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.

Alibaba

Qwen2.5 7B Instruct

Alibaba

Qwen2.5 7B Instruct is a language model developed by Alibaba. It achieves strong performance with an average score of 65.6% across 14 benchmarks. It excels particularly in GSM8k (91.6%), MT-Bench (87.5%), HumanEval (84.8%). The model shows particular specialization in math tasks with an average performance of 83.5%. It supports a 139K 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 Alibaba's latest advancement in AI technology.

Jamba 1.5 Large

AI21 Labs

2024-08-22

Alibaba

Qwen2.5 7B Instruct

Alibaba

2024-09-19

28 days newer

Pricing Comparison

Cost per million tokens (USD)

Jamba 1.5 Large

Input:$2.00
Output:$8.00
Alibaba

Qwen2.5 7B Instruct

$9.40 cheaper
Input:$0.30
Output:$0.30

Performance Metrics

Context window and performance specifications

Jamba 1.5 Large

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

Qwen2.5 7B Instruct

Max Context:139.3K
Parameters:7.6B

Average performance across 4 common benchmarks

Jamba 1.5 Large

+1.6%
Average Score:60.7%
Alibaba

Qwen2.5 7B Instruct

Average Score:59.1%

Performance comparison across key benchmark categories

Jamba 1.5 Large

math
+3.5%
87.0%
general
57.1%
Alibaba

Qwen2.5 7B Instruct

math
83.5%
general
+3.5%
60.6%
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
Alibaba

Qwen2.5 7B Instruct

1 providers

Together

Throughput: 138 tok/s
Latency: 0.5ms

Jamba 1.5 Large

+1.6%
Avg Score:60.7%
Providers:2
Alibaba

Qwen2.5 7B Instruct

Avg Score:59.1%
Providers:1