Gemini 3.5 Flash-Lite vs Jamba 1.5 Mini
Gemini 3.5 Flash-Lite leads the LLM Stats Score 29.9 to -5.7. Jamba 1.5 Mini is 3.4x cheaper per token.
Google · AI21 Labs · Updated for 2026
Which is better?
Gemini 3.5 Flash-Lite leads the overall LLM Stats Score 29.9 to -5.7, ranking #123 overall.
On price, Jamba 1.5 Mini is roughly 3.4x 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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemini 3.5 Flash-Lite
- overall performance matters — it scores 29.9 and ranks #123 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- 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 Mini
- cost matters — it's about 3.4x cheaper per token
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
6 reported for Gemini 3.5 Flash-Lite · 8 for Jamba 1.5 Mini
Gemini 3.5 Flash-Lite and Jamba 1.5 Minidon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 3.5 Flash-Lite ($0.30/1M tokens) is 1.5x more expensive than Jamba 1.5 Mini ($0.20/1M tokens).
For output processing, Gemini 3.5 Flash-Lite ($2.50/1M tokens) is 6.3x more expensive than Jamba 1.5 Mini ($0.40/1M tokens).
In conclusion, Gemini 3.5 Flash-Lite is more expensive than Jamba 1.5 Mini.*
* 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 Mini's 256,144 tokens. Jamba 1.5 Mini can generate longer responses up to 256,144 tokens, while Gemini 3.5 Flash-Lite is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
Gemini 3.5 Flash-Lite supports multimodal inputs, whereas Jamba 1.5 Mini 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 Mini
License
Usage and distribution terms
Gemini 3.5 Flash-Lite is licensed under a proprietary license, while Jamba 1.5 Mini 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 Mini was released on 2024-08-22.
Gemini 3.5 Flash-Lite is 23 months newer than Jamba 1.5 Mini.
Jul 21, 2026
1 months ago
1.9yr newerAug 22, 2024
2.1 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 Mini 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 Mini (2024-03-05).
Mar 2026
2 yr newerMar 2024
Provider Availability
Gemini 3.5 Flash-Lite is available from Google. Jamba 1.5 Mini is available from Bedrock, Google.
Gemini 3.5 Flash-Lite
Jamba 1.5 Mini
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 3.5 Flash-Lite and Jamba 1.5 Mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 3.5 Flash-Lite vs Jamba 1.5 Mini.