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Meta Announced partnership with today Cerebrum system To give strength to its new Lama APIDevelopers’ access increases rapidly than traditional GPU-based solutions.
Announced at the inauguration of Meta Lalmakon Developer Conference at Meno Park, deploys the company to compete directly Openi, anthropicAnd Google Rapidly growing AI Invention Service Market, where developers buy tokens by billions to provide electricity to their applications.
“Meta chose to cooperate to distribute the cerebras to distribute ultra-fast invention that he needs to serve the developers through his new Lama API,” said during a press briefing by Serbress Chief Marketing Officer Julie Shin Choi. “We are really excited to announce their first CSP hypersscaleer partnership to give ultra-fast invention to all developers in Cerebras.”
The partnership marks a formal entry into the business of selling Meta’s AI computation, converting its popular open-source Lama model into a commercial service. While the Lama models of the Meta are over A billion downloadTill now the company had not offered a first-sided cloud infrastructure to make applications with them for developers.
James Wang, a senior executive of Cerebrus, said, “It is very exciting, even without talking about cerealbra,” said James Wang, a senior executive of the cerebrace. “Openai, Anthropropic, Google – They have created a new AI business from scratches, which is AI Innerference Business. Developers who are building AI apps will sometimes buy tokens by millions by billions.
Breaking speed barrier: How Serbress Supercharge Lama Model
Meta distinguishes the offer of the offer that is the dramatic motion increased by special AI chips of cerebras. Cerebras system ends 2,600 tokens per second According to the benchmark, Lama for 4 Scouts, about 130 tokens per second per second for chat and about 25 tokens per second, according to the benchmark Artificial analysis,
“If you compare just API-to-API Aadhaar, Gemini and GPT, they are all great models, but they all walk on GPU speed, which is about 100 tokens per second,” Wang explained. “And 100 tokens per second are fine for chat, but it is very slow for logic. It is very slow for agents. And people are struggling with it today.”
This speed benefit enables the completely new categories of applications that were previously impractical, including real-time agents, conjunct low-oppression voice systems, interactive code generation, and instant multi-step Reasoning-all of which require many big language model calls that can now be completed in seconds instead of minutes.
Lama API Meta’s AI represents a significant change in strategy, mainly being a model provider infection to become a full-service AI infrastructure company. By offering the API service, Meta is creating a revenue stream from its AI investment, while maintaining its commitment to the open model.
Wang said during the press conference, “Meta is now in the business of selling tokens, and it is great for American types of AI ecosystems.” “They bring a lot to the table.”
API will provide equipment for fine-tuning and evaluation, starts with Lama 3.3 8B modelThe developers allow the developers to generate, train it and test the quality of their custom models. Meta emphasizes that it will not use customer data to train its own model, and the model manufactured using Lama API can be transferred to other hosts – a clear discrimination from the more closed approaches of some contestants.
Cerebras will power the new service of the meta through a network of data centers located across North America, including facilities in Dallas, Oklahoma, Minnesota, Montreal and California.
“All our data centers that are currently in North America are currently in North America,” Choi explained. “We will serve the meta with full capacity of cerebras. All these different data centers will be balanced.”
Business system is as such that Choi described as a model “Classic Compute Provider for a Hyperscaler”, similarly how NVidia provides hardware to major cloud providers. He said, “They are blocking our calculations that they can serve their developer population.”
Beyond the cerebras, Meta has also announced a partnership with Groke To provide rapid estimate options, the developers offer several high-performance options beyond traditional GPU-based estimates.
Entry of Meta into API market with better performance metrics can disrupt the order potentially established order Openi, GoogleAnd anthropicMeta commercial AI is creating itself as a malignant competitor in the commercial AI space, combining the popularity of its open-source model with dramatically fast estimates capabilities.
According to Serbress’s presentation material, “Meta is in a unique position with 3 billion users, hyper-scale datasters and a huge developer ecosystem.” Integration of cerebrous technology “Meta Leapfrog Helps Openi and Google performing about 20X.”
For cerebras, this partnership represents a major milestone and verification of its special AI hardware approach. “We have been manufacturing this wafer-scal engine over the years, and we always knew that the first rate of technology is, but eventually it would have to be finished as part of someone else’s hypersscale cloud.
Lama API Currently available as a limited preview, a comprehensive rollout planned in the coming weeks and months with meta. Developers Lalama, who are interested in reaching Ultra-Fast LLAMA 4 infection, can request an initial access by selecting cereal from model options within APIs.
“If you imagine a developer who knows nothing about cerebras because we are a relatively small company, they can click on two buttons on the standard software SDK of the meta, can generate an API key, select the cerebras flag, and then suddenly, their token is being processed on a huge wafer-cyl engine,” Wang said. “It is simply for us to have this kind of Meta’s entire developer ecosystem at the back end.”
The choice of special silicon meta gives some deep indication: in the next stage of AI, it doesn’t just know your model, but they can think how soon they can think. In that future, speed is not just a feature – this is the whole thing.
