Gemini 1.5 Pro vs Mistral Large 2
Gemini 1.5 Pro and Mistral Large 2 are closely matched at 12.5 and 8.1 on the LLM Stats Score. Mistral Large 2 is 1.5x cheaper per token.
Google · Mistral AI · Updated for 2026
Which is better?
Gemini 1.5 Pro and Mistral Large 2 are closely matched on the overall LLM Stats Score at 12.5 and 8.1.
In the 3 individual benchmarks reported for both models, Mistral Large 2 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Mistral Large 2 is roughly 1.5x 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
- you process long inputs — it offers a 2,097,152 token context window
Choose Mistral Large 2
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- cost matters — it's about 1.5x cheaper per token
- you want the most recent training data — it shipped Jul 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 · 5 for Mistral Large 2
Gemini 1.5 Pro outperforms in 1 benchmarks (MMLU), while Mistral Large 2 is better at 2 benchmarks (GSM8k, HumanEval).
Mistral Large 2 shows notably better performance in the majority of 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 1.3x more expensive than Mistral Large 2 ($2.00/1M tokens).
For output processing, Gemini 1.5 Pro ($10.00/1M tokens) is 1.7x more expensive than Mistral Large 2 ($6.00/1M tokens).
In conclusion, Gemini 1.5 Pro is more expensive than Mistral Large 2.*
* 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 Mistral Large 2's 128,000 tokens. Mistral Large 2 can generate longer responses up to 128,000 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 Mistral Large 2 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
Mistral Large 2
License
Usage and distribution terms
Gemini 1.5 Pro is licensed under a proprietary license, while Mistral Large 2 uses Mistral Research License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Mistral Research License
Open weights
Release Timeline
When each model was launched
Gemini 1.5 Pro was released on 2024-05-01, while Mistral Large 2 was released on 2024-07-24.
Mistral Large 2 is 3 months newer than Gemini 1.5 Pro.
May 1, 2024
2.3 years ago
Jul 24, 2024
2.1 years ago
2mo newerKnowledge Cutoff
When training data ends
Gemini 1.5 Pro has a documented knowledge cutoff of 2023-11-01, while Mistral Large 2's cutoff date is not specified.
We can confirm Gemini 1.5 Pro's training data extends to 2023-11-01, but cannot make a direct comparison without Mistral Large 2's cutoff date.
Nov 2023
—
Provider Availability
Gemini 1.5 Pro is available from Google. Mistral Large 2 is available from Google, Mistral AI.
Gemini 1.5 Pro
Mistral Large 2
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemini 1.5 Pro and Mistral Large 2 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemini 1.5 Pro vs Mistral Large 2.