MODEL PROFILE

Qwopus3.6-27B-Coder-MTP-GGUF

Jackrong · Qwopus3.6-27B-Coder-MTP-GGUF

🧬 Trace Inversion & Negentropy 🧠 27B Dense Model ⚡ Agentic Coding 🛠️ Tool Calling & Agent 🏆 SWE-bench Verified: 67.0% (off-thinking) 💡 What is Qwopus-3.6-27B-Coder? 🪐 Qwopus-3.6-27B-Coder is a reasoning-enhanced agentic coding model built on top of Qwopus3.6-27B-v2 . It inherits the powerful reasoning foundation of the v2 base — which achieved 87.43% MMLU-Pro and 75.25% SWE-bench Verified — and further specializes it for agentic code generation, structured tool calling, debugging, and instruction-following in developer workflows. The model is designed to excel at repository-level coding tasks, multi-turn tool orchestration, and complex logical reasoning under realistic agent environments. 🧩 Agentic Coding Optimized for repository-level coding, debugging, patch generation, and structured multi-step development workflows.

Visual QAmultimodalreasoningcoderlicense:apache-2.0
Context windowNot disclosed
Input → OutputText、Image → Text
Model weightsNot verified
Profile updated2026/10/30 02:23:06
OVERVIEW

Model overview

🧬 Trace Inversion & Negentropy 🧠 27B Dense Model ⚡ Agentic Coding 🛠️ Tool Calling & Agent 🏆 SWE-bench Verified: 67.0% (off-thinking) 💡 What is Qwopus-3.6-27B-Coder? 🪐 Qwopus-3.6-27B-Coder is a reasoning-enhanced agentic coding model built on top of Qwopus3.6-27B-v2 . It inherits the powerful reasoning foundation of the v2 base — which achieved 87.43% MMLU-Pro and 75.25% SWE-bench Verified — and further specializes it for agentic code generation, structured tool calling, debugging, and instruction-following in developer workflows. The model is designed to excel at repository-level coding tasks, multi-turn tool orchestration, and complex logical reasoning under realistic agent environments. 🧩 Agentic Coding Optimized for repository-level coding, debugging, patch generation, and structured multi-step development workflows.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

Source prices & cost analysis

Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.

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Estimate monthly base token costs

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Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.

INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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Frequently asked questions

Do open weights permit free commercial use?

Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.

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Sources & traceability

许可证:apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。