Model Comparison

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

Google

Gemini 2.0 Flash-Lite

Google

Gemini 2.0 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in MATH (86.8%), FACTS Grounding (83.6%), Global-MMLU-Lite (78.2%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.

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.

Jamba 1.5 Large

AI21 Labs

2024-08-22

Google

Gemini 2.0 Flash-Lite

Google

2025-02-05

5 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 2.0 Flash-Lite

$9.63 cheaper
Input:$0.07
Output:$0.30

Jamba 1.5 Large

Input:$2.00
Output:$8.00

Performance Metrics

Context window and performance specifications

Google

Gemini 2.0 Flash-Lite

Larger context
Max Context:1.1M

Jamba 1.5 Large

Max Context:512.0K
Parameters:398.0B

Average performance across 2 common benchmarks

Google

Gemini 2.0 Flash-Lite

+16.3%
Average Score:61.5%

Jamba 1.5 Large

Average Score:45.2%

Performance comparison across key benchmark categories

Google

Gemini 2.0 Flash-Lite

math
71.0%
factuality
+25.3%
83.6%
general
55.5%

Jamba 1.5 Large

math
+16.0%
87.0%
factuality
58.3%
general
+1.6%
57.1%
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

Gemini 2.0 Flash-Lite

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 2.0 Flash-Lite

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms

Jamba 1.5 Large

2 providers

Google

Throughput: 42 tok/s
Latency: 0.3ms

Bedrock

Throughput: 100 tok/s
Latency: 0.5ms
Google

Gemini 2.0 Flash-Lite

+16.3%
Avg Score:61.5%
Providers:1

Jamba 1.5 Large

Avg Score:45.2%
Providers:2