Model Comparison

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

Anthropic

Claude 3 Haiku

Anthropic

Claude 3 Haiku is a multimodal language model developed by Anthropic. It achieves strong performance with an average score of 71.5% across 10 benchmarks. It excels particularly in ARC-C (89.2%), GSM8k (88.9%), HellaSwag (85.9%). The model shows particular specialization in reasoning tasks with an average performance of 87.5%. It supports a 400K token context window for handling large documents. The model is available through 3 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Anthropic's latest advancement in AI technology.

Microsoft

Phi 4

Microsoft

Phi 4 is a language model developed by Microsoft. It achieves strong performance with an average score of 66.0% across 13 benchmarks. It excels particularly in MMLU (84.8%), HumanEval+ (82.8%), HumanEval (82.6%). The model shows particular specialization in math tasks with an average performance of 80.5%. 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.

Anthropic

Claude 3 Haiku

Anthropic

2024-03-13

Microsoft

Phi 4

Microsoft

2024-12-12

9 months newer

Pricing Comparison

Cost per million tokens (USD)

Anthropic

Claude 3 Haiku

Input:$0.25
Output:$1.25
Microsoft

Phi 4

$1.29 cheaper
Input:$0.07
Output:$0.14

Performance Metrics

Context window and performance specifications

Anthropic

Claude 3 Haiku

Larger context
Max Context:400.0K
Microsoft

Phi 4

Max Context:32.0K
Parameters:14.7B

Average performance across 6 common benchmarks

Anthropic

Claude 3 Haiku

Average Score:62.8%
Microsoft

Phi 4

+13.9%
Average Score:76.7%

Performance comparison across key benchmark categories

Anthropic

Claude 3 Haiku

math
67.6%
code
75.9%
general
+4.9%
65.1%
Microsoft

Phi 4

math
+12.9%
80.5%
code
+0.2%
76.1%
general
60.2%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Phi 4

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Anthropic

Claude 3 Haiku

3 providers

Google

Throughput: 42 tok/s
Latency: 0.4ms

Bedrock

Throughput: 104 tok/s
Latency: 0.5ms

Anthropic

Throughput: 100 tok/s
Latency: 0.5ms
Microsoft

Phi 4

1 providers

DeepInfra

Throughput: 33 tok/s
Latency: 0.2ms
Anthropic

Claude 3 Haiku

Avg Score:62.8%
Providers:3
Microsoft

Phi 4

+13.9%
Avg Score:76.7%
Providers:1