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-3.5-mini-instruct

Microsoft

Phi-3.5-mini-instruct is a language model developed by Microsoft. The model shows competitive results across 31 benchmarks. It excels particularly in GSM8k (86.2%), ARC-C (84.6%), RULER (84.1%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.

Microsoft

Phi-3.5-mini-instruct

Microsoft

2024-08-23

Meta

Llama 4 Maverick

Meta

2025-04-05

7 months newer

Pricing Comparison

Cost per million tokens (USD)

Meta

Llama 4 Maverick

Input:$0.17
Output:$0.60
Microsoft

Phi-3.5-mini-instruct

$0.57 cheaper
Input:$0.10
Output:$0.10

Performance Metrics

Context window and performance specifications

Meta

Llama 4 Maverick

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

Phi-3.5-mini-instruct

Max Context:256.0K
Parameters:3.8B

Average performance across 6 common benchmarks

Meta

Llama 4 Maverick

+25.7%
Average Score:77.8%
Microsoft

Phi-3.5-mini-instruct

Average Score:52.1%

Performance comparison across key benchmark categories

Meta

Llama 4 Maverick

math
+14.9%
75.7%
general
+16.1%
71.5%
code
60.5%
Microsoft

Phi-3.5-mini-instruct

math
60.9%
general
55.4%
code
+5.7%
66.2%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores

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-3.5-mini-instruct

1 providers

Azure

Throughput: 23 tok/s
Latency: 0.52ms
Meta

Llama 4 Maverick

+25.7%
Avg Score:77.8%
Providers:7
Microsoft

Phi-3.5-mini-instruct

Avg Score:52.1%
Providers:1