DeepSeek-V4-Flash-0423 Pricing

    OSS

    As of August 20, 2026, DeepSeek-V4-Flash-0423 API pricing is $0.10 per million input tokens and $0.20 per million output tokens. A typical 100K-in / 20K-out request costs $0.01. Source: https://api-docs.deepseek.com/quick_start/pricing

    Source: DeepSeek API pricing (https://api-docs.deepseek.com/quick_start/pricing)

    Updated August 20, 20261M context$0.30 blended / 1M

    Input $/M

    $0.10

    Output $/M

    $0.20

    Blended / 1M

    $0.30

    100K / 20K request

    $0.01

    DeepSeek-V4-Flash-0423 specs

    Context Window1M
    Max Output65.5K tokens
    Release Date2026-04-23
    Knowledge CutoffN/A
    LicenseOpen Source
    ThroughputN/A

    DeepSeek-V4-Flash-0423 benchmarks

    HLE40.3%
    GPQA87.4%
    SWE-bench Verified78.6%
    LiveCodeBench88.4%
    BrowseComp53.5%
    SimpleQA28.9%
    SWE-bench Multilingual70.2%
    Terminal-Bench 2.056.6%
    ToolAthlon43.5%
    MCP Atlas67.4%
    Codeforces93.9%
    Corpusqa 1m59.3%
    Csimpleqa73.2%
    Hmmt Feb 2691.9%
    Imo Answerbench85.1%
    Matharena Apex72.1%
    MMLU-Pro86.4%
    Mrcr 1m76.9%
    SWE-bench Pro52.3%
    Terminal-Bench 256.6%

    Compare DeepSeek-V4-Flash-0423

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    DeepSeek-V4-Flash-0423 FAQ

    How much does DeepSeek-V4-Flash-0423 cost per million tokens?

    As of August 20, 2026, DeepSeek-V4-Flash-0423 DeepSeek API pricing is $0.10 per million input tokens and $0.20 per million output tokens. Input tokens are the prompt you send; output tokens are the completion. Long answers therefore cost more than short ones even when the prompt stays the same. Source: https://api-docs.deepseek.com/quick_start/pricing

    What is the blended API cost for DeepSeek-V4-Flash-0423?

    On this page the blended DeepSeek-V4-Flash-0423 API cost is $0.30 for 1 million input tokens plus 1 million output tokens. That 1:1 mix is the comparison scale used across the LLM pricing table. A 3:1 mix (three million input tokens per one million output tokens), which some calculators use, would be about $0.50.

    How much does a typical DeepSeek-V4-Flash-0423 request cost?

    A typical DeepSeek-V4-Flash-0423 API request with 100K input tokens and 20K output tokens costs about $0.01 at current rates as of August 20, 2026. Multiply that by daily or monthly volume to estimate spend. Caching, batch APIs, and volume discounts from DeepSeek can bring the real invoice lower than the public list rate at https://api-docs.deepseek.com/quick_start/pricing.

    What is the context window for DeepSeek-V4-Flash-0423?

    DeepSeek-V4-Flash-0423 supports a 1M token context window and can generate up to 66K output tokens per request. The context window is the total prompt plus conversation history the model can see in one call. Larger windows cost more when you fill them, because every input token is billed per million tokens.

    Is DeepSeek-V4-Flash-0423 open source?

    Yes. DeepSeek-V4-Flash-0423 is an open-weight model by DeepSeek. You can download the weights and self-host, or pay DeepSeek's hosted API and skip GPU ops. Hosted API pricing on this page is the public per-million-token rate, not the electricity cost of running the weights yourself.

    What benchmarks does DeepSeek-V4-Flash-0423 perform well on?

    DeepSeek-V4-Flash-0423 currently reports HLE 40.3%, GPQA 87.4%, SWE-bench Verified 78.6%. See the performance table for the full eval set. Use those scores with the token prices above when you are choosing between a cheaper LLM and a frontier model. GPQA, SWE-bench, and HLE are the evals people usually compare first.

    Is DeepSeek-V4-Flash-0423 good for coding?

    DeepSeek-V4-Flash-0423 scores 78.6% on SWE-bench Verified. Pair that score with DeepSeek API pricing on this page: a slightly worse SWE-bench model can still win if it is much cheaper per million tokens. Open the SWE-bench or coding leaderboard from the sidebar for the full ranking, then jump into an LLM comparison against a coding specialist.

    How do I compare DeepSeek-V4-Flash-0423 with another LLM?

    Use the Compare picker on this page to start an LLM comparison. Search by model or provider, pick a second model, and AnotherWrapper opens a dedicated DeepSeek-V4-Flash-0423 vs page with per-million-token prices, blended 1M-in / 1M-out cost, context window, throughput, and benchmarks. You can also open any model from the sidebar, or go back to the LLM pricing table to sort the full index.

    What are the cheapest alternatives to DeepSeek-V4-Flash-0423?

    The cheapest LLM alternative depends on whether you optimize for blended token cost, coding evals, or context window. Start with the popular matchups on this page, then sort the LLM pricing table by blended cost to see which hosted APIs undercut DeepSeek-V4-Flash-0423. Open-weight models can be cheaper still if you self-host, but that is not the same as DeepSeek API pricing on this page.

    How do I use DeepSeek-V4-Flash-0423 in my application?

    DeepSeek-V4-Flash-0423 is called through DeepSeek's API with an API key. Bill against input and output tokens separately; cache or shorten prompts if spend is high. If you are shipping a full product, AnotherWrapper includes pre-built API routes and templates for DeepSeek and 5+ other providers with auth, payments, and deployment already configured.

    How accurate is this DeepSeek-V4-Flash-0423 pricing data?

    This DeepSeek-V4-Flash-0423 page tracks the latest published DeepSeek API pricing from DeepSeek, quoted per million tokens. List rates can differ from invoices because of prompt caching, batch discounts, committed-use tiers, and private contracts. Official rate sheet: https://api-docs.deepseek.com/quick_start/pricing. Benchmark scores come from official publications and independent evals, not from a private lab run by AnotherWrapper.

    About DeepSeek-V4-Flash-0423 API pricing

    DeepSeek-V4-Flash-0423 is a open-source model from DeepSeek. Current API pricing is $0.10 per million input tokens and $0.20 per million output tokens, with a 1M token context window. A blended 1M-in / 1M-out workload costs $0.30.

    Rank it on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.

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