Model Comparison

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

Meta

Llama 3.3 70B Instruct

Meta

Llama 3.3 70B Instruct is a language model developed by Meta. It achieves strong performance with an average score of 79.9% across 9 benchmarks. It excels particularly in IFEval (92.1%), MGSM (91.1%), HumanEval (88.4%). The model shows particular specialization in code tasks with an average performance of 89.4%. It supports a 256K token context window for handling large documents. The model is available through 9 API providers. Released in 2024, it represents Meta's latest advancement in AI technology.

Microsoft

Phi 4 Mini Reasoning

Microsoft

Phi 4 Mini Reasoning is a language model developed by Microsoft. It achieves strong performance with an average score of 68.0% across 3 benchmarks. It excels particularly in MATH-500 (94.6%), AIME (57.5%), GPQA (52.0%). 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 3.3 70B Instruct

Meta

2024-12-06

Microsoft

Phi 4 Mini Reasoning

Microsoft

2025-04-30

4 months newer

Performance Metrics

Context window and performance specifications

Meta

Llama 3.3 70B Instruct

Larger context
Max Context:256.0K
Parameters:70.0B
Microsoft

Phi 4 Mini Reasoning

Max Context:-
Parameters:3.8B

Average performance across 1 common benchmarks

Meta

Llama 3.3 70B Instruct

Average Score:50.5%
Microsoft

Phi 4 Mini Reasoning

+1.5%
Average Score:52.0%

Performance comparison across key benchmark categories

Meta

Llama 3.3 70B Instruct

math
84.0%
general
+15.9%
70.7%
Microsoft

Phi 4 Mini Reasoning

math
+10.5%
94.6%
general
54.8%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Phi 4 Mini Reasoning

2025-02-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Meta

Llama 3.3 70B Instruct

9 providers

Sambanova

Throughput: 1096 tok/s
Latency: 0.65ms

Together

Throughput: 65 tok/s
Latency: 0.65ms

Hyperbolic

Throughput: 42 tok/s
Latency: 0.65ms

DeepInfra

Throughput: 37 tok/s
Latency: 0.65ms

Fireworks

Throughput: 197 tok/s
Latency: 0.65ms

Groq

Throughput: 268 tok/s
Latency: 0.65ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms

Lambda

Throughput: 42 tok/s
Latency: 0.65ms

Cerebras

Throughput: 2220 tok/s
Latency: 0.65ms
Microsoft

Phi 4 Mini Reasoning

0 providers
Meta

Llama 3.3 70B Instruct

Avg Score:50.5%
Providers:9
Microsoft

Phi 4 Mini Reasoning

+1.5%
Avg Score:52.0%
Providers:0