Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Microsoft

Phi-3.5-MoE-instruct

Microsoft

Phi-3.5-MoE-instruct is a language model developed by Microsoft. It achieves strong performance with an average score of 65.6% across 31 benchmarks. It excels particularly in ARC-C (91.0%), OpenBookQA (89.6%), GSM8k (88.7%). The model shows particular specialization in reasoning tasks with an average performance of 85.4%. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.

Alibaba

QwQ-32B-Preview

Alibaba

QwQ-32B-Preview is a language model developed by Alibaba. It achieves strong performance with an average score of 64.0% across 4 benchmarks. It excels particularly in MATH-500 (90.6%), GPQA (65.2%), AIME 2024 (50.0%). The model is available through 4 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba's latest advancement in AI technology.

Microsoft

Phi-3.5-MoE-instruct

Microsoft

2024-08-23

Alibaba

QwQ-32B-Preview

Alibaba

2024-11-28

3 months newer

Performance Metrics

Context window and performance specifications

Microsoft

Phi-3.5-MoE-instruct

Max Context:-
Parameters:60.0B
Alibaba

QwQ-32B-Preview

Larger context
Max Context:65.5K
Parameters:32.5B

Average performance across 1 common benchmarks

Microsoft

Phi-3.5-MoE-instruct

Average Score:36.8%
Alibaba

QwQ-32B-Preview

+28.4%
Average Score:65.2%

Performance comparison across key benchmark categories

Microsoft

Phi-3.5-MoE-instruct

math
69.0%
code
+25.8%
75.8%
general
+3.3%
60.9%
Alibaba

QwQ-32B-Preview

math
+21.6%
90.6%
code
50.0%
general
57.6%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

QwQ-32B-Preview

2024-11-28

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Microsoft

Phi-3.5-MoE-instruct

0 providers
Alibaba

QwQ-32B-Preview

4 providers

Together

Throughput: 62.14 tok/s
Latency: 0.74ms

Hyperbolic

Throughput: 31.9 tok/s
Latency: 1.05ms

DeepInfra

Throughput: 76.04 tok/s
Latency: 0.44ms

Fireworks

Throughput: 99.15 tok/s
Latency: 0.53ms
Microsoft

Phi-3.5-MoE-instruct

Avg Score:36.8%
Providers:0
Alibaba

QwQ-32B-Preview

+28.4%
Avg Score:65.2%
Providers:4