Deep|LLM 26Q4: Model Capabilities Advance Rapidly, While Near-Term Monetization Remains Under Pressure

Key Highlights

• Competition has expanded from two leaders to a 4+1 field. OpenAI, Anthropic and Google are closely matched on composite benchmarks, but Opus 5.5 is clearly ahead in our hands-on use. Meta and SpaceX are stepping up investment, while the gap between open-weight and frontier models has widened again.
• Competition is driving price cuts as enterprises shift to optimizing token usage. List prices for the next tier below the top flagships are converging on $4/$20 per million input/output tokens. The effective unit price in Ramp’s sample is about 40% below its March peak. Implementation and ongoing support have become critical to enterprise adoption.
• Recursive self-improvement (RSI) is advancing model capabilities. AI is playing a larger role in its own development. The first lab to cross the RSI threshold could pull further ahead as its models accelerate subsequent development. Math benchmarks are largely saturated, and AI-generated proofs of open problems are now under review.
• Foundation models are becoming the basis for physical AI, video production and scientific research. Astra demonstrated robotics capabilities without specialized training on robot actions. Pure diffusion may be less suited to end-to-end video production; the workflow is likely to shift toward LLMs directing and diffusion models rendering.
• Cyber offense and defense are creating new demand for tokens. Our October 28 cybersecurity report estimates that security-related model revenue could grow from about US$5–7 billion to US$50–70 billion.
• The investment–revenue gap is widening in the near term, even as the long-term opportunity expands. Models can increasingly address white-collar and blue-collar work beyond coding. Based on the leading labs’ cost structures, we estimate that about 70% of their compute spending is not used for paid inference. We expect that split to persist through the end of 2027.

The timing mismatch identified in our August report persists, with clear near-term pressure on commercial returns.

Competition: The Field Expands from Two Leaders to 4+1

• When we published our August RSI report, OpenAI and Anthropic dominated frontier model development: at the end of July, they accounted for four of the top five models on the Artificial Analysis index. Three months later, Google’s Gemini 4 Carbon leads version 5 of the Artificial Analysis Intelligence Index, introduced on October 27, with Opus 5.5 and GPT-6 Astra close behind. Meta has released Muse Wonder, and SpaceX has acquired xAI and Cursor. In terms of capital, compute and investment in frontier model development, we see the competitive landscape taking shape as a 4+1 field: OpenAI, Anthropic, Google and Meta, plus SpaceX.

Artificial Analysis Intelligence Index v5, best model from each lab (October 28, 2026)

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