# OpenAI, Anthropic cut AI model costs as price-performance race intensifies

DevFeed: [OpenAI, Anthropic cut AI model costs as price-performance race intensifies](<https://devfeed.tech/articles/openai-anthropic-cut-ai-model-costs-as-price-performance-race-intensifies-58528.md>)

Original publisher: [Read original article](<https://www.infoworld.com/article/4225637/openai-anthropic-cut-ai-model-costs-as-price-performance-race-intensifies.html>)

Author: Gyana Swain

Published: 2026-09-23T15:21:44Z

Content type: news

Language: en

Sources: [InfoWorld](<https://devfeed.tech/sources/infoworld.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [anthropic](<https://devfeed.tech/topics/anthropic.md>), [OpenAI](<https://devfeed.tech/topics/openai.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [API](<https://devfeed.tech/topics/api.md>), [Claude](<https://devfeed.tech/topics/claude.md>), [Optimization](<https://devfeed.tech/topics/optimization.md>), [Cloud](<https://devfeed.tech/topics/cloud.md>), [Automation](<https://devfeed.tech/topics/automation.md>), [AI-assisted coding](<https://devfeed.tech/topics/ai-assisted-coding.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [anthropic](<https://devfeed.tech/tags/anthropic.md>), [artificial-intelligence](<https://devfeed.tech/tags/artificial-intelligence.md>), [automation](<https://devfeed.tech/tags/automation.md>), [claude](<https://devfeed.tech/tags/claude.md>), [claude-opus-5-5](<https://devfeed.tech/tags/claude-opus-5-5.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [coding-agents](<https://devfeed.tech/tags/coding-agents.md>), [data-sovereignty](<https://devfeed.tech/tags/data-sovereignty.md>), [efficiency](<https://devfeed.tech/tags/efficiency.md>), [enterprise-automation](<https://devfeed.tech/tags/enterprise-automation.md>), [hybrid](<https://devfeed.tech/tags/hybrid.md>), [inference](<https://devfeed.tech/tags/inference.md>), [openai](<https://devfeed.tech/tags/openai.md>), [optimization](<https://devfeed.tech/tags/optimization.md>), [performance](<https://devfeed.tech/tags/performance.md>), [security](<https://devfeed.tech/tags/security.md>)

## AI overview

OpenAI and Anthropic have reduced prices for newer frontier AI models, shifting competition toward price-performance. The article discusses inference efficiency, caching, model optimization, enterprise adoption, and the continuing role of private or hybrid deployments for organizations with data, security, and operational constraints.

## Source excerpt

Enterprises can now buy frontier AI for far less per token after OpenAI and Anthropic cut prices on their newest models on Tuesday. OpenAI released GPT-6 Sol and GPT-6 Luna with per-token costs half those of their GPT-5.6 predecessors. "These models help distribute the benefits of that intelligence by advancing the frontier on cost efficiency," OpenAI said in a blog post about the launch. "Improvements in caching and inference let us serve these models at lower cost, and we're passing those savings directly on... by reducing API prices for Sol and Luna by 50%," it said. Anthropic, meanwhile, launched Claude Opus 5.5 with token prices 20% below those of Opus 5, and claimed that this, with the model's lower compute requirements and reduced token usage, meant additional savings for enterprises: "It performs at the level of Claude Fable 5.1 on most work and costs 40% less to run than Opus 5," the company announced on Opus 5.5's web page. Focus shifts to cost-performance Rather than touting raw performance, as they did with the launch of their flagship models GPT 6 Astra and Claude Fable 5.1, the companies emphasized the value for money of their new models. But analysts say the moves are about more than the lower prices. AI vendors are increasingly competing on efficiency, said Forrester VP and principal analyst Charlie Dai. "Frontier AI is entering a prolonged price-performance race driven primarily by inference efficiency gains, better caching, and model optimization, and it's also intensified by competitive pressure as capabilities converge," Dai said. Providers are lowering costs to "expand enterprise adoption and stimulate higher-volume production usage." The economics of on-premises AI in question Lower API costs improve the economics of consuming AI via cloud platforms, particularly for workloads such as coding agents and enterprise automation. However, there's still a case for private or hybrid deployments, Dai said, citing data sovereignty, security, and intellect