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DeepSeekDeepSeek V4 ProVSMoonshot AI (Kimi)Kimi K2.7 Code

Analysis by:the whichllmmodel Editorial Team|Updated: June 2026

Our Take

We recommend Kimi K2.7 Code for practical local execution on standard developer hardware, or DeepSeek V4 Pro if you need peak reasoning and have the VRAM (or a cloud API) to host it. While DeepSeek V4 Pro offers frontier capability, its massive parameter size makes it extremely difficult to host locally. Choose Kimi K2.7 Code for standard local setups, or DeepSeek V4 Pro for peak reasoning.
▶WHY?
Benchmark Calculations & Evidence:
  • Model Size: DeepSeek V4 Pro is a massive 1600B parameter model requiring heavy GPU infrastructure, while Kimi K2.7 Code is a 1000B parameter model.
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    Model Specs

    DeepSeek V4 Pro

    Open SourceAPI Available
    Website🤗HF

    Benchmarks & Scores

    Coding (swe-bench-pro)
    52.1%

    complex codebases, multi-file repositories, and architectural planning

    Reasoning (gpqa-diamond)
    88%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)
    $2.17Input: $1.74 | Output: $3.48
    Context WindowLarger
    1.05M tokens
    Model Specs

    Kimi K2.7 Code

    Open SourceAPI Available
    Website🤗HF

    Benchmarks & Scores

    Coding (swe-bench-pro)Winner (+6.5%)
    58.6%

    complex codebases, multi-file repositories, and architectural planning

    Reasoning (gpqa-diamond)Winner (+2.0%)
    90%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)1.3x cheaper
    $1.71Input: $0.95 | Output: $4.00
    Context Window
    262.14k tokens
    Read our data collection methodology

    Frequently Asked Questions about DeepSeek V4 Pro vs Kimi K2.7 Code

    Kimi K2.7 Code is cheaper than DeepSeek V4 Pro. Kimi K2.7 Code has a blended cost of $1.71/1M tokens, which is about 1.3x cheaper than DeepSeek V4 Pro at $2.17/1M tokens.

    Kimi K2.7 Code is better for coding tasks on this benchmark. It scores 58.6% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning) compared to DeepSeek V4 Pro which scores 52.1%.

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