Alibaba
Qwen3.8 Omni Flash
qwen3.8-omni-flash
Total Context
1M
Max Output
131.1K
Released
N/A
Input$0.1143 / M tokens
Output$0.3857 / M tokens
Qwen3.6 Plus
qwen3.6-plusQwen3.6 Plus is described around hybrid linear attention and sparse MoE design, with clear gains in agentic coding, front-end development, and reasoning tasks. Public model cards mention repository-level work, interactive front-end generation, and stronger benchmark results such as SWE-style evaluations. This makes it more distinct as a developer/productivity model than as a generic conversational assistant.
Context Window
1M tokens
Maximum Output
65.5K tokens
Release Date
Apr 2, 2026
Modalities
Qwen3.6 Plus Pricing
| Token Tier | Input Price | Output Price | Cache Create 5m | Cache Read 5m |
|---|---|---|---|---|
| <=256K | $0.2857/M | $1.7143/M | $0.3571/M | $0.0286/M |
| >256K | $1.1429/M | $6.8571/M | $1.4286/M | $0.1143/M |
Qwen3.6 Plus API Capabilities
Reasoning
Supported
Tool calling
Supported
Temperature parameter
Supported
Attachments
Not supported
Knowledge Base
2025-04-01
Endpoint Protocols
Messages APIgeminiCompletions API
Qwen3.6-Plus Model Highlights
Qwen3.6-Plus combines agentic coding, native visual understanding and a million-token context window for demanding development workloads.
Agentic Coding
Handles repository-level engineering, frontend programming and iterative coding workflows with improved code-related capabilities.
Native Visual Understanding
Processes text, images and video, with enhanced object recognition, OCR and object localization for grounded analysis.
Million-Token Context
A one-million-token context window supports analysis of large codebases, extensive documents and long multimodal inputs.
Qwen3.6-Plus Use Cases
Qwen3.6-Plus is suited to repository engineering, visual frontend development and analysis of long multimodal materials.
Repository Engineering
Analyze dependencies across a large codebase, plan coordinated changes and produce implementations spanning multiple files.
Visual Frontend Development
Interpret screenshots or design references and turn their layout and visual details into frontend code.
Multimodal Content Analysis
Review long collections of text, images and video to identify objects, extract visible text and summarize relevant findings.
How to Use Qwen3.6 Plus via the TokenHub API
curl 'https://us-api.tokenhub.com/v1/messages' \
-X 'POST' \
-H "Authorization: Bearer $TOKENHUB_API_KEY"Qwen3.6 Plus Benchmarks
Qwen3.6 Plus
| Index score | ||
|---|---|---|
| Artificial Analysis Intelligence Index | Artificial Analysis broad capability aggregate | 39.6 |
| Artificial Analysis Coding Index | Artificial Analysis software task aggregate | 42.9 |
| Knowledge & Reasoning | ||
| GPQA | Advanced science problem solving | 88.2% |
| HLE | Broad expert-level exam set | 25.7% |
| Coding & Engineering | ||
| SciCode | Scientific coding challenges | 40.7% |
| Terminal-Bench Hard | Hard terminal task execution | 43.9% |
| Instruction Following & Agent Tasks | ||
| IFBench | Prompt constraint adherence | 75.2% |
| AA-LCR | Long-context reasoning | 69.7% |
| τ²-Bench | Agent workflow tasks | 97.7% |
Metrics sourced from Artificial Analysis
Qwen 3.6 Plus FAQ
Qwen 3.6 Plus: capabilities, use cases, limits, and TokenHub guidance.
What is Qwen 3.6 Plus?+
Qwen 3.6 Plus is a Alibaba Qwen model for balanced multimodal reasoning and production workloads.
Which workloads suit Qwen 3.6 Plus?+
Best for image and video understanding, document analysis and tool-heavy automation, especially when reliable multi-step execution is the priority.
Which feature stands out?+
Key strength: a strong balance of quality, multimodality, and production features and hybrid thinking that can switch between deliberate and direct responses.
