GPT-6 Sol
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What is GPT-6 Sol?
GPT-6 Sol is an advanced OpenAI model positioned between the cost-efficient GPT-6 Luna and the higher-capability GPT-6 Astra for demanding professional and agentic workloads. The model is designed for coding, knowledge work, business automation, computer use, research, and other tasks that require sustained reasoning across multiple steps. It inherits advances from the GPT-6 generation while emphasizing a balance of intelligence, speed, and operating cost for applications that need to run at scale. GPT-6 Sol supports multiple reasoning-effort levels so applications can spend more computation on difficult tasks and reduce effort for straightforward requests. In software development, it can handle complex real-codebase tasks, generate merge-ready changes, debug software, work through terminal workflows, and operate as part of coding agents. Its professional-work capabilities support multi-application processes spanning functions such as finance, operations, sales, marketing, customer support, and human resources. Computer-use abilities allow agents powered by GPT-6 Sol to interact with graphical interfaces and complete long-horizon workflows involving everyday and professional software. OpenAI has also improved the model’s factual reliability, communication style, and alignment compared with GPT-5.6 Sol, including lower rates of misleading claims in challenging coding evaluations. GPT-6 prompt caching provides higher cache-hit rates, supports changing reasoning effort or available tools without invalidating earlier cached context, and offers substantial discounts for cached input tokens. Developers can monitor caching behavior, configure prompt-cache breakpoints, and incorporate Sol into persistent agents that repeatedly reuse large amounts of context. GPT-6 Sol is accessible through ChatGPT Work, Codex, and the OpenAI API under the gpt-6-sol model identifier.
What is Claude Mythos 5.2?
Claude Mythos 5.2 is a frontier AI model developed by Anthropic to support advanced cybersecurity research, biomedical discovery, autonomous software engineering, and complex scientific reasoning. The model shares the same underlying architecture as Claude Fable 5.2 but is made available to verified organizations that require access to capabilities restricted by Fable's cybersecurity and biology safeguards. Its cybersecurity research capabilities include analyzing source code, identifying vulnerabilities, investigating software weaknesses, validating security findings, and supporting authorized penetration testing activities. Claude Mythos 5.2 can examine historical software versions to independently rediscover known vulnerabilities, helping researchers evaluate security risks and prioritize remediation efforts. Anthropic reports that the model identified 10.2% more vulnerabilities than Claude Opus 5.5 and 14.4% more than Claude Mythos 5.1 in its internal vulnerability rediscovery evaluations. Its published cybersecurity benchmark results include 76.3% on CyScenarioBench and 89.6% on CVE Rediscovery, reflecting improvements in technical security reasoning and vulnerability identification. In biological research, the model supports protein engineering, computational biology, molecular analysis, and scientific problem-solving, achieving 85.1% on a de novo protein binder design evaluation. The underlying model also demonstrates strong performance in software engineering, mathematics, scientific experimentation, visual reasoning, and agentic workflows that require multiple stages of planning and execution. Anthropic reports that Claude Mythos 5.2 generates output up to 30% faster than Mythos 5.1, with an optional fast mode that increases token generation speed by up to 2.5 times.
Integrations Supported
.NET
AiAssistWorks
Amp
Augment Code
Bash
C#
Databricks
GitHub Copilot
Go
Java
Integrations Supported
.NET
AiAssistWorks
Amp
Augment Code
Bash
C#
Databricks
GitHub Copilot
Go
Java
API Availability
Has API
API Availability
Has API
Pricing Information
$2 per 1M tokens (input)
Input: $2 per 1 million tokens
Output: $10 per 1 million tokens
Output: $10 per 1 million tokens
Pricing Information
$8 per 1M tokens (input)
$8 per million input tokens and $40 per million output tokens
Supported Platforms
SaaS
Supported Platforms
SaaS
Customer Service / Support
Web-Based Support
Customer Service / Support
Web-Based Support
Training Options
Documentation Hub
Training Options
Documentation Hub
Company Facts
Organization Name
OpenAI
Date Founded
2015
Company Location
United States
Company Website
openai.com
Company Facts
Organization Name
Anthropic
Date Founded
2021
Company Location
United States
Company Website
claude.ai
Categories and Features
AI Coding Models
Not specified
AI Models
Not specified
AI Reasoning Models
Not specified
AI Vision Models
Not specified
Foundation Models
Not specified
Large Language Models
Not specified
Multimodal Models
Not specified
Categories and Features
AI Coding Models
Not specified
AI Models
Not specified
AI Reasoning Models
Not specified
AI Vision Models
Not specified
Foundation Models
Not specified
Large Language Models
Not specified
Multimodal Models
Not specified