Model Comparison
Gemini 3.5 Flash-Lite vs Jamba 1.5 LargeWhich is better in 2026?
Comparing Gemini 3.5 Flash-Lite and Jamba 1.5 Large across benchmarks, pricing, and capabilities.
Verdict: Gemini 3.5 Flash-Lite vs Jamba 1.5 Large — which is better?
Gemini 3.5 Flash-Lite (by Google) and Jamba 1.5 Large (by AI21 Labs) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
On price, Gemini 3.5 Flash-Lite is roughly 4.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 3.5 Flash-Lite also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose Gemini 3.5 Flash-Lite if…
- cost matters — it's about 4.1x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jul 2026
Choose Jamba 1.5 Large if…
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
Gemini 3.5 Flash-Lite and Jamba 1.5 Largedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 3.5 Flash-Lite ($0.30/1M tokens) is 6.7x cheaper than Jamba 1.5 Large ($2.00/1M tokens).
For output processing, Gemini 3.5 Flash-Lite ($2.50/1M tokens) is 3.2x cheaper than Jamba 1.5 Large ($8.00/1M tokens).
In conclusion, Jamba 1.5 Large is more expensive than Gemini 3.5 Flash-Lite.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 3.5 Flash-Lite accepts 1,048,576 input tokens compared to Jamba 1.5 Large's 256,000 tokens. Jamba 1.5 Large can generate longer responses up to 256,000 tokens, while Gemini 3.5 Flash-Lite is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Gemini 3.5 Flash-Lite supports multimodal inputs, whereas Jamba 1.5 Large does not.
Gemini 3.5 Flash-Lite can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 3.5 Flash-Lite
Jamba 1.5 Large
License
Usage and distribution terms
Gemini 3.5 Flash-Lite is licensed under a proprietary license, while Jamba 1.5 Large uses Jamba Open Model License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Jamba Open Model License
Open weights
Release Timeline
When each model was launched
Gemini 3.5 Flash-Lite was released on 2026-07-21, while Jamba 1.5 Large was released on 2024-08-22.
Gemini 3.5 Flash-Lite is 23 months newer than Jamba 1.5 Large.
Jul 21, 2026
3 days ago
1.9yr newerAug 22, 2024
1.9 years ago
Knowledge Cutoff
When training data ends
Gemini 3.5 Flash-Lite has a knowledge cutoff of 2026-03-31, while Jamba 1.5 Large has a cutoff of 2024-03-05.
Gemini 3.5 Flash-Lite has more recent training data (up to 2026-03-31), making it potentially better informed about events through that date compared to Jamba 1.5 Large (2024-03-05).
Mar 2026
2 yr newerMar 2024
Provider Availability
Gemini 3.5 Flash-Lite is available from Google. Jamba 1.5 Large is available from Bedrock, Google.
Gemini 3.5 Flash-Lite
Jamba 1.5 Large
Outputs Comparison
Key Takeaways
Jamba 1.5 Large
View detailsAI21 Labs
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Gemini 3.5 Flash-Lite and Jamba 1.5 Large side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Gemini 3.5 Flash-Lite vs Jamba 1.5 Large.