DeepSeek-V4-Flash-0423 vs DeepSeek-V4-Pro-0813
DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks. DeepSeek-V4-Flash-0423 is 4.3x cheaper per token.
DeepSeek · DeepSeek · Updated for 2026
Which is better?
DeepSeek-V4-Flash-0423 outperforms in 0 benchmarks, while DeepSeek-V4-Pro-0813 is better at 2 benchmarks (Humanity's Last Exam, Toolathlon). DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks.
On price, DeepSeek-V4-Flash-0423 is roughly 4.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Flash-0423
- cost matters — it's about 4.3x cheaper per token
Choose DeepSeek-V4-Pro-0813
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-0423 outperforms in 0 benchmarks, while DeepSeek-V4-Pro-0813 is better at 2 benchmarks (Humanity's Last Exam, Toolathlon).
DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0423 ($0.10/1M tokens) is 4.3x cheaper than DeepSeek-V4-Pro-0813 ($0.43/1M tokens).
For output processing, DeepSeek-V4-Flash-0423 ($0.20/1M tokens) is 4.3x cheaper than DeepSeek-V4-Pro-0813 ($0.87/1M tokens).
In conclusion, DeepSeek-V4-Pro-0813 is more expensive than DeepSeek-V4-Flash-0423.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Pro-0813 has 1316.0B more parameters than DeepSeek-V4-Flash-0423, making it 463.4% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. DeepSeek-V4-Pro-0813 can generate longer responses up to 393,216 tokens, while DeepSeek-V4-Flash-0423 is limited to 65,536 tokens.
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Flash-0423 was released on 2026-04-23, while DeepSeek-V4-Pro-0813 was released on 2026-08-13.
DeepSeek-V4-Pro-0813 is 4 months newer than DeepSeek-V4-Flash-0423.
Apr 23, 2026
4 months ago
Aug 13, 2026
1 weeks ago
3mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Flash-0423 is available from DeepInfra, Novita. DeepSeek-V4-Pro-0813 is available from DeepSeek, DeepInfra, Novita, Together.
DeepSeek-V4-Flash-0423
DeepSeek-V4-Pro-0813
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0423 and DeepSeek-V4-Pro-0813 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-0423 vs DeepSeek-V4-Pro-0813.