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.

Meta

Llama 3.2 11B Instruct

Meta

Llama 3.2 11B Instruct is a multimodal language model developed by Meta. It achieves strong performance with an average score of 63.6% across 11 benchmarks. It excels particularly in AI2D (91.1%), DocVQA (88.4%), ChartQA (83.4%). It supports a 256K token context window for handling large documents. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents Meta's latest advancement in AI technology.

Jamba 1.5 Mini

AI21 Labs

2024-08-22

Meta

Llama 3.2 11B Instruct

Meta

2024-09-25

1 month newer

Pricing Comparison

Cost per million tokens (USD)

Jamba 1.5 Mini

Input:$0.20
Output:$0.40
Meta

Llama 3.2 11B Instruct

$0.50 cheaper
Input:$0.05
Output:$0.05

Performance Metrics

Context window and performance specifications

Jamba 1.5 Mini

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

Llama 3.2 11B Instruct

Max Context:256.0K
Parameters:10.6B

Average performance across 2 common benchmarks

Jamba 1.5 Mini

Average Score:51.0%
Meta

Llama 3.2 11B Instruct

+1.9%
Average Score:52.9%

Performance comparison across key benchmark categories

Jamba 1.5 Mini

math
+18.4%
75.8%
general
46.6%
Meta

Llama 3.2 11B Instruct

math
57.4%
general
+23.5%
70.1%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Llama 3.2 11B Instruct

2023-12-31

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
Meta

Llama 3.2 11B Instruct

6 providers

Sambanova

Throughput: 100 tok/s
Latency: 0.5ms

Together

Throughput: 168 tok/s
Latency: 0.5ms

DeepInfra

Throughput: 108 tok/s
Latency: 0.5ms

Fireworks

Throughput: 125 tok/s
Latency: 0.2ms

Groq

Throughput: 100 tok/s
Latency: 0.5ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms

Jamba 1.5 Mini

Avg Score:51.0%
Providers:2
Meta

Llama 3.2 11B Instruct

+1.9%
Avg Score:52.9%
Providers:6