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Description

Claude Opus 4.8 is Anthropic’s newest flagship AI model built to improve coding performance, reasoning accuracy, agentic task execution, and collaborative AI workflows for developers, enterprises, and advanced productivity use cases. The model serves as an upgrade to Claude Opus 4.7, delivering measurable improvements across benchmarks related to coding, practical reasoning, software engineering, and autonomous task management while maintaining the same pricing structure for standard usage. One of the most significant improvements in Claude Opus 4.8 is its enhanced honesty and judgment during complex tasks, reducing the likelihood of unsupported claims, hidden errors, or overlooked flaws in generated code and analytical outputs. Anthropic’s evaluations show that Opus 4.8 is substantially less likely than previous versions to allow software defects or reasoning mistakes to pass without flagging uncertainty or requesting clarification. The platform introduces new effort control settings that allow users to adjust how deeply the model reasons through tasks, balancing response quality, processing depth, speed, and token usage depending on workflow requirements. Claude Opus 4.8 also powers new dynamic workflow functionality in Claude Code, enabling the model to coordinate hundreds of parallel subagents within a single session to handle large-scale software engineering tasks such as codebase migrations and extensive automation projects. The model supports high-speed fast mode processing, now significantly more affordable than previous versions, while also offering higher-effort reasoning modes optimized for difficult coding and operational workflows.

Description

Ling 2.6 represents an independently developed and open-source series of large language models created by Ant Group, utilizing a Mixture of Experts (MoE) architecture to enhance inference efficiency, long context modeling, training methodologies, and collaborative reasoning for AI agents. By employing this MoE architecture, Ling effectively directs each token to engage only the most pertinent expert subnetworks, significantly reducing the computational load while preserving the extensive capabilities of the model. This series makes strides in long-sequence modeling, exemplified by Ling-2.6-1T, which accommodates a native context window of up to 1 million tokens and offers a 256K context window through its official API; additionally, Ling-2.6-flash features a native 256K context window, enabling it to handle around 200,000 characters in lengthy inputs. These models are meticulously crafted to ensure dependable retrieval of long-range information without any discernible loss of quality, regardless of whether the data is located at the start, middle, or end of the context. This innovative approach to long-context processing sets a new benchmark for efficiency and reliability in language model performance.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Claude Code Yes 
Hermes Agent Yes 
OpenClaw Yes 
AgentSea Yes 
Claude Agent SDK Yes 
Command Code Yes 
Cursor Yes 
DataGrip Yes 
LaunchLemonade Yes 
Lovable Yes 
Perplexity Pro Yes 
PhpStorm Yes 
Python Yes 
Ruby Yes 
Scala Yes 
Springhub Yes 
Swift Yes 
WebStorm Yes 
XML Yes 
Yonoo Yes 

Integrations

Claude Code Yes 
Hermes Agent Yes 
OpenClaw Yes 
AgentSea No 
Claude Agent SDK No 
Command Code No 
Cursor No 
DataGrip No 
LaunchLemonade No 
Lovable No 
Perplexity Pro No 
PhpStorm No 
Python No 
Ruby No 
Scala No 
Springhub No 
Swift No 
WebStorm No 
XML No 
Yonoo No 

Pricing Details

$5 per 1M (input)
$5 per million input tokens and $25 per million output tokens. Pricing for fast mode is $10 per million input tokens and $50 per million output tokens.
Free Trial No 
Free Version No 

Pricing Details

$0.0028 per 1M tokens
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Anthropic

Founded

2021

Country

United States

Website

claude.ai/

Vendor Details

Company Name

Ant Group

Founded

2014

Country

China

Website

developer.ant-ling.com/en/docs/models/ling/

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