Enterprises use both OpenAI and Anthropic

This is becoming a portfolio market, not a winner take all market. Enterprises increasingly keep both Anthropic and OpenAI live because the best model for coding, reasoning, or workflow automation can flip with each release, and switching traffic is often as simple as changing the model behind an existing API call or agent workflow. That makes benchmark performance, price per token, and product integration into tools like Codex, Claude Code, ChatGPT, and Claude matter continuously, not just at annual contract time.1 2 3 4 5

• The multi model pattern already shows up in infrastructure. OpenRouter’s growth came from developers routing requests across OpenAI, Anthropic, Google, and others with failover, model selection, and analytics in one layer, which only makes sense when customers expect to swap providers regularly.6
• Coding is the clearest example because quality differences are easy to feel. Anthropic got an early edge with Claude Code and Claude 3.7 Sonnet in 2025, which helped power tools like Cursor and Bolt.new, then OpenAI responded by pushing Codex and reallocating more compute toward coding and enterprise workloads in 2026.3 4 7 8
• This is why buyers prefer model agnostic control layers. Companies like Harvey have already moved to multi model setups, and enterprise platforms like Langdock pitch a unified workspace precisely because no single lab stays best across every task, team, or compliance need for long.9 10 11

The next phase is less about picking one lab and more about building routing, evaluation, and workflow software that can shift work automatically. As Anthropic and OpenAI bundle more of the stack into full work products, the pressure moves upstream to whoever best combines frontier model quality, lower inference costs, and the most convenient place where work already happens.1 2 6 11