Qwen3.5 27B Claude 4.6 Opus Reasoning Distilled v2

Qwen3.5

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released March 2026context N/A

A distilled reasoning model that inherits structured thinking patterns from Claude Opus, packaged into a more accessible 27B parameter form. It handles multi-step reasoning and visual inputs with methodical deliberation, though as a distilled variant it may occasionally lose nuance present in the original teacher model. Its open-weight nature makes it inspectable and locally deployable.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Reasoning & Logic

Strong

Creative Writing

Moderate

Multimodal

Use Case Fit

Fit scores are AI-generated based on model capabilities, intended use, and technical specifications. Learn more

Qwen3.5 27B Claude 4.6 Opus Reasoning Distilled v2

Qwen3.5

Open WeightModel weights are publicly available — can be downloaded and self-hosted

Released March 2026context N/A

A distilled reasoning model that inherits structured thinking patterns from Claude Opus, packaged into a more accessible 27B parameter form. It handles multi-step reasoning and visual inputs with methodical deliberation, though as a distilled variant it may occasionally lose nuance present in the original teacher model. Its open-weight nature makes it inspectable and locally deployable.

Capabilities

Capability scores are AI-generated based on model documentation, benchmarks, and technical specifications. Learn more

Reasoning & Logic

Strong

Creative Writing

Moderate

Multimodal

Use Case Fit

Fit scores are AI-generated based on model capabilities, intended use, and technical specifications. Learn more

Glossary

DistilledA model that has been compressed by training a smaller model to mimic a larger, more capable model, reducing size and computational requirements while retaining performance.Multi-Step ReasoningThe ability to break down complex problems into smaller steps and solve them sequentially, rather than jumping directly to an answer.ReasoningThe model's ability to work through multi-step logical problems and provide justified answers rather than just pattern-matching.Reasoning ModelA model trained to show explicit step-by-step reasoning and problem-solving logic before producing final answers, rather than jumping directly to conclusions.