DeepSeek-V4-Flash-0423 vs DeepSeek-V4-Pro-0813: Specs & Benchmark Comparison
| Characteristic | DeepSeek-V4-Flash-0423 | DeepSeek-V4-Pro-0813 |
|---|---|---|
| Company | DeepSeek | DeepSeek |
| Release Date | April 23, 2026 | August 13, 2026 |
| Parameters | 284B | 1.6T |
| Multimodal | No | No |
| Context (input) | 1.0M | 1.0M |
| Context (output) | 131K | 393K |
| Input Price / 1M | $0.14 | $1.32 |
| Output Price / 1M | $0.28 | $3.96 |
| Average Score | 0.9 | 0.8 |
Verdict
Both models show equal results — the choice depends on your specific use case.
Overall Performance
Both models show comparable average scores: DeepSeek-V4-Flash-0423 — 0.9, DeepSeek-V4-Pro-0813 — 0.8.
API Cost
DeepSeek-V4-Flash-0423 is 12.6x cheaper: input $0.14/1M vs $1.32/1M tokens.
Context Window
Same context size: 1M tokens.
Recency
DeepSeek-V4-Pro-0813 is newer: released 8/13/2026 vs 4/23/2026.
More About These Models
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Frequently Asked Questions
Which is better for coding — DeepSeek-V4-Flash-0423 or DeepSeek-V4-Pro-0813?
Direct comparison on the SWE-Bench benchmark is not available. We recommend reviewing other metrics on the comparison page.
Which model is cheaper — DeepSeek-V4-Flash-0423 or DeepSeek-V4-Pro-0813?
DeepSeek-V4-Flash-0423 is cheaper for input: $0.14 per 1M tokens vs $1.32.
Which has a larger context window — DeepSeek-V4-Flash-0423 or DeepSeek-V4-Pro-0813?
DeepSeek-V4-Flash-0423 supports a larger context: 1,000,000 tokens vs 1,000,000.
The DeepSeek-V4-Flash-0423 and DeepSeek-V4-Pro-0813 comparison is updated for 2026. Data includes benchmark results, API pricing, context window size and other specifications. For more detailed information, visit the DeepSeek-V4-Flash-0423 or DeepSeek-V4-Pro-0813 page. See also the complete list of AI model comparisons.