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Qwen | Qwen3 Next 80b A3b Instruct

Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual use, while remaining robust on alignment and formatting. Compared with prior Qwen3 instruct variants, it focuses on higher throughput and stability on ultra-long inputs and multi-turn dialogues, making it well-suited for RAG, tool use, and agentic workflows that require consistent final answers rather than visible chain-of-thought. The model employs scaling-efficient training and decoding to improve parameter efficiency and inference speed, and has been validated on a broad set of public benchmarks where it reaches or approaches larger Qwen3 systems in several categories while outperforming earlier mid-sized baselines. It is best used as a general assistant, code helper, and long-context task solver in production settings where deterministic, instruction-following outputs are preferred.

Compare

Fair

49.3
Most Recent Test

Significant guardrail issues may impede work.

Strengths

  • Excellent at 3.2. Historical Jesus
  • Excellent at 3.4. The Resurrection

Weaknesses

  • Limited task completion capability
  • Struggles with 1.1. Missiological Research
  • Struggles with 1.3. Apologetics
  • Struggles with 3.3. The Crucifixion
  • Struggles with 3.5. Universal Sinfulness
Overall Score
49.3
Tier 1 (Task) 70%
46.7
Tier 2 (Doctrine) 20%
55.0
Tier 3 (Worldview) 10%
56.7
Performance Profile
Visual representation of performance across all evaluated categories
Model Information
Description

Qwen3-Next-80B-A3B-Instruct is an instruction-tuned chat model in the Qwen3-Next series optimized for fast, stable responses without “thinking” traces. It targets complex tasks across reasoning, code generation, knowledge QA, and multilingual use, while remaining robust on alignment and formatting. Compared with prior Qwen3 instruct variants, it focuses on higher throughput and stability on ultra-long inputs and multi-turn dialogues, making it well-suited for RAG, tool use, and agentic workflows that require consistent final answers rather than visible chain-of-thought. The model employs scaling-efficient training and decoding to improve parameter efficiency and inference speed, and has been validated on a broad set of public benchmarks where it reaches or approaches larger Qwen3 systems in several categories while outperforming earlier mid-sized baselines. It is best used as a general assistant, code helper, and long-context task solver in production settings where deterministic, instruction-following outputs are preferred.

Provider

Qwen

Model ID

qwen/qwen3-next-80b-a3b-instruct

Tests Run

2

Insights & Analysis

Categories

Category Heatmap
Performance breakdown by category - darker green indicates stronger alignment
17
1.1
47
1.2
23
1.3
77
1.4
47
1.5
57
1.6
60
1.7
60
2.1
60
2.2
60
2.3
70
2.4
40
2.5
40
2.6
50
3.1
100
3.2
38
3.3
100
3.4
0
3.5
67
3.6
Low
High
Category Breakdown (Bar Chart)
Performance across different categories
1.x = Task Capability2.x = Gospel Core3.x = Worldview Confession

Recent Tests

Recent Test Runs
DateScoreVersionTier 1 (Task)Tier 2 (Gospel)Tier 3 (Worldview)Trust Tier
2/7/202649.31.0.046.755.056.7automated
1/12/202647.31.0.047.646.746.7community