Model Comparison

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

Meta

Llama 4 Maverick

Meta

Llama 4 Maverick is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.8% across 13 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (92.3%), ChartQA (90.0%). The model shows particular specialization in vision tasks with an average performance of 75.8%. With a 2.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 7 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, 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 4 Maverick

Meta

2025-04-05

Microsoft

Phi 4 Reasoning

Microsoft

2025-04-30

25 days newer

Performance Metrics

Context window and performance specifications

Meta

Llama 4 Maverick

Larger context
Max Context:2.0M
Parameters:400.0B
Microsoft

Phi 4 Reasoning

Max Context:-
Parameters:14.0B

Average performance across 3 common benchmarks

Meta

Llama 4 Maverick

Average Score:64.6%
Microsoft

Phi 4 Reasoning

+0.1%
Average Score:64.6%

Performance comparison across key benchmark categories

Meta

Llama 4 Maverick

code
60.5%
math
75.7%
general
71.5%
Microsoft

Phi 4 Reasoning

code
+16.2%
76.7%
math
+0.9%
76.6%
general
+2.8%
74.3%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

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 4 Maverick

7 providers

Sambanova

Throughput: 638.7 tok/s
Latency: 2.04ms

Together

Throughput: 97.93 tok/s
Latency: 0.2ms

DeepInfra

Throughput: 83.59 tok/s
Latency: 0.38ms

Fireworks

Throughput: 63.03 tok/s
Latency: 0.62ms

Groq

Throughput: 307.3 tok/s
Latency: 0.27ms

Novita

Throughput: 69.42 tok/s
Latency: 0.62ms

Lambda

Throughput: 93.69 tok/s
Latency: 0.65ms
Microsoft

Phi 4 Reasoning

0 providers
Meta

Llama 4 Maverick

Avg Score:64.6%
Providers:7
Microsoft

Phi 4 Reasoning

+0.1%
Avg Score:64.6%
Providers:0