Recent reports highlight a wave of next-generation large language model (LLM) releases from major AI players, including Alphabet (GOOGL.US), Anthropic, and DeepSeek, driving fierce competition in the AI sector. UBS analysts emphasize that the "scaling laws" of model performance remain valid, with computing power investment continuing to be a decisive factor in shaping the AI competitive landscape.
Over the past weeks, the AI model space has seen a flurry of activity. On November 18, Alphabet unveiled its Gemini 3 Pro multimodal model, which secured top rankings in Hugging Face benchmarks for overall performance, text-to-image generation, and visual tasks, while placing second in web development tasks. Anthropic followed on November 24 with Claude Opus 4.5, excelling in software engineering tasks and demonstrating enhanced safety and anti-abuse features, claiming the top spot in web development. DeepSeek joined the race on December 1 with its open-source DeepSeek V3.2 model, which leverages reinforcement learning innovations and sparse attention architecture to reduce inference costs while matching the performance of closed-source models like Gemini 3 Pro.
Breakthroughs in core performance metrics are evident. The ARC-AGI-2 benchmark shows Gemini 3 Deep Think and Claude Opus 4.5 achieving multi-step reasoning scores of 45% and 38%, respectively—far surpassing previous models' 10%-20% range and nearing human-level performance (60%). UBS analysts note these results validate the scaling laws, where increased computing power yields nonlinear improvements in model capabilities.
The competition in chip technology also remains intense. Alphabet's disclosure that Gemini 3 Pro was trained entirely on its proprietary TPU chips has reignited debates over GPU versus AI-specific ASIC chips. While ASICs offer higher efficiency for specialized tasks, GPUs still dominate data centers with 90% market share due to their flexibility and robust software ecosystems. Partnerships like OpenAI-Broadcom (AVGO.US) and Anthropic-Alphabet are boosting ASIC adoption, though both chip types are expected to coexist.
NVIDIA's (NVDA.US) latest earnings reveal $500 billion in revenue visibility for its next-gen GPUs, underscoring soaring demand for computing power. With new chips like Blackwell and Rubin on the horizon, UBS anticipates sustained investment in computing infrastructure, prompting upward revisions to its AI capex forecasts. Beyond Alphabet's leaps, Anthropic and DeepSeek's models are intensifying competition, pressuring rivals like OpenAI and accelerating the shift toward a multi-model, multi-vendor AI ecosystem—a trend likely to persist through 2026.
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