerebras' infrastructure.
“All of our inference-serving data centers are currently in North America,” Choi said. “Meta will be utilizing the full capacity of our compute.”
Meta also revealed a partnership with Groq, providing developers with multiple fast-inference options and further reinforcing its commitment to performance diversity.
Redefining the AI Inference Market
Meta’s entry into the inference market with cutting-edge performance could disrupt the established dominance of OpenAI and Google. By merging open-source accessibility with ultra-fast inference, Meta sets itself apart from closed systems with slower response times.
“Meta has the trifecta—3 billion users, hyperscale data centers, and a vast developer ecosystem,” Cerebras noted in its presentation. “With Cerebras, Meta leapfrogs OpenAI and Google in inference performance by up to 20x.”
For Cerebras, the partnership is a milestone achievement that validates years of hardware innovation aimed at hyperscale AI deployment.
“We’ve built this wafer-scale engine with the goal of reaching hyperscale cloud integration,” Wang said. “This is that moment.”
How Developers Can Get Started
The Llama API is currently available as a limited preview, with a wider release coming soon. Developers can request early access and select Cerebras as the preferred inference engine directly through Meta’s SDK.
“Just two clicks,” said Wang. “Generate an API key, select the Cerebras flag—and your tokens are being processed on a giant wafer-scale engine.”
The Future of AI is Measured in Milliseconds
With this announcement, Meta has signaled a new era in AI—where performance isn’t just an added benefit, but the foundation of the entire experience. As the demand for real-time AI capabilities grows, Meta and Cerebras are betting that faster thinking machines will define the next frontier of innovation.
In the race to build the future of AI, Meta isn’t just catching up—it’s setting the pace.
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