Model Comparison

Phi-3.5-MoE-instruct vs Qwen3-Next-80B-A3B-Thinking

Qwen3-Next-80B-A3B-Thinking significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Phi-3.5-MoE-instruct outperforms in 0 benchmarks, while Qwen3-Next-80B-A3B-Thinking is better at 2 benchmarks (GPQA, MMLU-Pro).

Qwen3-Next-80B-A3B-Thinking significantly outperforms across most benchmarks.

Tue Apr 14 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Tue Apr 14 2026 • llm-stats.com
Microsoft
Phi-3.5-MoE-instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Alibaba Cloud / Qwen Team
Qwen3-Next-80B-A3B-Thinking
Input tokens$0.15
Output tokens$1.50
Best providerNovita
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

20.0B diff

Qwen3-Next-80B-A3B-Thinking has 20.0B more parameters than Phi-3.5-MoE-instruct, making it 33.3% larger.

Microsoft
Phi-3.5-MoE-instruct
60.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3-Next-80B-A3B-Thinking
80.0Bparameters
60.0B
Phi-3.5-MoE-instruct
80.0B
Qwen3-Next-80B-A3B-Thinking

Context Window

Maximum input and output token capacity

Only Qwen3-Next-80B-A3B-Thinking specifies input context (65,536 tokens). Only Qwen3-Next-80B-A3B-Thinking specifies output context (65,536 tokens).

Microsoft
Phi-3.5-MoE-instruct
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen3-Next-80B-A3B-Thinking
Input65,536 tokens
Output65,536 tokens
Tue Apr 14 2026 • llm-stats.com

License

Usage and distribution terms

Phi-3.5-MoE-instruct is licensed under MIT, while Qwen3-Next-80B-A3B-Thinking uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Phi-3.5-MoE-instruct

MIT

Open weights

Qwen3-Next-80B-A3B-Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Phi-3.5-MoE-instruct was released on 2024-08-23, while Qwen3-Next-80B-A3B-Thinking was released on 2025-09-10.

Qwen3-Next-80B-A3B-Thinking is 13 months newer than Phi-3.5-MoE-instruct.

Phi-3.5-MoE-instruct

Aug 23, 2024

1.6 years ago

Qwen3-Next-80B-A3B-Thinking

Sep 10, 2025

7 months ago

1.0yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Microsoft
Alibaba Cloud / Qwen Team
Larger context window (65,536 tokens)
Higher GPQA score (77.2% vs 36.8%)
Higher MMLU-Pro score (82.7% vs 45.3%)

Detailed Comparison

AI Model Comparison Table
Feature
Microsoft
Phi-3.5-MoE-instruct
Alibaba Cloud / Qwen Team
Qwen3-Next-80B-A3B-Thinking

FAQ

Common questions about Phi-3.5-MoE-instruct vs Qwen3-Next-80B-A3B-Thinking

Qwen3-Next-80B-A3B-Thinking significantly outperforms across most benchmarks. Phi-3.5-MoE-instruct is made by Microsoft and Qwen3-Next-80B-A3B-Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Phi-3.5-MoE-instruct scores ARC-C: 91.0%, OpenBookQA: 89.6%, GSM8k: 88.7%, PIQA: 88.6%, RULER: 87.1%. Qwen3-Next-80B-A3B-Thinking scores MMLU-Redux: 92.5%, IFEval: 88.9%, AIME 2025: 87.8%, WritingBench: 84.6%, MMLU-Pro: 82.7%.
Phi-3.5-MoE-instruct supports an unknown number of tokens and Qwen3-Next-80B-A3B-Thinking supports 66K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Phi-3.5-MoE-instruct is developed by Microsoft and Qwen3-Next-80B-A3B-Thinking is developed by Alibaba Cloud / Qwen Team.