Skip to main content

Documentation Index

Fetch the complete documentation index at: https://documentation.deepmask.io/llms.txt

Use this file to discover all available pages before exploring further.

Alibaba’s Qwen3 models bring frontier-class reasoning and repository-scale coding to DeepMask in two deployment configurations. Qwen (DeepMask) is the 235B flagship with dual-mode inference, spatial-visual logic, and a 1M-token context window. Qwen3 (StackIT) is a StackIT-tuned variant co-developed for European cloud environments, with native infrastructure awareness and the same powerful reasoning core. Both models excel at multilingual tasks, document analysis, and agentic workflows.

​
About

Qwen (DeepMask) is Alibaba’s 235B Qwen3 flagship model. It features Dual-Mode Inference, allowing you to toggle between “Instant” mode for fast chat and “Thinking” mode for deep, PhD-level problem solving. It leads on repository-scale coding — able to reason across tens of thousands of lines of code without context drift — and supports a 1M-token context window with efficient hardware use via a tiered KV cache.
Qwen (DeepMask) is hosted on DeepMask infrastructure with a 1M-token context window. Your data remains within DeepMask’s EU-compliant environment.

​
Key Capabilities

Dual-Mode Reasoning

Toggles between fast chat and deep Thinking mode for complex, multi-step problem solving.

Spatial-Visual Logic

Excels at understanding complex diagrams, maps, technical blueprints, and spatial relationships.

1M Token Context

Handles up to 1 million tokens, enabling analysis of very large codebases and document sets.

Repository-Scale Coding

Understands the architectural intent behind a codebase, enabling whole-repo reasoning and refactoring.

​
Use Cases

  • Enterprise software architecture — Plan and refactor multi-repository backend systems with full structural awareness.
  • Global fintech analytics — Process large volumes of financial data for predictive market analysis.
  • Creative design suite — Leverage native support for high-fidelity image understanding and natural speech tasks.
  • Multilingual RAG — Build retrieval-augmented generation pipelines across multiple languages with strong reasoning.
Qwen (DeepMask) is your best choice for repository-scale coding and complex reasoning tasks on DeepMask. Use Thinking mode for difficult problems and Instant mode for interactive chat at 0.22s TTFT.

​
Specifications

SpecificationValue
Model ProviderAlibaba
Main Use CasesAgents Coding, Multilingual RAG
Reasoning EffortHigh (Instant & Thinking)
GPQA Diamond89.3%
Max Context1M Tokens
Latency (TTFT)0.22s (Non-Thinking Mode)
Throughput145 Tokens/sec