Meta Releases LLaMa 4: It Could Help Drive Big Growth Long Term

Key Points

• Meta recently unveiled its latest family of large language models: LLaMa 4.
• Despite early controversy and consternation, LLaMa 4 hits the mark on intelligence to value.
• LLaMa 4 could be significantly accretive to Meta long-term, boosting its advertising business and potentially monetizing Meta AI.

Magnificent Seven stock Meta Platforms NASDAQ: META made headlines in early April as the company announced the release of its next-generation large language model (LLM), LLaMa 4. The company’s open-source large language models are part of its long-term strategy to become the preeminent player in AI adoption. The tech giant has released LLaMa 4 Scout and LLaMa 4 Maverick so far, while LLaMa 4 Behemoth is still in development. 

So, how does LLaMa 4's performance compare to competitors? How does LLaMa 4 position Meta in the LLM landscape, and can it add to Meta's shares in the long term?

LLaMa 4 Gets Off to a Shaky Start

In Meta’s press release detailing its three models in the LLaMa 4 "herd," the company purported impressive performance. In short, it showed that the various LLaMa 4 models outperformed comparable leading models in almost every benchmark tested.

Additionally, LLaMa 4 Maverick initially ranked as the second-best among all models on the LM Arena Leaderboard. This leaderboard is commonly used to show how different models compete head-to-head based on perceived response quality by humans.

However, it was quickly revealed that the model used in the LM Arena testing was not the same model that Meta released to the public. The developers tailored this model version to perform particularly well on LM Arena’s tests. With this mistake fixed, Maverick now ranks as the 35th best model on the leaderboard.

Overall, many felt disappointed in LLaMa 4 when they tested its performance individually. Additionally, Artificial Analysis ranks Maverick and Scout much lower than models developed by OpenAI and Alphabet NASDAQ: GOOG on their Intelligence Index. They also rank notably lower than DeepSeek’s models. However, LLaMa 4 showed substantially better performance than LLaMa 3. Overall, the LLaMa models available today aren't viewed as the most advanced or highest performing. However, that might not matter.

LLaMa 4: Price-to-Performance Paints a Compelling Picture

The LLaMA 4 models stand out for their strong cost-to-performance ratio. The Artificial Analysis Intelligence vs. Price matrix evaluates how various large language models (LLMs) balance intelligence with cost, measured by price per token. In this context, a token represents a basic unit of text, often a word or part of a word, that the model processes. Each token processed requires computational resources, which ultimately translates into a cost.

Keeping costs per token low is very important for businesses using AI. Lower costs per token allow them to process more data for the same price. Getting quality results is also very important. So, finding the right balance between intelligence and price is essential. In this matrix, Maverick and Scout perform well, costing very little per token but still delivering good performance versus many other models, including LLaMa 3.

What Does This All Mean for Shares of Meta Platforms?

Meta's models aren't the most advanced. However, LLaMa 4 models are solid and cost-effective. This can benefit Meta's business substantially in the long run. This is particularly true for the company’s advertising business. Meta can use LLaMa 4 to increase the capabilities of tools like Advantage+ Creative.

This is a tool advertisers use to create AI-optimized text, images and videos for advertisements. LLaMa 4’s improvements could help make these ads even more effective, increasing the overall value of using Meta’s apps for advertising.

Additionally, Meta's lower price per token compared to LLaMa 3 can help it offer these recommendations at a lower cost.

LLaMa 4 will also power Meta AI. Meta has built this AI assistant into its WhatsApp, Messenger, and Instagram apps. The increased capabilities of Meta AI due to LLaMa 4 should help drive the adoption of Meta AI features. Additionally, the lower token costs of LLaMa 4 compared to LLaMa 3 should decrease costs, boosting margins over time. Meta could begin to explore the direct monetization of Meta AI in early 2026.

As of its last earnings report, Meta AI had 700 million users. The company typically looks to monetize its products once users reach 1 billion. LLaMa 4 should help increase the effectiveness of a Meta AI monetization campaign.

Although some felt disappointed with LLaMa 4, the update looks like a step in the right direction for the overall business. It could be significantly additive to shares in the long term. The company will host LLaMaCon on Apr. 29, where it could reveal more exciting details about its LLM family.