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K-EXAONE-236B-A23B vs Parse

Comparing K-EXAONE-236B-A23B and Parse across benchmarks, pricing, and capabilities.

LG AI Research · Cohere · Updated for 2026

Which is better?

K-EXAONE-236B-A23B and Parse trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

K-EXAONE-236B-A23B also accepts a larger context window (32,768 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 K-EXAONE-236B-A23B

  • you process long inputs — it offers a 32,768 token context window

Choose Parse

  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Benchmark wins
Input price
$0.60 / M
— / M
Output price
$1.00 / M
— / M
Context window
32,768
8,192

Individual benchmarks

6 reported for K-EXAONE-236B-A23B · 1 for Parse

No common benchmarks found

K-EXAONE-236B-A23B and Parsedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

233.7B diff

K-EXAONE-236B-A23B has 233.7B more parameters than Parse, making it 10160.9% larger.

LG AI Research
K-EXAONE-236B-A23B
236.0Bparameters
Cohere
Parse
2.3Bparameters
236.0B
K-EXAONE-236B-A23B
2.3B
Parse

Context Window

Maximum input and output token capacity

K-EXAONE-236B-A23B accepts 32,768 input tokens compared to Parse's 8,192 tokens. Only K-EXAONE-236B-A23B specifies output context (32,768 tokens).

LG AI Research
K-EXAONE-236B-A23B
Input32,768 tokens
Output32,768 tokens
Cohere
Parse
Input8,192 tokens
Output- tokens
Mon Sep 21 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Parse supports multimodal inputs, whereas K-EXAONE-236B-A23B does not.

Parse can handle both text and other forms of data like images, making it suitable for multimodal applications.

K-EXAONE-236B-A23B

Text
Images
Audio
Video

Parse

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.

K-EXAONE-236B-A23B

Proprietary

Closed source

Parse

Proprietary

Closed source

Release Timeline

When each model was launched

K-EXAONE-236B-A23B was released on 2025-12-31, while Parse was released on 2026-08-27.

Parse is 8 months newer than K-EXAONE-236B-A23B.

K-EXAONE-236B-A23B

Dec 31, 2025

8 months ago

Parse

Aug 27, 2026

3 weeks ago

7mo newer

Knowledge Cutoff

When training data ends

K-EXAONE-236B-A23B has a documented knowledge cutoff of 2025-10-01, while Parse's cutoff date is not specified.

We can confirm K-EXAONE-236B-A23B's training data extends to 2025-10-01, but cannot make a direct comparison without Parse's cutoff date.

K-EXAONE-236B-A23B

Oct 2025

Parse

Provider Availability

K-EXAONE-236B-A23B is available from FriendliAI. Parse is available from Azure, Cohere.

K-EXAONE-236B-A23B

friendli logo
FriendliAI
Input Price:Input: $0.60/1MOutput Price:Output: $1.00/1M

Parse

azure logo
Azure
cohere logo
Cohere
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against K-EXAONE-236B-A23B and Parse side-by-side, then vote on the output you prefer.

K-EXAONE-236B-A23B
✓ Preferred
Parse
Open in Playground

FAQ

Common questions about K-EXAONE-236B-A23B vs Parse.

Which is better, K-EXAONE-236B-A23B or Parse?

K-EXAONE-236B-A23B (LG AI Research) and Parse (Cohere) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does K-EXAONE-236B-A23B compare to Parse in benchmarks?

K-EXAONE-236B-A23B scores AIME 2025: 92.8%, MMMLU: 85.7%, MMLU-Pro: 83.8%, LiveCodeBench v6: 80.7%, t2-bench: 73.2%. Parse scores ParseBench: 79.2%.

What are the context window sizes for K-EXAONE-236B-A23B and Parse?

K-EXAONE-236B-A23B supports 33K tokens and Parse supports 8K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between K-EXAONE-236B-A23B and Parse?

Key differences include context window (33K vs 8K), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

Who makes K-EXAONE-236B-A23B and Parse?

K-EXAONE-236B-A23B is developed by LG AI Research and Parse is developed by Cohere.