## Can LlamaCon Rekindle Developer Love for Meta’s AI?
Meta is hosting its inaugural LlamaCon today, April 29th, 2025, at its Menlo Park headquarters. The goal? To woo AI developers to build applications leveraging Meta’s open-source Llama AI models. While this pitch would have been an easy sell a year ago, Meta now faces an uphill battle to regain its standing in the rapidly evolving AI landscape.
The company has struggled to maintain pace with both “open” AI labs like DeepSeek and commercial giants like OpenAI. LlamaCon is thus arriving at a critical juncture, representing Meta’s attempt to reignite developer interest and expand its Llama ecosystem. The core issue is straightforward: Meta needs to deliver superior open models. However, achieving this is proving to be more complex than it seems.
Meta’s earlier launch of Llama 4 disappointed developers. Benchmark scores fell short of models like DeepSeek’s R1 and V3, a far cry from when the Llama family was at the forefront of AI innovation. Last summer, the Llama 3.1 405B model was hailed by Mark Zuckerberg as a major victory. Meta even went so far as to call it the “most capable openly available foundation model,” rivaling the performance of OpenAI’s GPT-4o. These models solidified Meta’s reputation as a leader, particularly due to their cutting-edge performance and the freedom they offered developers to host models on their own infrastructure.
However, Hugging Face’s head of product and growth, Jeff Boudier, notes that today, the older Llama 3.3 model sees more downloads than Llama 4, highlighting a significant shift in developer preferences. The reception of Llama 4 has been controversial, marked by accusations of benchmark manipulation.
A version of Llama 4, dubbed “Maverick,” was optimized for “conversationality” to achieve a top ranking on the crowdsourced LM Arena benchmark. However, the generally released version of Maverick performed significantly worse. LM Arena co-founder Ion Stoica expressed concern that this discrepancy harmed the developer community’s trust in Meta, emphasizing the need for transparency and better models to restore confidence.
Furthermore, the absence of a reasoning model within the Llama 4 family was a glaring omission. As AI reasoning models have demonstrated superior performance on specific benchmarks, their absence suggests that Meta might have rushed the launch. Ai2 researcher Nathan Lambert highlights the increasing pressure on Meta due to rival open models rapidly approaching the frontier, and now come in varied shapes and sizes. He pointed to Alibaba’s recent release of the Qwen 3 family of hybrid AI reasoning models, which purportedly outperformed some of OpenAI and Google’s best coding models on the Codeforces benchmark.
NYU AI researcher Ravid Shwartz-Ziv believes that Meta needs to take greater risks, like employing new techniques, to deliver superior models. Whether Meta is currently positioned to do so is uncertain. Earlier reports suggested that Meta’s AI research lab is struggling, and the recent departure of its VP of AI Research, Joelle Pineau, further complicates matters.
LlamaCon is Meta’s opportunity to showcase its latest advancements and demonstrate its ability to surpass upcoming releases from competitors like OpenAI, Google, and xAI. Failure to impress could result in Meta falling further behind in this highly competitive AI landscape. The pressure is on for Meta to prove that it can still deliver on its promise of cutting-edge, open-source AI.