Model Comparison

Gemini 3.1 Pro vs K-EXAONE-236B-A23B

Gemini 3.1 Pro significantly outperforms across most benchmarks. K-EXAONE-236B-A23B is 8.0x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

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.

Tue Apr 07 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

K-EXAONE-236B-A23B costs less

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

Lowest available price from all providers
Tue Apr 07 2026 • llm-stats.com
Google
Gemini 3.1 Pro
Input tokens$2.50
Output tokens$15.00
Best providerGoogle
LG AI Research
K-EXAONE-236B-A23B
Input tokens$0.60
Output tokens$1.00
Best providerUnknown Organization
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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.

Google
Gemini 3.1 Pro
Input1,048,576 tokens
Output65,536 tokens
LG AI Research
K-EXAONE-236B-A23B
Input32,768 tokens
Output32,768 tokens
Tue Apr 07 2026 • llm-stats.com

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

Text
Images
Audio
Video

K-EXAONE-236B-A23B

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

Gemini 3.1 Pro

Proprietary

Closed source

K-EXAONE-236B-A23B

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.

Gemini 3.1 Pro

Feb 19, 2026

1 months ago

1mo newer
K-EXAONE-236B-A23B

Dec 31, 2025

3 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).

Gemini 3.1 Pro

Jan 2025

K-EXAONE-236B-A23B

Oct 2025

9 mo newer

Provider Availability

Gemini 3.1 Pro is available from Google. K-EXAONE-236B-A23B is available from FriendliAI.

Gemini 3.1 Pro

google logo
Google
Input Price:Input: $2.50/1MOutput Price:Output: $15.00/1M

K-EXAONE-236B-A23B

friendli logo
Unknown Organization
Input Price:Input: $0.60/1MOutput Price:Output: $1.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Google
Larger context window (1,048,576 tokens)
Supports multimodal inputs
Higher MMMLU score (92.6% vs 85.7%)
Higher t2-bench score (99.3% vs 73.2%)
LG AI Research
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 3.1 Pro
LG AI Research
K-EXAONE-236B-A23B

FAQ

Common questions about Gemini 3.1 Pro vs K-EXAONE-236B-A23B

Gemini 3.1 Pro significantly outperforms across most benchmarks. Gemini 3.1 Pro is made by Google and K-EXAONE-236B-A23B is made by LG AI Research. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Gemini 3.1 Pro scores t2-bench: 99.3%, LiveCodeBench Pro: 96.2%, GPQA: 94.3%, MMMLU: 92.6%, BrowseComp: 85.9%. K-EXAONE-236B-A23B scores AIME 2025: 92.8%, MMMLU: 85.7%, MMLU-Pro: 83.8%, LiveCodeBench v6: 80.7%, t2-bench: 73.2%.
K-EXAONE-236B-A23B is 4.2x cheaper for input tokens. Gemini 3.1 Pro costs $2.50/M input and $15.00/M output via google. K-EXAONE-236B-A23B costs $0.60/M input and $1.00/M output via friendli.
Gemini 3.1 Pro supports 1.0M tokens and K-EXAONE-236B-A23B supports 33K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (1.0M vs 33K), input pricing ($2.50 vs $0.60/M), multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.
Gemini 3.1 Pro is developed by Google and K-EXAONE-236B-A23B is developed by LG AI Research.