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DeepSeek-V4.1-Flash vs K-EXAONE-236B-A23B

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 26.2. DeepSeek-V4.1-Flash is 2.1x cheaper per token.

DeepSeek · LG AI Research · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 26.2, ranking #12 overall.

On price, DeepSeek-V4.1-Flash is roughly 2.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

DeepSeek-V4.1-Flash also accepts a larger context window (1,040,000 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 DeepSeek-V4.1-Flash

  • overall performance matters — it scores 51.8 and ranks #12 on LLM Stats
  • your work emphasizes reasoning and agents — it leads those capability indexes
  • cost matters — it's about 2.1x cheaper per token
  • you process long inputs — it offers a 1,040,000 token context window
  • you want the most recent training data — it shipped Sep 2026
  • you need open weights you can self-host or fine-tune

Choose K-EXAONE-236B-A23B

  • you want predictable pricing at $0.60/M input and $1.00/M output

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
K-EXAONE-236B-A23B
LG AI Research
Core performance indexes
LLM Stats Score
51.8
#12
26.2
#150
Reasoning
48.9
#17
27.2
#138
Agents
41.3
#4
4.1
#158
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.22 / M
$0.60 / M
Output price
$0.66 / M
$1.00 / M
Context window
1,040,000
32,768

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V4.1-Flash
K-EXAONE-236B-A23B
Math
35.2#43
28.0#96
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 6 for K-EXAONE-236B-A23B

No common benchmarks found

DeepSeek-V4.1-Flash and K-EXAONE-236B-A23Bdon'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

DeepSeek-V4.1-Flash costs less

For input processing, DeepSeek-V4.1-Flash ($0.22/1M tokens) is 2.7x cheaper than K-EXAONE-236B-A23B ($0.60/1M tokens).

For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 1.5x cheaper than K-EXAONE-236B-A23B ($1.00/1M tokens).

In conclusion, K-EXAONE-236B-A23B is more expensive than DeepSeek-V4.1-Flash.*

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

Lowest available price from all providers
Fri Sep 11 2026 • llm-stats.com
DeepSeek
DeepSeek-V4.1-Flash
Input tokens$0.22
Output tokens$0.66
Best providerFireworks
LG AI Research
K-EXAONE-236B-A23B
Input tokens$0.60
Output tokens$1.00
Best providerFriendliAI
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

527.2B diff

DeepSeek-V4.1-Flash has 527.2B more parameters than K-EXAONE-236B-A23B, making it 223.4% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
LG AI Research
K-EXAONE-236B-A23B
236.0Bparameters
763.2B
DeepSeek-V4.1-Flash
236.0B
K-EXAONE-236B-A23B

Context Window

Maximum input and output token capacity

DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to K-EXAONE-236B-A23B's 32,768 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while K-EXAONE-236B-A23B is limited to 32,768 tokens.

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
LG AI Research
K-EXAONE-236B-A23B
Input32,768 tokens
Output32,768 tokens
Fri Sep 11 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash supports multimodal inputs, whereas K-EXAONE-236B-A23B does not.

DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

K-EXAONE-236B-A23B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash is licensed under MIT, while K-EXAONE-236B-A23B uses a proprietary license.

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

DeepSeek-V4.1-Flash

MIT

Open weights

K-EXAONE-236B-A23B

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while K-EXAONE-236B-A23B was released on 2025-12-31.

DeepSeek-V4.1-Flash is 8 months newer than K-EXAONE-236B-A23B.

DeepSeek-V4.1-Flash

Sep 10, 2026

0 days ago

8mo newer
K-EXAONE-236B-A23B

Dec 31, 2025

8 months ago

Knowledge Cutoff

When training data ends

K-EXAONE-236B-A23B has a documented knowledge cutoff of 2025-10-01, while DeepSeek-V4.1-Flash'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 DeepSeek-V4.1-Flash's cutoff date.

DeepSeek-V4.1-Flash

—

K-EXAONE-236B-A23B

Oct 2025

Provider Availability

DeepSeek-V4.1-Flash is available from Fireworks, DeepInfra, DeepSeek, Novita. K-EXAONE-236B-A23B is available from FriendliAI.

DeepSeek-V4.1-Flash

fireworks logo
Fireworks
Input Price:Input: $0.22/1MOutput Price:Output: $0.66/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
deepseek logo
DeepSeek
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M
novita logo
Novita
Input Price:Input: $0.30/1MOutput Price:Output: $1.20/1M

K-EXAONE-236B-A23B

friendli logo
FriendliAI
Input Price:Input: $0.60/1MOutput Price:Output: $1.00/1M
* 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 DeepSeek-V4.1-Flash and K-EXAONE-236B-A23B side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
K-EXAONE-236B-A23B
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs K-EXAONE-236B-A23B.

Which is better, DeepSeek-V4.1-Flash or K-EXAONE-236B-A23B?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 26.2. DeepSeek-V4.1-Flash is made by DeepSeek and K-EXAONE-236B-A23B is made by LG AI Research. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V4.1-Flash compare to K-EXAONE-236B-A23B in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. K-EXAONE-236B-A23B scores AIME 2025: 92.8%, MMMLU: 85.7%, MMLU-Pro: 83.8%, LiveCodeBench v6: 80.7%, t2-bench: 73.2%.

Is DeepSeek-V4.1-Flash cheaper than K-EXAONE-236B-A23B?

DeepSeek-V4.1-Flash is 2.7x cheaper for input tokens. DeepSeek-V4.1-Flash costs $0.22/M input and $0.66/M output via fireworks. K-EXAONE-236B-A23B costs $0.60/M input and $1.00/M output via friendli.

What are the context window sizes for DeepSeek-V4.1-Flash and K-EXAONE-236B-A23B?

DeepSeek-V4.1-Flash supports 1.0M tokens and K-EXAONE-236B-A23B supports 33K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4.1-Flash and K-EXAONE-236B-A23B?

Key differences include LLM Stats Score (51.8 vs 26.2), context window (1.0M vs 33K), input pricing ($0.22 vs $0.60/M), multimodal support (yes vs no), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and K-EXAONE-236B-A23B?

DeepSeek-V4.1-Flash is developed by DeepSeek and K-EXAONE-236B-A23B is developed by LG AI Research.

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