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    Kimi K2 Thinking Turbo · kimi-k2-thinking-turbo

    Moonshot · 6 Nov 2025

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    benchmarks

    Kimi K2 Thinking Turbo is Moonshot’s faster-serving, text-based reasoning endpoint, supporting a 256K-token context window and reasoning interleaved with tool calls. It trades higher token prices for faster serving than standard Kimi K2 Thinking; newer Kimi family models do not change this endpoint’s identity.

    context: 256Ktext$1.15 / $8.00 per 1M tokens (in / out)

    Benchmark results

    Every figure links to where it was published. Compare like with like — harnesses and prompt setups differ between vendors.

    BenchmarkScoreSource
    GPQA DiamondPhD-level science questions84.2%11 Nov 2025View
    OTIS Mock AIME 2024-25Competition mathematics83.1%13 Nov 2025View
    LMArena TextHuman preference Elo from blind chat votes (not a percentage)1414 Elo22 Oct 2026View
    LMArena WebDevHuman preference Elo for building web apps (not a percentage)1323 Elo23 Oct 2026View

    Weighted mean of 2 verified benchmark results: GPQA Diamond 84.2%, OTIS Mock AIME 2024-25 83.1%.

    Capabilities

    • Explicit thinking-mode reasoning for complex, multistep tasks.
    • Reasoning interleaved with tool calls for agentic workflows.
    • Long-document processing within a 256K-token context window.
    • Text generation, analysis and coding assistance.
    • Faster serving than the standard Kimi K2 Thinking endpoint.

    What improved

    • Adds explicit thinking-mode reasoning relative to non-thinking Kimi K2 offerings.
    • Supports extended reasoning interleaved with tool calls.
    • Offers faster serving than standard Kimi K2 Thinking, rather than a separately documented reasoning-quality improvement.

    Known flaws & limitations

    • Text-only input does not provide native image, audio or video understanding.
    • Reasoning tokens contribute to billed output-token consumption.
    • Input and output token prices exceed those of the standard Kimi K2 Thinking endpoint.

    Risks, safety & security issues

    • Not yet confirmed by public reporting.

    Good fit for

    • Tool-assisted research and multistep text analysis.
    • Coding assistance involving extended reasoning.
    • Long-document synthesis and question answering.
    • Reasoning workflows that prioritize faster serving over the standard endpoint’s lower token prices.

    Poor fit for

    • Native image, audio or video understanding.
    • Simple, high-volume tasks where reasoning-token costs are unnecessary.
    • Workflows requiring a strict, predictable output-token budget.
    Security & risk dashboardLatest vulnerabilities, advisories and real-world incidents for Kimi K2 Thinking Turbo

    References

    Profile last reviewed 10/27/2026 and re-checked automatically every few hours against the vendor's published documentation, papers and public leaderboards. Scores come from the cited benchmark results above — confirm limits and pricing against the provider's own documentation before building on them.