Ratings and Reviews 1 Rating

Total
ease
features

Ratings and Reviews 1 Rating

Total
ease
features
design

Alternatives to Consider

  • Astra Pentest Reviews & Ratings
    295 Ratings
    Company Website
  • Gemini Enterprise Agent Platform Reviews & Ratings
    999 Ratings
    Company Website
  • StackAI Reviews & Ratings
    54 Ratings
    Company Website
  • JetBrains Junie Reviews & Ratings
    12 Ratings
    Company Website
  • LTX Reviews & Ratings
    182 Ratings
    Company Website
  • Dragonfly Reviews & Ratings
    16 Ratings
    Company Website
  • FinOpsly Reviews & Ratings
    3 Ratings
    Company Website
  • Yeastar P-Series PBX System Reviews & Ratings
    116 Ratings
    Company Website
  • Retool Reviews & Ratings
    593 Ratings
    Company Website
  • BoldTrail Reviews & Ratings
    2,107 Ratings
    Company Website

What is GPT-6.1 Sol?

GPT-6.1 Sol is OpenAI's upgraded Sol model for developers and professionals who need advanced reasoning and agentic capabilities without the higher cost of GPT-6 Astra. It is designed for coding, professional knowledge work, computer use, scientific research, factual question answering, and multi-step business workflows. OpenAI describes GPT-6.1 Sol as approaching GPT-6 Astra's intelligence across several important workloads while charging one-fifth of Astra's standard input and output token prices. On DeepSWE v1.1, which evaluates long-horizon software engineering in real codebases, GPT-6.1 Sol matches GPT-6 Astra at approximately one-fifth of the cost and exceeds GPT-6 Sol's best score by 6.4 percentage points. Its professional-work capabilities include understanding complex PDFs containing tables, charts, diagrams, and fine-print details across fields such as finance, healthcare, and legal work. On AutomationBench, GPT-6.1 Sol improves on GPT-6 Sol by 4.8 percentage points at the same reasoning setting and scores 2.2 points above Opus 5.5 at medium reasoning effort. Computer-use performance also advances significantly, with GPT-6.1 Sol outperforming GPT-6 Sol by seven percentage points on the OSWorld 2.0 offline set at maximum reasoning effort and coming within 2.1 points of GPT-6 Astra. For scientific research, the model can work with code and terminal tools on workflows involving data analysis, simulations, model fitting, and theorem proving, more than doubling GPT-6 Sol's Terminal-Bench Science 0.1 score at maximum effort. OpenAI also reports improved factual accuracy, including a reduction in the factual-error rate from 11.4% with GPT-6 Sol to 7.7% with GPT-6.1 Sol at low reasoning effort on its deliberately difficult factuality evaluation.

What is Claude Opus 5?

Claude Opus 5 is Anthropic’s advanced Opus model designed for high-value coding, knowledge work, problem-solving, automation, scientific research, and everyday AI workflows. The model is positioned as a thoughtful and proactive system that approaches the frontier intelligence of Claude Fable 5 at half the price. Anthropic says Claude Opus 5 delivers greatly improved performance for the same cost as Opus 4.8, with base pricing of $5 per million input tokens and $25 per million output tokens. The model supports effort settings that allow customers to optimize for deeper intelligence or conserve tokens for faster and cheaper results. Claude Opus 5 performs especially well on software engineering evaluations, including tasks that require debugging, code generation, root-cause analysis, test creation, and multi-step implementation. It also shows strong results on knowledge work, business automation, computer use, novel problem solving, and research-heavy tasks. Anthropic highlights that Opus 5 is better at checking its own work, iterating until it succeeds, and building supporting tools when a task requires it. The model improves on Opus 4.8 across life sciences evaluations, including structural biology, organic chemistry, bioinformatics, molecular structure inference, and protein function tasks. Claude Opus 5 includes alignment and safety protections that aim to allow beneficial cybersecurity and biology use cases while restricting riskier exploit generation, penetration testing, and certain autonomous misuse scenarios. It is available on Claude Max as the default model, on Claude Pro as the strongest model, and through the Claude API as claude-opus-5, with a Fast mode that runs around 2.5 times the default speed.

Media

Media

Integrations Supported

.NET
Amazon Bedrock
Augment Code
Bash
Brokk
Devin
Devin Desktop
Gemini Enterprise Agent Platform
GitHub
JetBrains Junie
Kotlin
Lua
OpenClaw
OpenCode
Perplexity Pro
PowerShell
PrivatClaw
Rust
Solidity
Swift

Integrations Supported

.NET
Amazon Bedrock
Augment Code
Bash
Brokk
Devin
Devin Desktop
Gemini Enterprise Agent Platform
GitHub
JetBrains Junie
Kotlin
Lua
OpenClaw
OpenCode
Perplexity Pro
PowerShell
PrivatClaw
Rust
Solidity
Swift

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
Cached Input: $0.10 per 1 million cached input tokens

Pricing Information

$5 per 1M tokens (input)
$5 per million input tokens and $25 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

Popular Alternatives

Popular Alternatives