DeepSeek-V4-Flash-0731 vs Kimi K3

    Comparison

    As of August 20, 2026, DeepSeek-V4-Flash-0731 is 90% cheaper per million tokens than Kimi K3. DeepSeek-V4-Flash-0731 is $0.44 / $1.32 per million input/output tokens versus Kimi K3 at $3.00 / $15.00. Sources: https://api-docs.deepseek.com/quick_start/pricing and https://platform.kimi.com/docs/pricing/chat

    Sources: DeepSeek API pricing (https://api-docs.deepseek.com/quick_start/pricing); Moonshot AI pricing (https://platform.kimi.com/docs/pricing/chat)

    Better value

    DeepSeek-V4-Flash-0731

    DeepSeek

    $1.76blended / 1M

    Input

    $0.44

    Output

    $1.32

    1M ctx|Open Source
    90%
    cheaper

    Kimi K3

    Moonshot AI

    $18.00blended / 1M

    Input

    $3.00

    Output

    $15.00

    1M ctx|Open Source
    Save $16.24 per million tokens by choosing DeepSeek-V4-Flash-0731 over Kimi K3.

    DeepSeek-V4-Flash-0731 vs Kimi K3 comparison

    Token pricing, specs, and benchmarks side by side

    Metric
    DeepSeek-V4-Flash-0731
    Kimi K3
    Provider
    Provider
    DeepSeek
    Moonshot AI
    License
    Open Source
    Open Source
    Release Date
    2026-07-31
    2026-07-16
    Pricing (per 1M tokens)
    Input Price-85%
    $0.44
    $3.00
    Output Price-91%
    $1.32
    $15.00
    Blended (1M + 1M)
    $1.76
    $18.00
    Model Details
    Context Window
    1M
    1M
    Max Output Tokens
    65.5K
    1M
    Knowledge Cutoff
    N/A
    N/A
    Throughput
    5.860066709299238 tok/s
    8.253358168863906 tok/s
    Benchmarks
    56%
    93.5%
    91.0%
    93.5%
    54.4%
    67.5%
    53.3%
    68.5%
    87.3%
    87.2%
    49.9%
    58.7%
    1681.75
    74.7%
    85.0%
    91.2%
    34.7%
    42.7%
    49.5%
    54.4%
    61.4%
    60.4%
    84.8%
    70.3%
    76.5%
    84.2%
    81.6%
    91.3%
    94.4%
    68.9%
    88.2%
    51.6%
    37.6%
    25.1%
    30.8%
    85.7%
    84.8%
    38.6%
    16.1%
    61.9%
    71.6%
    16.6%
    23.4%
    77.5%
    79.0%
    76.7%
    73.5%
    Deck Bench Internal
    73.5%
    67.5%
    59.6%
    57.0%
    66.4%
    81.2%
    44.2%
    81.2%
    19%
    43.5%
    52.9%
    Kimi Code Bench 2 0 Internal
    72.9%
    97.8%
    41.4%
    48.9%
    80.4%
    88.0%
    86.2%
    88.0%
    54.2%
    63.3%
    91.1%
    Perceptionbench Internal
    58.5%
    54.3%
    50.7%
    70.7%
    75.7%
    51%
    41%
    Benchmark Wins
    DeepSeek-V4-Flash-0731 4|21 Kimi K3

    Verdict

    DeepSeek-V4-Flash-0731 vs Kimi K3: the bottom line

    DeepSeek-V4-Flash-0731 offers significantly lower pricing, while Kimi K3 leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.

    DeepSeek-V4-Flash-0731 vs Kimi K3 FAQ

    Which is cheaper, DeepSeek-V4-Flash-0731 or Kimi K3?

    As of August 20, 2026, DeepSeek-V4-Flash-0731 is 90% cheaper on blended LLM API pricing. DeepSeek-V4-Flash-0731 costs $0.44 per million input tokens and $1.32 per million output tokens ($1.76 blended 1M-in + 1M-out). Kimi K3 costs $3.00 / $15.00 per million tokens ($18.00 blended). Sources: https://api-docs.deepseek.com/quick_start/pricing and https://platform.kimi.com/docs/pricing/chat. The cheapest LLM for your app still depends on how many output tokens you generate.

    How much does DeepSeek-V4-Flash-0731 vs Kimi K3 cost per million tokens?

    DeepSeek-V4-Flash-0731 DeepSeek API pricing is $0.44 input and $1.32 output per million tokens via DeepSeek. Kimi K3 Moonshot AI API pricing is $3.00 input and $15.00 output per million tokens via Moonshot AI. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.

    Which is better for coding, DeepSeek-V4-Flash-0731 or Kimi K3?

    Kimi K3 leads on SWE-bench Verified: DeepSeek-V4-Flash-0731 at 88.8% vs Kimi K3 at 93.4%. SWE-bench measures real GitHub fixes; LiveCodeBench measures contest programming.

    What is the context window for DeepSeek-V4-Flash-0731 vs Kimi K3?

    DeepSeek-V4-Flash-0731 supports a 1M token context window, while Kimi K3 supports 1M tokens. Both models have the same context window size. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.

    Which model performs better on benchmarks, DeepSeek-V4-Flash-0731 or Kimi K3?

    Kimi K3 leads on 21 of 25 shared benchmarks versus DeepSeek-V4-Flash-0731's 4 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.

    Is DeepSeek-V4-Flash-0731 or Kimi K3 better for production use?

    Both DeepSeek-V4-Flash-0731 and Kimi K3 are production API models. For cost-sensitive production traffic, DeepSeek-V4-Flash-0731 has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.

    Can I switch between DeepSeek-V4-Flash-0731 and Kimi K3 in my app?

    Yes. Call DeepSeek-V4-Flash-0731 through DeepSeek and Kimi K3 through Moonshot AI with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.

    How accurate is this DeepSeek-V4-Flash-0731 vs Kimi K3 pricing data?

    List rates are the latest published DeepSeek API pricing and Moonshot AI API pricing, quoted per million tokens. Official rate sheets: https://api-docs.deepseek.com/quick_start/pricing and https://platform.kimi.com/docs/pricing/chat. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.

    What is the output token limit for DeepSeek-V4-Flash-0731 and Kimi K3?

    DeepSeek-V4-Flash-0731 supports up to 66K output tokens per request, while Kimi K3 supports up to 1M output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.

    Which model has better throughput, DeepSeek-V4-Flash-0731 or Kimi K3?

    DeepSeek-V4-Flash-0731 runs at approximately 5.860066709299238 tokens/second while Kimi K3 runs at 8.253358168863906 tokens/second. Kimi K3 is faster in raw throughput. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.

    How do I switch the models in this DeepSeek-V4-Flash-0731 vs Kimi K3 comparison?

    Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open DeepSeek-V4-Flash-0731 or Kimi K3 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

    DeepSeek-V4-Flash-0731 vs Kimi K3 pricing

    This comparison covers API pricing, context window, throughput, and benchmark scores. DeepSeek-V4-Flash-0731 costs $0.44/M input and $1.32/M output. Kimi K3 costs $3.00/M input and $15.00/M output.

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

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