language-models

Google released Gemma 4, a new line of open-weights models available in sizes from 2 billion to 31 billion parameters, under a permissive Apache 2.0 license. The release includes multimodal capabilities, support for 140+ languages, native function calling, and a 256,000-token context window for the larger variants.

Google has previewed Gemini Nano 4, a new on-device language model for Android, available now in early access via AICore Developer Preview. The model comes in two versions: Gemini Nano 4 Fast (3x faster than previous models, 60% less battery) and Gemini Nano 4 Full (higher reasoning capability). The models will launch on new flagship Android devices later this year.

OpenAI President Greg Brockman stated that GPT reasoning models have 'line of sight' to AGI and represents a settled debate on whether text-based models can achieve general intelligence. The company is prioritizing this approach over multimodal world models like Sora, which Brockman views as 'a different branch of the tech tree.' The stance contradicts prominent AI researchers including Yann LeCun and Demis Hassabis, who argue LLMs alone are insufficient for human-level intelligence.

Mistral AI has released Mistral Small 4, the latest iteration of its small-scale language model. The company claims improvements in reasoning and coding capabilities, though specific benchmark scores and pricing details have not been publicly disclosed.

Amazon Bedrock now offers NVIDIA's Nemotron 3 Nano as a fully managed serverless model, expanding its Nemotron portfolio alongside previously available Nemotron 2 Nano 9B and Nemotron 2 Nano VL 12B variants. The addition enables developers to deploy NVIDIA's smallest inference-optimized model without managing infrastructure.

Guide Labs has open-sourced Steerling-8B, an 8 billion parameter language model built with a new architecture specifically designed to make the model's reasoning and actions easily interpretable. The release addresses a persistent challenge in AI development: understanding how large language models arrive at their outputs.