Gemini 1.0 Pro vs Jamba 1.5 Mini
Gemini 1.0 Pro and Jamba 1.5 Mini are closely matched at -5.3 and -5.5 on the LLM Stats Score. Jamba 1.5 Mini is 3.0x cheaper per token.
Google · AI21 Labs · Updated for 2026
Which is better?
Gemini 1.0 Pro and Jamba 1.5 Mini are closely matched on the overall LLM Stats Score at -5.3 and -5.5.
The models split the 2 individual benchmarks reported for both models evenly.
On price, Jamba 1.5 Mini is roughly 3.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Jamba 1.5 Mini also accepts a larger context window (256,144 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 1.0 Pro
- you want predictable pricing at $0.50/M input and $1.50/M output
Choose Jamba 1.5 Mini
- cost matters — it's about 3.0x cheaper per token
- you process long inputs — it offers a 256,144 token context window
- 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
9 reported for Gemini 1.0 Pro · 8 for Jamba 1.5 Mini
Gemini 1.0 Pro outperforms in 1 benchmarks (MMLU), while Jamba 1.5 Mini is better at 1 benchmark (GPQA).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 1.0 Pro ($0.50/1M tokens) is 2.5x more expensive than Jamba 1.5 Mini ($0.20/1M tokens).
For output processing, Gemini 1.0 Pro ($1.50/1M tokens) is 3.8x more expensive than Jamba 1.5 Mini ($0.40/1M tokens).
In conclusion, Gemini 1.0 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
Jamba 1.5 Mini accepts 256,144 input tokens compared to Gemini 1.0 Pro's 32,760 tokens. Jamba 1.5 Mini can generate longer responses up to 256,144 tokens, while Gemini 1.0 Pro is limited to 8,192 tokens.
License
Usage and distribution terms
Gemini 1.0 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 1.0 Pro was released on 2024-02-15, while Jamba 1.5 Mini was released on 2024-08-22.
Jamba 1.5 Mini is 6 months newer than Gemini 1.0 Pro.
Feb 15, 2024
2.6 years ago
Aug 22, 2024
2.0 years ago
6mo newerKnowledge Cutoff
When training data ends
Gemini 1.0 Pro has a knowledge cutoff of 2024-02-01, 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 1.0 Pro (2024-02-01).
Feb 2024
Mar 2024
1 mo newerProvider Availability
Gemini 1.0 Pro is available from Google. Jamba 1.5 Mini is available from Bedrock, Google.
Gemini 1.0 Pro
Jamba 1.5 Mini
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 1.0 Pro and Jamba 1.5 Mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 1.0 Pro vs Jamba 1.5 Mini.