Qwen3-Coder-Next

Name: Qwen3-Coder-Next
Author: Alibaba

AlibabaOpen WeightsPending Human Review

Qwen3-Coder-Next is an open-weight coding-agent model built from Qwen3-Next-80B-A3B-Base. It combines hybrid attention with an 80B MoE model that activates 3B parameters, targeting efficient software engineering and local agent development. Native 256K context supports repository-level tasks, while agent-oriented training improves tool use, code execution, and recovery from failures. Apache-2.0 base and instruction-tuned weights are available. The released post-trained checkpoint uses non-thinking mode and a dedicated function-call format.

2026-02-02

80B total, 3B activated

Mixture of Experts (MoE) with hybrid Gated DeltaNet and gated attention

Apache-2.0

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Specifications

Parameters: 80B total, 3B activated
Architecture: Mixture of Experts (MoE) with hybrid Gated DeltaNet and gated attention
License: Apache-2.0
Context Window: 262,144 tokens
Type: text
Modalities: text

Benchmark Scores

Advanced Specifications

Model Family: Qwen
Finetuned From: Qwen3-Next-80B-A3B-Base
API Access: Not Available
Chat Interface: Not Available
Variants: Qwen3-Coder-Next-BaseQwen3-Coder-Next

Capabilities & Limitations

Capabilities: agentic codingtool userepository reasoningcode debugging
Known Limitations: Self-hosting requires sufficient memory for all model weights, including inactive experts.Reasoning and agent benchmark results depend on the harness and sampling settings.Only non-thinking behavior is supported by the post-trained checkpoint.
Notable Use Cases: local coding agentsrepository maintenancesoftware engineering research
Function Calling Support: Yes
Tool Use Support: Yes

Resources

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Typetext

Parameters35.95B total, approximately 3B active

2026-09-25

Open Weights

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