Compare
DeepSeek-V4-Pro-0813 vs K-EXAONE
DeepSeek-V4-Pro-0813 (DeepSeek) and K-EXAONE (LG AI Research) compared on benchmarks, pricing, context window, and use-case rankings.
- DeepSeek-V4-Pro-0813 ranks higher for coding (78th vs 26th percentile).
| Attribute | DeepSeek-V4-Pro-0813 | K-EXAONE |
|---|---|---|
| Scores | ||
| Intelligence (ECI) | 155 | — |
| Coding | 78 | 26 |
| Math | 88 | 51 |
| Reasoning & Knowledge | 69 | 28 |
| Agentic & Tools | — | 21 |
| Specifications | ||
| Developer | DeepSeek | LG AI Research |
| Family | DeepSeek | — |
| Released | Aug 13, 2026 | Dec 31, 2025 |
| Parameters | 1.6T | 236B |
| Availability | Open weights (unrestricted) | Open weights (restricted use) |
| Context window | 1M | — |
| Price — $/M input | $0.58 | — |
| Price — $/M output | $1.74 | — |
| Inputs | text | — |
| Outputs | text | — |
| Benchmarks | ||
| AIME 2024/2025 | 99% | 90% |
| ARC-AGI | 91% | — |
| ARC-AGI-2 | 61% | — |
| GPQA Diamond | 92% | 78% |
| Humanity's Last Exam | 41% | 14% |
| SciCode | 51% | 36% |
| SimpleQA Verified | 53% | — |
| WebDev Arena | 1582 | — |
| WeirdML | 66% | — |
| LiveCodeBench | — | 77% |
| MMLU-Pro | — | 84% |
| τ²-bench | — | 74% |
Use-case scores are 0–100 percentile composites across each area’s benchmarks, ranked against every model from the past year. Highlighted cells lead each row. Open a model for the full picture.
Frequently asked questions
Which is better for coding, DeepSeek-V4-Pro-0813 or K-EXAONE?
Across coding benchmarks like SWE-bench Verified and Terminal-Bench, DeepSeek-V4-Pro-0813 ranks higher — 78th vs 26th percentile among the models tracked on Model Beat.
Want a different match-up? Open the compare tool to add or swap models.
More comparisons
Benchmarks & model data from Epoch AI (CC BY); pricing & specs from OpenRouter. ECI = Epoch Capabilities Index.