Gemini 1.5 Pro vs Jamba 1.5 Mini
Gemini 1.5 Pro leads the LLM Stats Score 12.0 to -5.7. Jamba 1.5 Mini is 17.5x cheaper per token.
Google · AI21 Labs · Updated for 2026
Which is better?
Gemini 1.5 Pro leads the overall LLM Stats Score 12.0 to -5.7, ranking #271 overall.
In the 4 individual benchmarks reported for both models, Gemini 1.5 Pro wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Jamba 1.5 Mini is roughly 17.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 1.5 Pro also accepts a larger context window (2,097,152 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 1.5 Pro
- overall performance matters — it scores 12.0 and ranks #271 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
- you process long inputs — it offers a 2,097,152 token context window
Choose Jamba 1.5 Mini
- cost matters — it's about 17.5x cheaper per token
- you want the most recent training data — it shipped Aug 2024
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
23 reported for Gemini 1.5 Pro · 8 for Jamba 1.5 Mini
Gemini 1.5 Pro outperforms in 4 benchmarks (GPQA, GSM8k, MMLU, MMLU-Pro), while Jamba 1.5 Mini is better at 0 benchmarks.
Gemini 1.5 Pro significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 1.5 Pro ($2.50/1M tokens) is 12.5x more expensive than Jamba 1.5 Mini ($0.20/1M tokens).
For output processing, Gemini 1.5 Pro ($10.00/1M tokens) is 25.0x more expensive than Jamba 1.5 Mini ($0.40/1M tokens).
In conclusion, Gemini 1.5 Pro 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 1.5 Pro accepts 2,097,152 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 1.5 Pro is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Gemini 1.5 Pro supports multimodal inputs, whereas Jamba 1.5 Mini does not.
Gemini 1.5 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 1.5 Pro
Jamba 1.5 Mini
License
Usage and distribution terms
Gemini 1.5 Pro 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 1.5 Pro was released on 2024-05-01, while Jamba 1.5 Mini was released on 2024-08-22.
Jamba 1.5 Mini is 4 months newer than Gemini 1.5 Pro.
May 1, 2024
2.4 years ago
Aug 22, 2024
2.1 years ago
3mo newerKnowledge Cutoff
When training data ends
Gemini 1.5 Pro has a knowledge cutoff of 2023-11-01, while Jamba 1.5 Mini has a cutoff of 2024-03-05.
Jamba 1.5 Mini has more recent training data (up to 2024-03-05), making it potentially better informed about events through that date compared to Gemini 1.5 Pro (2023-11-01).
Nov 2023
Mar 2024
4 mo newerProvider Availability
Gemini 1.5 Pro is available from Google. Jamba 1.5 Mini is available from Bedrock, Google.
Gemini 1.5 Pro
Jamba 1.5 Mini
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 1.5 Pro and Jamba 1.5 Mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 1.5 Pro vs Jamba 1.5 Mini.