Model Comparison
Gemini 3.1 Pro vs K-EXAONE-236B-A23BWhich is better in 2026?
Gemini 3.1 Pro significantly outperforms across most benchmarks. K-EXAONE-236B-A23B is 8.0x cheaper per token.
Verdict: Gemini 3.1 Pro vs K-EXAONE-236B-A23B — which is better?
Gemini 3.1 Pro (by Google) and K-EXAONE-236B-A23B (by LG AI Research) 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 3.1 Pro outperforms in 2 benchmarks (MMMLU, t2-bench), while K-EXAONE-236B-A23B is better at 0 benchmarks. Gemini 3.1 Pro significantly outperforms across most benchmarks.
On price, K-EXAONE-236B-A23B is roughly 8.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 3.1 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 3.1 Pro if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Feb 2026
Choose K-EXAONE-236B-A23B if…
- cost matters — it's about 8.0x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
Gemini 3.1 Pro outperforms in 2 benchmarks (MMMLU, t2-bench), while K-EXAONE-236B-A23B is better at 0 benchmarks.
Gemini 3.1 Pro significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Gemini 3.1 Pro ($2.50/1M tokens) is 4.2x more expensive than K-EXAONE-236B-A23B ($0.60/1M tokens).
For output processing, Gemini 3.1 Pro ($15.00/1M tokens) is 15.0x more expensive than K-EXAONE-236B-A23B ($1.00/1M tokens).
In conclusion, Gemini 3.1 Pro is more expensive than K-EXAONE-236B-A23B.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 3.1 Pro accepts 1,048,576 input tokens compared to K-EXAONE-236B-A23B's 32,768 tokens. Gemini 3.1 Pro can generate longer responses up to 65,536 tokens, while K-EXAONE-236B-A23B is limited to 32,768 tokens.
Input Capabilities
Supported data types and modalities
Gemini 3.1 Pro supports multimodal inputs, whereas K-EXAONE-236B-A23B does not.
Gemini 3.1 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemini 3.1 Pro
K-EXAONE-236B-A23B
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
Gemini 3.1 Pro was released on 2026-02-19, while K-EXAONE-236B-A23B was released on 2025-12-31.
Gemini 3.1 Pro is 2 months newer than K-EXAONE-236B-A23B.
Feb 19, 2026
3 months ago
1mo newerDec 31, 2025
5 months ago
Knowledge Cutoff
When training data ends
Gemini 3.1 Pro has a knowledge cutoff of 2025-01-31, while K-EXAONE-236B-A23B has a cutoff of 2025-10-01.
K-EXAONE-236B-A23B has more recent training data (up to 2025-10-01), making it potentially better informed about events through that date compared to Gemini 3.1 Pro (2025-01-31).
Jan 2025
Oct 2025
9 mo newerProvider Availability
Gemini 3.1 Pro is available from Google. K-EXAONE-236B-A23B is available from FriendliAI.
Gemini 3.1 Pro
K-EXAONE-236B-A23B
Outputs Comparison
Key Takeaways
K-EXAONE-236B-A23B
View detailsLG AI Research
Detailed Comparison
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FAQ
Common questions about Gemini 3.1 Pro vs K-EXAONE-236B-A23B.