Model Comparison

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

Jamba 1.5 Large

AI21 Labs

Jamba 1.5 Large is a language model developed by AI21 Labs. It achieves strong performance with an average score of 65.5% across 8 benchmarks. It excels particularly in ARC-C (93.0%), GSM8k (87.0%), MMLU (81.2%). 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 Large

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 Large

Larger context
Max Context:512.0K
Parameters:398.0B
Microsoft

Phi-3.5-MoE-instruct

Max Context:-
Parameters:60.0B

Average performance across 7 common benchmarks

Jamba 1.5 Large

+2.7%
Average Score:67.9%
Microsoft

Phi-3.5-MoE-instruct

Average Score:65.2%

Performance comparison across key benchmark categories

Jamba 1.5 Large

reasoning
+7.6%
93.0%
math
+18.0%
87.0%
factuality
58.3%
general
57.1%
Microsoft

Phi-3.5-MoE-instruct

reasoning
85.4%
math
69.0%
factuality
+19.2%
77.5%
general
+3.8%
60.9%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Jamba 1.5 Large

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 Large

2 providers

Google

Throughput: 42 tok/s
Latency: 0.3ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms
Microsoft

Phi-3.5-MoE-instruct

0 providers

Jamba 1.5 Large

+2.7%
Avg Score:67.9%
Providers:2
Microsoft

Phi-3.5-MoE-instruct

Avg Score:65.2%
Providers:0