Model Comparison

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

Meta

Llama 3.2 11B Instruct

Meta

Llama 3.2 11B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 63.6% across 11 benchmarks. It excels particularly in AI2D (91.1%), DocVQA (88.4%), ChartQA (83.4%). It supports a 256K token context window for handling large documents. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Meta's latest advancement in AI technology.

Microsoft

Phi 4 Reasoning

Microsoft

Phi 4 Reasoning is a language model developed by Microsoft. It achieves strong performance with an average score of 75.1% across 11 benchmarks. It excels particularly in FlenQA (97.7%), HumanEval+ (92.9%), IFEval (83.4%). The model shows particular specialization in code tasks with an average performance of 76.7%. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.

Meta

Llama 3.2 11B Instruct

Meta

2024-09-25

Microsoft

Phi 4 Reasoning

Microsoft

2025-04-30

7 months newer

Performance Metrics

Context window and performance specifications

Meta

Llama 3.2 11B Instruct

Larger context
Max Context:256.0K
Parameters:10.6B
Microsoft

Phi 4 Reasoning

Max Context:-
Parameters:14.0B

Average performance across 1 common benchmarks

Meta

Llama 3.2 11B Instruct

Average Score:32.8%
Microsoft

Phi 4 Reasoning

+33.0%
Average Score:65.8%

Performance comparison across key benchmark categories

Meta

Llama 3.2 11B Instruct

math
57.4%
general
70.1%
Microsoft

Phi 4 Reasoning

math
+19.2%
76.6%
general
+4.2%
74.3%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Llama 3.2 11B Instruct

2023-12-31

Phi 4 Reasoning

2025-03-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Meta

Llama 3.2 11B Instruct

6 providers

Sambanova

Throughput: 100 tok/s
Latency: 0.5ms

Together

Throughput: 168 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 108 tok/s
Latency: 0.5ms

Fireworks

Throughput: 125 tok/s
Latency: 0.2ms

Groq

Throughput: 100 tok/s
Latency: 0.5ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms
Microsoft

Phi 4 Reasoning

0 providers
Meta

Llama 3.2 11B Instruct

Avg Score:32.8%
Providers:6
Microsoft

Phi 4 Reasoning

+33.0%
Avg Score:65.8%
Providers:0