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AIモデルライブラリ/阿里巴巴 · Qwen/Qwen3-Coder-Next-GGUF
モデル情報

Qwen3-Coder-Next-GGUF

阿里巴巴 · Qwen · Qwen3-Coder-Next-GGUF

Today, we're announcing **Qwen3-Coder-Next**, an open-weight language model designed specifically for coding agents and local development. It features the following key enhancements: - **Super Efficient with Significant Performance**: With only 3B activated parameters (80B total parameters), it achieves performance comparable to models with 10–20x more active parameters, making it highly cost-effective for agent deployment. - **Advanced Agentic Capabilities**: Through an elaborate training recipe, it excels at long-horizon reasoning, complex tool usage, and recovery from execution failures, ensuring robust performance in dynamic coding tasks. - **Versatile Integration with Real-World IDE**: Its 256k context length, combined with adaptability to various scaffold templates, enables seamless integration with different CLI/IDE platforms (e.g., Claude Code, Qwen Code, Qoder, Kilo, Trae, Cline, etc.), supporting diverse development environments. **Qwen3-Coder-Next** has the following features: - Type: Causal Language Models - Training Stage: Pretraining & Post-training - Number of Parameters: 80B in total and 3B activated - Number of Parameters (Non-Embedding): 79B - Hidden Dimension: 2048 - Number of Layers: 48 - Hybrid Layout: 12 \* (3 \* (Gated DeltaNet -> MoE) -> 1 \* (Gated Attention -> MoE)) - Gated Attention: - Number of Attention Heads: 16 for Q and 2 for KV - Head Dimension: 256 - Rotary Position Embedding Dimension: 64 - Gated DeltaNet: - Number of Linear Attention Heads: 32 for V and 16 for QK - Head Dimension: 128 - Mixture of Experts: - Number of Experts: 512 - Number of Activated Experts: 10 - Number of Shared Experts: 1 - Expert Intermediate Dimension: 512 - Context Length: 262,144 natively

翻訳待ちのため原文を表示しています。

テキスト生成license:apache-2.0
コンテキスト長262,144 Token
入力 → 出力テキスト → テキスト
モデルウェイト未確認
情報更新日時2026/10/30 17:37:16
OVERVIEW

モデル紹介

Today, we're announcing **Qwen3-Coder-Next**, an open-weight language model designed specifically for coding agents and local development. It features the following key enhancements: - **Super Efficient with Significant Performance**: With only 3B activated parameters (80B total parameters), it achieves performance comparable to models with 10–20x more active parameters, making it highly cost-effective for agent deployment. - **Advanced Agentic Capabilities**: Through an elaborate training recipe, it excels at long-horizon reasoning, complex tool usage, and recovery from execution failures, ensuring robust performance in dynamic coding tasks. - **Versatile Integration with Real-World IDE**: Its 256k context length, combined with adaptability to various scaffold templates, enables seamless integration with different CLI/IDE platforms (e.g., Claude Code, Qwen Code, Qoder, Kilo, Trae, Cline, etc.), supporting diverse development environments. **Qwen3-Coder-Next** has the following features: - Type: Causal Language Models - Training Stage: Pretraining & Post-training - Number of Parameters: 80B in total and 3B activated - Number of Parameters (Non-Embedding): 79B - Hidden Dimension: 2048 - Number of Layers: 48 - Hybrid Layout: 12 \* (3 \* (Gated DeltaNet -> MoE) -> 1 \* (Gated Attention -> MoE)) - Gated Attention: - Number of Attention Heads: 16 for Q and 2 for KV - Head Dimension: 256 - Rotary Position Embedding Dimension: 64 - Gated DeltaNet: - Number of Linear Attention Heads: 32 for V and 16 for QK - Head Dimension: 128 - Mixture of Experts: - Number of Experts: 512 - Number of Activated Experts: 10 - Number of Shared Experts: 1 - Expert Intermediate Dimension: 512 - Context Length: 262,144 natively

主な特徴

特点摘要待依据来源补齐，不凭模型名称推断能力。

制約と注意点

具体的な制約を判断する出典が不足しています。実際の性能、遅延、データ方針、ライセンス、提供期間を確認してください。

PRICING & COST

出典別料金と費用分析

料金はチャネル・地域・設定によって異なります。各チャネルの料金は個別に表示し、提供元の統一公式料金とは見なしません。

出典・チャネル入力出力課金単位収集日時
確認可能な料金がありません。出典を確認してください。

月額の基本トークン費用を試算

—

試算はキャッシュ割引、段階料金、マルチモーダル追加料金、検索、税金、追加推論出力を含みません。

INDEPENDENT BENCHMARKS

公開評価と実行設定

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。

収録済みの全ランキング →

よくある質問

オープンウェイトなら無料で商用利用できますか？

必ずしもそうではありません。バージョン別のライセンス、商用条件、利用方針を確認してください。自前運用には計算資源と保守費用も必要です。

これはリアルタイムの請求料金ですか？

収集日時付きの料金スナップショットです。最新のバージョン、地域、割引、課金方式は各チャネルで確認してください。

出典と追跡記録

huggingface · Qwen/Qwen3-Coder-Next-GGUF ↗2026/10/30 17:37:16
huggingface · enrich:2099b37b-f930-4d66-bf49-2f1be6853c8c ↗2026/10/29 12:41:34

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。