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DeepSeek · DeepSeek
DeepSeek V4 Flash 0423.
DeepSeek V4 Flash 0423 is a DeepSeek model, listed on 31 July 2026. It takes text and returns text, with a 1.05 million-token context window.
- Open weights
- 1.05M context
Specification
- Provider
- DeepSeek
- Family
- DeepSeek
- Listed
- 31 July 2026
- Catalogue id
- deepseek/deepseek-v4-flash
- Context window
- 1.05 million tokens
- Maximum output
- 943,717 tokens
- Inputs and output
- Text in; text out
- Capabilities
- Tool calling, structured outputs and adjustable reasoning
- Weights
- Published: deepseek-ai/DeepSeek-V4-Flash
- Listed price
- $0.091 input, $0.182 output, $0.018 cached input per million tokens
Provider-published specifications as of 30 October 2026, not figures we measured. Model families move quickly — check the provider's own documentation before committing to a number.
Source: DeepSeek V4 Flash 0423 in the OpenRouter catalogue, checked weekly. Confirm current terms in DeepSeek's own documentation before you commit.
What it costs
Price the whole answer.
Illustrative calculation at listed rates: a batch of 10 million input tokens and 1 million output tokens costs $1.09 on DeepSeek V4 Flash 0423. A thousand requests of 2,000 input and 500 output tokens each costs $0.273. Calculation: input millions × input rate + output millions × output rate; it excludes reasoning tokens, retries, tools, tax and review time.
Compare cost per accepted result, not per token: replay the same work on two or three candidates and count the answers you would actually ship. Our model-routing approach sends each request to the cheapest model that passes.
THE REST OF THE FAMILY
Other DeepSeek models.
Every DeepSeek model in the catalogue. Our DeepSeek page covers where the family fits and how we evaluate it.
| DeepSeek V4 Flash 0423 open | 31 Jul 2026 | — | — | 1.05M | $0.091 | $0.182 |
|---|---|---|---|---|---|---|
| DeepSeek V4.1 Flash 1017 open | 17 Oct 2026 | 32.5 | 159 | 1.05M | $0.150 | $0.600 |
| DeepSeek V4.1 Flash open | 10 Sep 2026 | — | — | 1.05M | $0.045 | $0.500 |
| DeepSeek V4 Pro 0813 open | 13 Aug 2026 | 23.1 | 77 | 1.05M | $0.660 | $1.98 |
| DeepSeek V4 Flash 0731 open | 31 Jul 2026 | — | — | 1.05M | $0.119 | $0.238 |
| DeepSeek V4 Pro 0423 open | 13 Aug 2026 | 23.1 | 77 | 1.05M | $0.948 | $1.90 |
| DeepSeek V3.2 open | 1 Dec 2025 | — | — | 164k | $0.260 | $0.380 |
| DeepSeek V3.1 Terminus open | 22 Sep 2025 | — | — | 164k | $0.270 | $1.00 |
| DeepSeek V3.1 open | 21 Aug 2025 | — | — | 164k | $0.250 | $0.950 |
| R1 0528 open | 28 May 2025 | — | — | 164k | $0.500 | $2.15 |
| DeepSeek V3 0324 open | 25 Mar 2025 | — | — | 164k | $0.290 | $1.14 |
| DeepSeek V3 open | 26 Dec 2024 | — | — | 164k | $0.257 | $1.03 |
Intelligence and coding: Artificial Analysis indices at the model's best reasoning setting, and its measured output speed. Context and prices: the OpenRouter catalogue list price in USD per million tokens. Released: the provider's date where Artificial Analysis records one, otherwise the date the catalogue first listed it. Refreshed weekly; not measured by QQuantum.ai. Select a heading to sort.
Questions
Questions about DeepSeek V4 Flash 0423.
When was DeepSeek V4 Flash 0423 listed?
DeepSeek V4 Flash 0423 was listed on 31 July 2026 in the OpenRouter catalogue; the provider's own announcement may predate it.
What is the context window of DeepSeek V4 Flash 0423?
1.05 million tokens, with up to 943,717 output tokens per response, as listed in the OpenRouter catalogue on 30 October 2026. A long window is not the same as reliable recall across it; evaluate retrieval on your own documents.
How much does DeepSeek V4 Flash 0423 cost?
The catalogue lists $0.091 per million input tokens and $0.182 per million output tokens, and $0.018 per million cached input tokens (checked 30 October 2026). DeepSeek's own rates, batch discounts and cloud marketplaces can differ.
Can DeepSeek V4 Flash 0423 run on our own hardware?
Its weights are published (on Hugging Face as deepseek-ai/DeepSeek-V4-Flash), so it can be self-hosted subject to its licence. Check the licence and size the serving stack before buying hardware.
