Model Comparison

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

Jamba 1.5 Mini

AI21 Labs

Jamba 1.5 Mini is a language model developed by AI21 Labs. The model shows competitive results across 8 benchmarks. It excels particularly in ARC-C (85.7%), GSM8k (75.8%), MMLU (69.7%). It supports a 512K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, it represents AI21 Labs's latest advancement in AI technology.

Microsoft

Phi-3.5-MoE-instruct

Microsoft

Phi-3.5-MoE-instruct is a language model developed by Microsoft. It achieves strong performance with an average score of 65.6% across 31 benchmarks. It excels particularly in ARC-C (91.0%), OpenBookQA (89.6%), GSM8k (88.7%). The model shows particular specialization in reasoning tasks with an average performance of 85.4%. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.

Jamba 1.5 Mini

AI21 Labs

2024-08-22

Microsoft

Phi-3.5-MoE-instruct

Microsoft

2024-08-23

1 days newer

Performance Metrics

Context window and performance specifications

Jamba 1.5 Mini

Larger context
Max Context:512.3K
Parameters:52.0B
Microsoft

Phi-3.5-MoE-instruct

Max Context:-
Parameters:60.0B

Average performance across 7 common benchmarks

Jamba 1.5 Mini

Average Score:58.0%
Microsoft

Phi-3.5-MoE-instruct

+7.1%
Average Score:65.2%

Performance comparison across key benchmark categories

Jamba 1.5 Mini

reasoning
+0.3%
85.7%
factuality
54.1%
math
+6.8%
75.8%
general
46.6%
Microsoft

Phi-3.5-MoE-instruct

reasoning
85.4%
factuality
+23.4%
77.5%
math
69.0%
general
+14.3%
60.9%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Jamba 1.5 Mini

2024-03-05

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Jamba 1.5 Mini

2 providers

Google

Throughput: 100 tok/s
Latency: 0.3ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms
Microsoft

Phi-3.5-MoE-instruct

0 providers

Jamba 1.5 Mini

Avg Score:58.0%
Providers:2
Microsoft

Phi-3.5-MoE-instruct

+7.1%
Avg Score:65.2%
Providers:0