When should teams avoid Qwen 3.6 Plus?+
It belongs to an older generation and may lack newer capabilities. For the latest capabilities matter, consider Qwen 3.7 Plus.
What should I verify in TokenHub?+
Use the exact ID shown by TokenHub; follow your account docs and verify current features.
Ready to use Qwen3.6 Plus?
Use one API key to access Qwen3.6 Plus and more AI models through TokenHub.
Media and Discussions
Selected public videos and posts related to this model.
X (Twitter)
Qwen ·
（1/8）🚀 Introducing Qwen3.6-Plus: Towards Real-World Agents! 🤖 Today, we’re thrilled to drop a major milestone in our journey toward native multimodal agents. Here is what makes Qwen3.6-Plus a game-changer： 💻 Next-level Agentic Coding: Smarter, faster execution. 👁️ https://t.co/uUpcyLaB6d
https://pbs.twimg.com/media/HE5885PbgAAlo4y.jpgView originalQwen ·
🚀 Introducing Qwen3.6-Max-Preview, an early preview of our next flagship model Highlights： ⚡️ Improved agentic coding capability over Qwen3.6-Plus 📖 Stronger world knowledge and instruction following 🌍 Improved real-world agent and knowledge reliability performance Smarter, https://t.co/0Fr8jgqDbJ
https://pbs.twimg.com/media/HGWpSykaMAAqsJn.jpgView originalTogether AI ·
Introducing Qwen3.6-Plus from @Alibaba_Qwen, a 1M-context model built for real-world agents, agentic coding, and multimodal reasoning. AI natives can now use Qwen3.6-Plus on Together AI and benefit from reliable inference for production-scale agent workflows. https://t.co/s4Ysm1ZsKt
https://pbs.twimg.com/media/HHF9k19bQAA8aaM.jpgView originalReddit
[deleted by user]
View originalAlibaba's Qwen3.6-Plus is beating Claude Opus in coding!!
AdVirtual2648 ·
Read full post
alibaba just dropped qwen 3.6-plus and the benchmarks are kind of ridiculous. it's scoring 61.6 on terminal-bench and 57.1 on swe-bench verified. for context that puts it ahead of claude 4.5 opus, kimi k2.5, and gemini 3 pro on most of the agentic coding tests. the crazy part is it's less than half the size of kimi k2.5 and glm-5. way smaller model but matching or beating the big ones. it also has a native 1M context window which is huge if you're working on long codebases or big document tasks. and they built it specifically for agentic workflows so it's not just "generate code and hope for the best"... it actually handles multi-step tasks. it's already free on openrouter too. open source versions coming soon apparently. link's in the comments.
qwen/qwen3.6-plus is testing very well in my setup
productboy ·
Read full post
I'm about ten days into hardcore testing of Hermes with different setups. What I've tried: Hetzner VPS with 4vCPU, 8GB memory. Free models via OpenRouter. It was very unreliable because of rate limiting of free models. Hermes would start strong on a task then stall with 429 errors. Hetzner VPS with 4vCPU, 8GB memory. Free models via Ollama running on the VPS. This was unusable because of the small models that had to be used given VPS memory constraints. Hermes needs larger models to perform reliably. Oracle VPS with 1vCPU, 1GB memory. Had to try it but Hermes wouldn't run and barely installed. Hetnzer VPS with 4vCPU, 8GB memory. Paid models via OpenRouter. The default model is qwen3.6-plus with a gemma model as fallback. This has been the best performing setup. And, it really shows off the self-improvement architecture where Hermes seems to get better with each session. The Discord integration is also more stable with higher fidelity output.
YouTube
Qwen3.6-Plus : New AI Model is Breaking the Internet!
Codedigipt
View originalQwen3.6-Plus - The #1 AI Model?
Blunt AI - Technology through Data
View originalQwen3.6-Plus: Advancing Real-World Agentic Intelligence
LuxaK
View original