Model Comparison
Gemini 3 Pro vs Jamba 1.5 LargeWhich is better in 2026?
Gemini 3 Pro significantly outperforms across most benchmarks. Jamba 1.5 Large is 1.3x cheaper per token.
Verdict: Gemini 3 Pro vs Jamba 1.5 Large — which is better?
Gemini 3 Pro (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.
Gemini 3 Pro outperforms in 1 benchmarks (GPQA), while Jamba 1.5 Large is better at 0 benchmarks. Gemini 3 Pro significantly outperforms across most benchmarks.
On price, Jamba 1.5 Large is roughly 1.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 3 Pro 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 Pro if…
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Nov 2025
Choose Jamba 1.5 Large if…
- cost matters — it's about 1.3x cheaper per token
- you need open weights you can self-host or fine-tune
Performance Benchmarks
Comparative analysis across standard metrics
Gemini 3 Pro outperforms in 1 benchmarks (GPQA), while Jamba 1.5 Large is better at 0 benchmarks.
Gemini 3 Pro significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 3 Pro ($2.00/1M tokens) costs the same as Jamba 1.5 Large ($2.00/1M tokens).
For output processing, Gemini 3 Pro ($12.00/1M tokens) is 1.5x more expensive than Jamba 1.5 Large ($8.00/1M tokens).
In conclusion, Gemini 3 Pro is more expensive than Jamba 1.5 Large.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 3 Pro 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 Pro is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Gemini 3 Pro supports multimodal inputs, whereas Jamba 1.5 Large does not.
Gemini 3 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 3 Pro
Jamba 1.5 Large
License
Usage and distribution terms
Gemini 3 Pro 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 Pro was released on 2025-11-18, while Jamba 1.5 Large was released on 2024-08-22.
Gemini 3 Pro is 15 months newer than Jamba 1.5 Large.
Nov 18, 2025
6 months ago
1.2yr newerAug 22, 2024
1.8 years ago
Knowledge Cutoff
When training data ends
Gemini 3 Pro has a knowledge cutoff of 2025-01-31, while Jamba 1.5 Large has a cutoff of 2024-03-05.
Gemini 3 Pro has more recent training data (up to 2025-01-31), making it potentially better informed about events through that date compared to Jamba 1.5 Large (2024-03-05).
Jan 2025
10 mo newerMar 2024
Provider Availability
Gemini 3 Pro is available from Google. Jamba 1.5 Large is available from Bedrock, Google.
Gemini 3 Pro
Jamba 1.5 Large
Outputs Comparison
Key Takeaways
Gemini 3 Pro
View details
Jamba 1.5 Large
View detailsAI21 Labs
Detailed Comparison
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FAQ
Common questions about Gemini 3 Pro vs Jamba 1.5 Large.