VFF - The signal in the noise
News

Qwen3.7-Plus Now Available Only Through Alibaba's Proprietary API

Read original
Share
Qwen3.7-Plus Now Available Only Through Alibaba's Proprietary API

Alibaba released Qwen3.7-Plus, a multimodal AI model supporting text, video, and image inputs at $0.40/$1.60 per 1M tokens, 60% cheaper than its text-only predecessor Qwen3.7-Max. The model marks a strategic shift away from Alibaba's open-source focus, available only through proprietary APIs and closed commercial licensing. It includes a 1-million token context window and a 'preserve_thinking' parameter to maintain reasoning state across multi-step tasks, positioning it competitively on cost among major AI models.

  • Qwen3.7-Plus costs $2.00 per 1M tokens total ($0.40 input, $1.60 output), making it among the cheapest powerful multimodal models available
  • Model supports text, video, and image inputs, unlike the text-only Qwen3.7-Max it replaces
  • Available only via proprietary API and Qwen Chat, departing from Alibaba's prior open-source strategy
  • Features 1-million token context window and 'preserve_thinking' parameter to maintain reasoning continuity in multi-step agent tasks

Alibaba's shift to proprietary licensing for its latest models signals a broader industry trend toward closed commercial offerings for frontier capabilities, even among companies historically committed to open-source release. The low pricing and multimodal support make this a viable option for enterprises running autonomous agents and complex workflows, but the closed model limits adoption among developers and researchers who relied on open-weight alternatives.

For enterprises deploying autonomous agents and multi-step workflows, Qwen3.7-Plus offers cost-effective multimodal processing with architectural features designed to prevent reasoning state decay. However, organizations invested in open-source Qwen models, including major users like Airbnb, must now evaluate proprietary alternatives or remain on older open-weight versions.

  • Alibaba is abandoning its open-source-first strategy for newer model releases, consolidating advanced capabilities behind proprietary APIs
  • The 'preserve_thinking' parameter and 1M token context window address a real technical bottleneck in agentic AI systems, but this capability is now locked behind a commercial license
  • Pricing pressure from competitors like DeepSeek and MiniMax is driving aggressive cost positioning, with Qwen3.7-Plus among the cheapest multimodal options available

Monitor whether Alibaba continues to release open-source variants alongside proprietary models, or if this marks a permanent shift to closed releases for frontier capabilities. Track adoption rates among enterprises currently using open-weight Qwen models and whether the 'preserve_thinking' feature becomes a standard expectation across competing platforms. Watch for competitive pricing responses from OpenAI, Google, and Anthropic in the multimodal segment.

OneUpAI
OneUp Your Business. Get More Done. OneUp Your Business. Get More Done. OneUp Your Business. Get More Done.
Learn More
Share

Subscribe to the newsletter

The latest stories and analysis, delivered to your inbox.

Free. No spam. Unsubscribe any time.

Related stories

Google DeepMind Launches Sign Language AI for Deaf Users
TrendingNews

Google DeepMind Launches Sign Language AI for Deaf Users

Google DeepMind has introduced sign-language-to-text (SL2T), a new AI model that converts sign language into text for Deaf and hard of hearing users. The model powers new sign language features designed to improve accessibility. The announcement marks a significant step in making AI tools more inclusive for sign language users.

· Google Deepmind
NVIDIA Opens Alpamayo 2 Super for Commercial AV Use
TrendingModel Release

NVIDIA Opens Alpamayo 2 Super for Commercial AV Use

NVIDIA has released Alpamayo 2 Super, an open-source reasoning model for autonomous vehicles, under a permissive commercial license. The model ranks first on autonomous driving benchmarks and is designed to handle complex, rare scenarios that challenge AV systems. The release includes a cloud-to-vehicle workflow that pairs frontier-scale reasoning in development with efficient, specialized models for production deployment.

by Jessica Soares· NVIDIA Blog (AI)
Google DeepMind Releases Gemini Robotics 2 for Whole-Body Robot Control
TrendingModel Release

Google DeepMind Releases Gemini Robotics 2 for Whole-Body Robot Control

Google DeepMind introduced Gemini Robotics 2, a suite of AI models designed to give robots whole-body control, dexterous manipulation, and multi-robot collaboration capabilities. The system includes three models: a vision-language-action model for motor control, an embodied reasoning model for planning and communication, and an on-device model optimized for fast adaptation to new robot bodies. Early-access partners can now deploy these models on humanoid and bi-arm robots to perform complex, multi-step tasks in unstructured environments.

· Google Deepmind
Brain Waves Join Video as Physical AI Training Data
TrendingNews

Brain Waves Join Video as Physical AI Training Data

Frontier physical AI models are moving beyond video training data to incorporate multiple camera angles, dense annotation, and brain wave readings as training inputs. The shift reflects growing recognition that traditional video datasets alone are insufficient for training AI systems that interact with the physical world. Brain wave data represents an emerging frontier in multimodal training approaches for robotics and embodied AI.

by Tim Fernholz· TechCrunch AI