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Meta’s Llama API Hits 18x Speed via Cerebras partnership

Meta’s Llama API Hits 18x Speed via Cerebras partnership

Meta’s Llama API boosted by Cerebras for ultra-fast AI inference speed.

Meta has officially entered the AI inference market by partnering with Cerebras Systems. Announced during its first LlamaCon developer conference, the tech giant unveiled its new Llama API, which will offer inference speeds up to 18 times faster than standard GPU solutions. This move directly positions Meta against rivals like OpenAI, Google, and Anthropic.

Unlike traditional cloud services, Meta’s API leverages Cerebras’ specialized chips to drastically boost token processing speeds. According to performance benchmarks, Cerebras can process Llama 4 at a blazing 2,648 tokens per second far exceeding competitors like SambaNova and Groq. As a result, developers can now run complex, multi-step reasoning tasks in seconds instead of minutes.

This performance advantage opens the door to applications that were previously impractical. Real-time voice assistants, interactive coding tools, and responsive AI agents now become viable thanks to the speed Cerebras provides. While ChatGPT runs at roughly 130 tokens per second, Meta’s solution, by contrast, redefines expectations for AI speed.

A New Revenue Stream for Meta’s AI Ambitions

Previously known for offering open-source models, Meta is now transitioning to a full-scale AI infrastructure provider. Through its new Llama API, the company aims to monetize its popular models while maintaining its open-access philosophy. According to executives, Meta’s goal is to provide developers with scalable, commercial-grade tools without restricting portability.

In fact, developers using the API will be able to fine-tune, train, and evaluate custom models. Meta has emphasized it won’t use customer data to train its own models marking a distinct stance from some closed-platform competitors.

Cerebras will handle the back-end processing through a network of North American data centers. These facilities spanning Dallas, Montreal, Minnesota, and more ensure load balancing and stable performance across regions. Additionally, Meta has partnered with Groq to offer further inference speed options, giving developers more flexibility.

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Graphic representation of the Gemini 2.5 model with the name "Gemini 2.5" displayed prominently in white against a dark background featuring blue geometric shapes and lines.

Speed, Not Just Intelligence, Becomes the Differentiator

By combining the popularity of Llama with Cerebras’ speed, Meta may be reshaping the landscape of commercial AI. Industry observers see this as a potential disruption to incumbents like OpenAI and Google. With over 3 billion users and vast infrastructure, Meta is well-positioned to scale fast.

Cerebras, for its part, views the deal as validation of its long-term chip strategy. Years of wafer-scale development have culminated in this hyperscale breakthrough. Developers can now access the preview version of the Llama API, simply by selecting Cerebras as their preferred model option.

Ultimately, Meta’s pivot to speed-driven inference suggests a deeper truth: in the AI future, how fast a model can reason may matter just as much as what it knows.

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