MODEL PROFILE

Qwopus3.6-27B-v2-MTP-GGUF

Jackrong · Qwopus3.6-27B-v2-MTP-GGUF

💡 What is Qwopus3.6-27B-v2-MTP? 🪐 Qwopus3.6-27B-v2-MTP is a speed-oriented reasoning release built on top of Qwen3.6-27B . It keeps the Qwopus line's focus on reconstructed reasoning traces, coding discipline, DevOps procedures, and mathematical derivations, while adding Multi-Token Prediction for faster generation. The goal is simple: preserve the depth and structure of a 27B reasoning model while making real interactive use noticeably faster. ⚡ MTP Decoding Auxiliary future-token prediction improves throughput on long reasoning, code, math, and strict-format prompts. 🧩 Structured Reasoning Inherits the Qwopus training recipe built around reconstructed step-by-step reasoning trajectories. 🧪 GB10 Tested Validated on a 30-question local benchmark across Logic, Coding, DevOps, Math, and Edge tasks. 🚀 Practical Speed Designed for workflows where strong answers matter, but waiting several extra minutes per task does not. Qwen3.6-27B provides the dense 27B foundation for this release. Qwopus3.6-27B-v2-MTP focuses on preserving the base model's broad reasoning capability while tuning the output style toward stepwise analysis, tool-aware execution, and practical engineering answers. Attribute Specifications & Details 🧠 Architecture Dense Transformer / 27 Billion Parameters 🎯 Focus Domains Agentic Coding, DevOps, structured logic, mathematics, and strict-format output ⚡ MTP Objective Improve generation throughput through multi-token speculative prediction while retaining final-answer quality.

Visual QAmultimodalreasoningcoderlicense:apache-2.0
Context windowNot disclosed
Input → OutputText、Image → Text
Model weightsNot verified
Profile updated2026/11/2 19:15:30
OVERVIEW

Model overview

💡 What is Qwopus3.6-27B-v2-MTP? 🪐 Qwopus3.6-27B-v2-MTP is a speed-oriented reasoning release built on top of Qwen3.6-27B . It keeps the Qwopus line's focus on reconstructed reasoning traces, coding discipline, DevOps procedures, and mathematical derivations, while adding Multi-Token Prediction for faster generation. The goal is simple: preserve the depth and structure of a 27B reasoning model while making real interactive use noticeably faster. ⚡ MTP Decoding Auxiliary future-token prediction improves throughput on long reasoning, code, math, and strict-format prompts. 🧩 Structured Reasoning Inherits the Qwopus training recipe built around reconstructed step-by-step reasoning trajectories. 🧪 GB10 Tested Validated on a 30-question local benchmark across Logic, Coding, DevOps, Math, and Edge tasks. 🚀 Practical Speed Designed for workflows where strong answers matter, but waiting several extra minutes per task does not. Qwen3.6-27B provides the dense 27B foundation for this release. Qwopus3.6-27B-v2-MTP focuses on preserving the base model's broad reasoning capability while tuning the output style toward stepwise analysis, tool-aware execution, and practical engineering answers. Attribute Specifications & Details 🧠 Architecture Dense Transformer / 27 Billion Parameters 🎯 Focus Domains Agentic Coding, DevOps, structured logic, mathematics, and strict-format output ⚡ MTP Objective Improve generation throughput through multi-token speculative prediction while retaining final-answer quality.

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.

Source / channelInputOutputBilling unitCollected at
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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.

Are these real-time billing prices?

These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.

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。