K-EXAONE-236B-A23B vs Qwen3 Max
K-EXAONE-236B-A23B and Qwen3 Max are closely matched at 26.2 and 21.7 on the LLM Stats Score. K-EXAONE-236B-A23B is 2.3x cheaper per token.
LG AI Research · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
K-EXAONE-236B-A23B and Qwen3 Max are closely matched on the overall LLM Stats Score at 26.2 and 21.7.
In the 3 individual benchmarks reported for both models, K-EXAONE-236B-A23B wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, K-EXAONE-236B-A23B is roughly 2.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Qwen3 Max also accepts a larger context window (256,000 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 value its reported benchmark strengths — it wins 2 of 3 exact shared results
- cost matters — it's about 2.3x cheaper per token
- you want the most recent training data — it shipped Dec 2025
Choose Qwen3 Max
- you process long inputs — it offers a 256,000 token context window
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
6 reported for K-EXAONE-236B-A23B · 6 for Qwen3 Max
K-EXAONE-236B-A23B outperforms in 2 benchmarks (AIME 2025, LiveCodeBench v6), while Qwen3 Max is better at 1 benchmark (t2-bench).
K-EXAONE-236B-A23B 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, K-EXAONE-236B-A23B ($0.60/1M tokens) is 1.2x more expensive than Qwen3 Max ($0.50/1M tokens).
For output processing, K-EXAONE-236B-A23B ($1.00/1M tokens) is 5.0x cheaper than Qwen3 Max ($5.00/1M tokens).
In conclusion, Qwen3 Max is more expensive than K-EXAONE-236B-A23B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 Max has 764.0B more parameters than K-EXAONE-236B-A23B, making it 323.7% larger.
Context Window
Maximum input and output token capacity
Qwen3 Max accepts 256,000 input tokens compared to K-EXAONE-236B-A23B's 32,768 tokens. Qwen3 Max can generate longer responses up to 131,072 tokens, while K-EXAONE-236B-A23B is limited to 32,768 tokens.
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 Qwen3 Max was released on 2025-12-15.
K-EXAONE-236B-A23B is 1 month newer than Qwen3 Max.
Dec 31, 2025
8 months ago
2w newerDec 15, 2025
9 months ago
Knowledge Cutoff
When training data ends
K-EXAONE-236B-A23B has a documented knowledge cutoff of 2025-10-01, while Qwen3 Max'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 Qwen3 Max's cutoff date.
Oct 2025
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Provider Availability
K-EXAONE-236B-A23B is available from FriendliAI. Qwen3 Max is available from Novita, DeepInfra.
K-EXAONE-236B-A23B
Qwen3 Max
Outputs Comparison
Judge for yourself.
Run your own prompts against K-EXAONE-236B-A23B and Qwen3 Max side-by-side, then vote on the output you prefer.
FAQ
Common questions about K-EXAONE-236B-A23B vs Qwen3 Max.