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K-EXAONE-236B-A23B vs LFM3-1.7B

K-EXAONE-236B-A23B and LFM3-1.7B are closely matched at 25.5 and 25.0 on the LLM Stats Score.

LG AI Research · Liquid AI · Updated for 2026

Which is better?

K-EXAONE-236B-A23B and LFM3-1.7B are closely matched on the overall LLM Stats Score at 25.5 and 25.0.

The models split the 2 individual benchmarks reported for both models evenly.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose K-EXAONE-236B-A23B

  • your work emphasizes reasoning — it leads those capability indexes

Choose LFM3-1.7B

  • you want the most recent training data — it shipped Oct 2026
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

K-EXAONE-236B-A23B
LG AI Research
LFM3-1.7B
Liquid AI
Core performance indexes
LLM Stats Score
25.5
#186
25.0
#191
Reasoning
26.6
#174
20.8
#216
Agents
3.3
#196
18.1
#97
Cost, coverage & limits
Benchmark wins
1 of 2
1 of 2
Input price
$0.60 / M
— / M
Output price
$1.00 / M
— / M
Context window
32,768
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
K-EXAONE-236B-A23B
LFM3-1.7B
Math
28.0#107
7.6#285
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

6 reported for K-EXAONE-236B-A23B · 20 for LFM3-1.7B

2 shared

K-EXAONE-236B-A23B outperforms in 1 benchmarks (LiveCodeBench v6), while LFM3-1.7B is better at 1 benchmark (IFBench).

Both models are evenly matched across the benchmarks.

Fri Nov 06 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

234.3B diff

K-EXAONE-236B-A23B has 234.3B more parameters than LFM3-1.7B, making it 13541.6% larger.

LG AI Research
K-EXAONE-236B-A23B
236.0Bparameters
Liquid AI
LFM3-1.7B
1.7Bparameters
236.0B
K-EXAONE-236B-A23B
1.7B
LFM3-1.7B

Context Window

Maximum input and output token capacity

Only K-EXAONE-236B-A23B specifies input context (32,768 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
Liquid AI
LFM3-1.7B
Input- tokens
Output- tokens
Fri Nov 06 2026 • llm-stats.com

License

Usage and distribution terms

K-EXAONE-236B-A23B is licensed under a proprietary license, while LFM3-1.7B uses LFM Open License v1.0.

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

K-EXAONE-236B-A23B

Proprietary

Closed source

LFM3-1.7B

LFM Open License v1.0

Open weights

Release Timeline

When each model was launched

K-EXAONE-236B-A23B was released on 2025-12-31, while LFM3-1.7B was released on 2026-10-27.

LFM3-1.7B is 10 months newer than K-EXAONE-236B-A23B.

K-EXAONE-236B-A23B

Dec 31, 2025

10 months ago

LFM3-1.7B

Oct 27, 2026

1 weeks ago

10mo newer

Knowledge Cutoff

When training data ends

K-EXAONE-236B-A23B has a documented knowledge cutoff of 2025-10-01, while LFM3-1.7B'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 LFM3-1.7B's cutoff date.

K-EXAONE-236B-A23B

Oct 2025

LFM3-1.7B

—

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against K-EXAONE-236B-A23B and LFM3-1.7B side-by-side, then vote on the output you prefer.

K-EXAONE-236B-A23B
✓ Preferred
LFM3-1.7B
Open in Playground

FAQ

Common questions about K-EXAONE-236B-A23B vs LFM3-1.7B.

Which is better, K-EXAONE-236B-A23B or LFM3-1.7B?

K-EXAONE-236B-A23B and LFM3-1.7B are closely matched on the LLM Stats Score at 25.5 and 25.0. K-EXAONE-236B-A23B is made by LG AI Research and LFM3-1.7B is made by Liquid AI. 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 LFM3-1.7B 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%. LFM3-1.7B scores IFEval: 96.7%, Multi-IF: 89.1%, LiveCodeBench v6: 73.5%, IFBench: 73.0%, BFCL-V4: 71.4%.

What are the context window sizes for K-EXAONE-236B-A23B and LFM3-1.7B?

K-EXAONE-236B-A23B supports 33K tokens and LFM3-1.7B supports an unknown number of 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 LFM3-1.7B?

Key differences include LLM Stats Score (25.5 vs 25.0), licensing (Proprietary vs LFM Open License v1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes K-EXAONE-236B-A23B and LFM3-1.7B?

K-EXAONE-236B-A23B is developed by LG AI Research and LFM3-1.7B is developed by Liquid AI.

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