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K-EXAONE-236B-A23B vs Qwen3 VL 30B A3B Thinking

K-EXAONE-236B-A23B leads the LLM Stats Score 26.2 to 18.2. Qwen3 VL 30B A3B Thinking is 1.8x cheaper per token.

LG AI Research · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

K-EXAONE-236B-A23B leads the overall LLM Stats Score 26.2 to 18.2, ranking #155 overall.

In the 3 individual benchmarks reported for both models, K-EXAONE-236B-A23B wins 3; this is a narrower head-to-head signal than the composite indexes.

On price, Qwen3 VL 30B A3B Thinking is roughly 1.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Qwen3 VL 30B A3B Thinking also accepts a larger context window (131,072 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

  • overall performance matters — it scores 26.2 and ranks #155 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 3 of 3 exact shared results
  • you want the most recent training data — it shipped Dec 2025

Choose Qwen3 VL 30B A3B Thinking

  • cost matters — it's about 1.8x cheaper per token
  • you process long inputs — it offers a 131,072 token context window
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Core performance indexes
26.2
#155
18.2
#217
27.2
#143
19.5
#203
4.0
#162
7.1
#140
Cost, coverage & limits
Benchmark wins
3 of 3
0 of 3
Input price
$0.60 / M
$0.20 / M
Output price
$1.00 / M
$0.99 / M
Context window
32,768
131,072

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
K-EXAONE-236B-A23B
Qwen3 VL 30B A3B Thinking
28.0#97
22.3#139
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

6 reported for K-EXAONE-236B-A23B · 50 for Qwen3 VL 30B A3B Thinking

3 shared

K-EXAONE-236B-A23B outperforms in 3 benchmarks (AIME 2025, LiveCodeBench v6, MMLU-Pro), while Qwen3 VL 30B A3B Thinking is better at 0 benchmarks.

K-EXAONE-236B-A23B significantly outperforms across most benchmarks.

Tue Sep 22 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Qwen3 VL 30B A3B Thinking costs less

For input processing, K-EXAONE-236B-A23B ($0.60/1M tokens) is 3.0x more expensive than Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).

For output processing, K-EXAONE-236B-A23B ($1.00/1M tokens) is 1.0x more expensive than Qwen3 VL 30B A3B Thinking ($0.99/1M tokens).

In conclusion, K-EXAONE-236B-A23B is more expensive than Qwen3 VL 30B A3B Thinking.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Tue Sep 22 2026 • llm-stats.com
LG AI Research
K-EXAONE-236B-A23B
Input tokens$0.60
Output tokens$1.00
Best providerFriendliAI
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Input tokens$0.20
Output tokens$0.99
Best providerNovita
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

205.0B diff

K-EXAONE-236B-A23B has 205.0B more parameters than Qwen3 VL 30B A3B Thinking, making it 661.3% larger.

LG AI Research
K-EXAONE-236B-A23B
236.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
31.0Bparameters
236.0B
K-EXAONE-236B-A23B
31.0B
Qwen3 VL 30B A3B Thinking

Context Window

Maximum input and output token capacity

Qwen3 VL 30B A3B Thinking accepts 131,072 input tokens compared to K-EXAONE-236B-A23B's 32,768 tokens. Both models can generate responses up to 32,768 tokens.

LG AI Research
K-EXAONE-236B-A23B
Input32,768 tokens
Output32,768 tokens
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Input131,072 tokens
Output32,768 tokens
Tue Sep 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Qwen3 VL 30B A3B Thinking supports multimodal inputs, whereas K-EXAONE-236B-A23B does not.

Qwen3 VL 30B A3B Thinking 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

Qwen3 VL 30B A3B Thinking

Text
Images
Audio
Video

License

Usage and distribution terms

K-EXAONE-236B-A23B is licensed under a proprietary license, while Qwen3 VL 30B A3B Thinking uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

K-EXAONE-236B-A23B

Proprietary

Closed source

Qwen3 VL 30B A3B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

K-EXAONE-236B-A23B was released on 2025-12-31, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.

K-EXAONE-236B-A23B is 3 months newer than Qwen3 VL 30B A3B Thinking.

K-EXAONE-236B-A23B

Dec 31, 2025

8 months ago

3mo newer
Qwen3 VL 30B A3B Thinking

Sep 22, 2025

1.0 years ago

Knowledge Cutoff

When training data ends

K-EXAONE-236B-A23B has a documented knowledge cutoff of 2025-10-01, while Qwen3 VL 30B A3B Thinking'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 VL 30B A3B Thinking's cutoff date.

K-EXAONE-236B-A23B

Oct 2025

Qwen3 VL 30B A3B Thinking

Provider Availability

K-EXAONE-236B-A23B is available from FriendliAI. Qwen3 VL 30B A3B Thinking is available from Novita, DeepInfra.

K-EXAONE-236B-A23B

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

Qwen3 VL 30B A3B Thinking

novita logo
Novita
Input Price:Input: $0.20/1MOutput Price:Output: $1.00/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.29/1MOutput Price:Output: $0.99/1M
* 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 Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.

K-EXAONE-236B-A23B
✓ Preferred
Qwen3 VL 30B A3B Thinking
Open in Playground

FAQ

Common questions about K-EXAONE-236B-A23B vs Qwen3 VL 30B A3B Thinking.

Which is better, K-EXAONE-236B-A23B or Qwen3 VL 30B A3B Thinking?

K-EXAONE-236B-A23B leads the LLM Stats Score 26.2 to 18.2. K-EXAONE-236B-A23B is made by LG AI Research and Qwen3 VL 30B A3B Thinking is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does K-EXAONE-236B-A23B compare to Qwen3 VL 30B A3B Thinking 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%. Qwen3 VL 30B A3B Thinking scores DocVQAtest: 95.0%, ScreenSpot: 94.7%, MMLU-Redux: 90.9%, MMBench-V1.1: 88.9%, MMLU: 87.6%.

Is K-EXAONE-236B-A23B cheaper than Qwen3 VL 30B A3B Thinking?

Qwen3 VL 30B A3B Thinking is 3.0x cheaper for input tokens. K-EXAONE-236B-A23B costs $0.60/M input and $1.00/M output via friendli. Qwen3 VL 30B A3B Thinking costs $0.20/M input and $0.99/M output via novita.

What are the context window sizes for K-EXAONE-236B-A23B and Qwen3 VL 30B A3B Thinking?

K-EXAONE-236B-A23B supports 33K tokens and Qwen3 VL 30B A3B Thinking supports 131K 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 Qwen3 VL 30B A3B Thinking?

Key differences include LLM Stats Score (26.2 vs 18.2), context window (33K vs 131K), input pricing ($0.60 vs $0.20/M), multimodal support (no vs yes), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes K-EXAONE-236B-A23B and Qwen3 VL 30B A3B Thinking?

K-EXAONE-236B-A23B is developed by LG AI Research and Qwen3 VL 30B A3B Thinking is developed by Alibaba Cloud / Qwen Team.