K-EXAONE-236B-A23B vs Muse Spark 1.3
Muse Spark 1.3 leads the LLM Stats Score 54.4 to 26.2. Muse Spark 1.3 is 5.6x cheaper per token.
LG AI Research · Meta · Updated for 2026
Which is better?
Muse Spark 1.3 leads the overall LLM Stats Score 54.4 to 26.2, ranking #6 overall.
On price, Muse Spark 1.3 is roughly 5.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Muse Spark 1.3 also accepts a larger context window (1,048,576 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 want predictable pricing at $0.60/M input and $1.00/M output
Choose Muse Spark 1.3
- overall performance matters — it scores 54.4 and ranks #6 on LLM Stats
- your work emphasizes reasoning and agents — it leads those capability indexes
- cost matters — it's about 5.6x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Individual benchmarks
6 reported for K-EXAONE-236B-A23B · 11 for Muse Spark 1.3
K-EXAONE-236B-A23B and Muse Spark 1.3don'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
Pricing Analysis
Price comparison per million tokens
For input processing, K-EXAONE-236B-A23B ($0.60/1M tokens) is 6.0x more expensive than Muse Spark 1.3 ($0.10/1M tokens).
For output processing, K-EXAONE-236B-A23B ($1.00/1M tokens) is 5.0x more expensive than Muse Spark 1.3 ($0.20/1M tokens).
In conclusion, K-EXAONE-236B-A23B is more expensive than Muse Spark 1.3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Muse Spark 1.3 accepts 1,048,576 input tokens compared to K-EXAONE-236B-A23B's 32,768 tokens. Muse Spark 1.3 can generate longer responses up to 943,718 tokens, while K-EXAONE-236B-A23B is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Muse Spark 1.3 supports multimodal inputs, whereas K-EXAONE-236B-A23B does not.
Muse Spark 1.3 can handle both text and other forms of data like images, making it suitable for multimodal applications.
K-EXAONE-236B-A23B
Muse Spark 1.3
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
K-EXAONE-236B-A23B was released on 2025-12-31, while Muse Spark 1.3 was released on 2026-09-02.
Muse Spark 1.3 is 8 months newer than K-EXAONE-236B-A23B.
Dec 31, 2025
8 months ago
Sep 2, 2026
1 weeks ago
8mo newerKnowledge Cutoff
When training data ends
K-EXAONE-236B-A23B has a documented knowledge cutoff of 2025-10-01, while Muse Spark 1.3'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 Muse Spark 1.3's cutoff date.
Oct 2025
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Provider Availability
K-EXAONE-236B-A23B is available from FriendliAI. Muse Spark 1.3 is available from Meta Model API.
K-EXAONE-236B-A23B
Muse Spark 1.3
Outputs Comparison
Judge for yourself.
Run your own prompts against K-EXAONE-236B-A23B and Muse Spark 1.3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about K-EXAONE-236B-A23B vs Muse Spark 1.3.