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Description
Nexusflow has unveiled Athene-V2, its newest model suite boasting 72 billion parameters, which has been meticulously fine-tuned from Qwen 2.5 72B to rival the capabilities of GPT-4o. Within this suite, Athene-V2-Chat-72B stands out as a cutting-edge chat model that performs comparably to GPT-4o across various benchmarks; it excels particularly in chat helpfulness (Arena-Hard), ranks second in the code completion category on bigcode-bench-hard, and demonstrates strong abilities in mathematics (MATH) and accurate long log extraction. Furthermore, Athene-V2-Agent-72B seamlessly integrates chat and agent features, delivering clear and directive responses while surpassing GPT-4o in Nexus-V2 function calling benchmarks, specifically tailored for intricate enterprise-level scenarios. These innovations highlight a significant industry transition from merely increasing model sizes to focusing on specialized customization, showcasing how targeted post-training techniques can effectively enhance models for specific skills and applications. As technology continues to evolve, it becomes essential for developers to leverage these advancements to create increasingly sophisticated AI solutions.
Description
Inkling-Small is an efficient Mixture-of-Experts transformer model built to provide performance comparable to Inkling while using a much smaller active parameter footprint. The model has 276 billion total parameters and 12 billion active parameters, making it designed for strong capability with more efficient compute usage. Inkling-Small was trained on NVIDIA GB300 NVL72 systems and supports native reasoning across text, images, and audio. It offers context windows of up to one million tokens, making it suitable for long documents, large codebases, multimodal context, and extended agent workflows. Users can set reasoning effort from minimal to extra high to control the balance between speed, cost, compute, and task complexity. The model benefits from improved pre-training data, post-training with on-policy distillation from Inkling, and extended agentic coding reinforcement learning. These improvements helped Inkling-Small surpass its larger counterpart on reasoning and coding benchmarks. Its encoder-free multimodal architecture processes audio as dMel spectrograms and images as 40-by-40-pixel patches alongside text tokens. By combining efficient MoE scaling, long-context reasoning, multimodal input, coding strength, and adjustable thinking effort, Inkling-Small is built for practical high-performance AI deployment.
API Access
Has API
No
API Access
Has API
Yes
Integrations
GPT-4o
Yes
Model Context Protocol (MCP)
No
Nexusflow
Yes
Qwen
Yes
Tinker
No
Integrations
GPT-4o
No
Model Context Protocol (MCP)
Yes
Nexusflow
No
Qwen
No
Tinker
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$0.30 per million input tokens
$0.30 per million input tokens and $1.20 per million output 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
Yes
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)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Nexusflow
Country
United States
Website
nexusflow.ai/blogs/athene-v2
Vendor Details
Company Name
Thinking Machines Lab
Founded
2025
Country
United States
Website
thinkingmachines.ai/news/inkling-small/