Hostinger — Moonshot's Kimi K3.1 Pro lands at 65.7 on Terminal-Bench 4.0, again... (Launch Video Storyboard & Reverse-Engineering Breakdown)

About Hostinger & This Product Release

Hostinger — Moonshot's Kimi K3.1 Pro lands at 65.7 on Terminal-Bench 4.0, against Claude Opus 5.5 at 66.4 and GPT-6 Astra at 58.2. Those are Moonshot's own runs, using the Claude Code harness. 2.8T parameters, 1M context. Open weights by 4 November, which is when anyone can check. Watch the full 60s Hostinger launch video with shot-by-shot breakdown and Remotion code.

Official X Account: @Hostinger | Original X Launch Post →

Explore Hostinger Company Profile & Video Archive (/company/hostinger) | Visit Official Hostinger Website (Hostinger) →

Editorial Structure & Storyboard Timeline (60s Total Runtime · Fast (2.2s avg shot))

  • 01 · THE HOOK (00:00 – 00:08 · 13%): Prompt-to-Execution Split Reveal for Hostinger — Opens immediately on the high-contrast tension point before showing the brand logo, locking viewer retention in the first 8 seconds. (Camera: 1.6x macro push-in with 0ms dead air on frame 1)
  • 02 · HERO UI REVEAL (00:08 – 00:26 · 30%): Core Hostinger Surface & Interaction Loop — Demonstrates the primary action in a single continuous take (18s) with cursor smoothing and highlighted focal bounds. (Camera: Isometric-to-flat spring settle (cubic-bezier 0.22, 1, 0.36, 1))
  • 03 · VELOCITY MONTAGE (00:26 – 00:47 · 35%): Multi-State Feature Proof on Downbeat Cuts — Compresses 3–4 secondary workflows into rapid visual proof without narration drag. (Camera: Fast (2.2s avg shot) matched to 122 BPM transients)
  • 04 · PAYOFF & LOCKUP (00:47 – 01:00 · 22%): Hostinger Brand Lockup & Availability CTA — Holds final URL and launch status cleanly for 13s so viewers on X stop scrolling and click the link. (Camera: Clean center lockup with subtle radial luminance decay)

Release Context & Production Format

Published by Hostinger (@Hostinger) on 2026-11-01 in the ai category (60s total runtime).

Hostinger — Moonshot's Kimi K3.1 Pro lands at 65.7 on Terminal-Bench 4.0, against Claude Opus 5.5 at 66.4 and GPT-6 Astra at 58.2: What Shipped, Key Capabilities & Use Cases

Moonshot's Kimi K3.1 Pro lands at 65.7 on Terminal-Bench 4.0, against Claude Opus 5.5 at 66.4 and GPT-6 Astra at 58.2. Here is a clear breakdown of what Hostinger released, how it works, and where it fits in real-world workflows.

Hostinger announced Moonshot's Kimi K3.1 Pro lands at 65.7 on Terminal-Bench 4.0, against Claude Opus 5.5 at 66.4 and GPT-6 Astra at 58.2. Moonshot's Kimi K3.1 Pro lands at 65.7 on Terminal-Bench 4.0, against Claude Opus 5.5 at 66.4 and GPT-6 Astra at 58.2. Those are Moonshot's own runs, using the Claude Code harness. 2.8T parameters, 1M context. Open weights by 4 November, which is when anyone can check.

Hostinger is a mcp servers, cloud & dev infra company. Something big just landed for devs A new way to deploy Node.js apps is here — built for speed and serious security. 1-click deploy from GitHub Fully managed servers & security $3.99/mo flat. No usa… With this release, Hostinger focuses on practical workflow utility.

Core Feature & Architecture Breakdown

  • [WHAT SHIPPED] Moonshot's Kimi K3.1 Pro lands at 65.7 on Terminal-Bench 4.0, against Claude Opus 5.5 at 66.4 and GPT-6 Astra at 58.2: Moonshot's Kimi K3.1 Pro lands at 65.7 on Terminal-Bench 4.0, against Claude Opus 5.5 at 66.4 and GPT-6 Astra at 58.2. Those are Moonshot's own runs, using the Claude Code harness. 2.8T parameters, 1M context. Open weights by 4 November, which is when anyone can check.
  • [PLATFORM CAPABILITIES] Core Hostinger Stack & Workflow Features: Hostinger combines this release with its core platform capabilities: Hostinger Node.js app deployment — Something big just… (22s launch film · 0s UI Cold Open).

Real-World Use Cases & Team Workflows

  • ML Systems & GPU Infrastructure Engineers (Optimizing training throughput and inference efficiency with Hostinger): Reduces GPU cluster hours and memory bandwidth bottlenecks across large-scale model runs.
  • Applied AI Research Teams (Fine-tuning and post-training open-weight checkpoints): Accelerates iteration cycles on custom domain models and reinforcement learning pipelines.

Related Technologies, Protocols & Ecosystem Stack

30fps Remotion React Code Specification

import { AbsoluteFill, Sequence, useCurrentFrame, useVideoConfig } from "remotion";

// Hostinger — Hostinger — Moonshot's Kimi K3.1 Pro lands at 65.7 on Terminal-Bench 4.0, again... (60s @ 30fps)
export const HostingerComposition = () => {
  const frame = useCurrentFrame();
  const { fps } = useVideoConfig();

  return (
    <AbsoluteFill style={{ backgroundColor: "#141413" }}>
      <Sequence from={0} durationInFrames={240} name="Act01_hook">
        {/* 00:00 – 00:08: Prompt-to-Execution Split Reveal for Hostinger */}
      </Sequence>
      <Sequence from={240} durationInFrames={540} name="Act02_reveal">
        {/* 00:08 – 00:26: Core Hostinger Surface & Interaction Loop */}
      </Sequence>
      <Sequence from={780} durationInFrames={630} name="Act03_velocity">
        {/* 00:26 – 00:47: Multi-State Feature Proof on Downbeat Cuts */}
      </Sequence>
      <Sequence from={1410} durationInFrames={390} name="Act04_payoff">
        {/* 00:47 – 01:00: Hostinger Brand Lockup & Availability CTA */}
      </Sequence>
    </AbsoluteFill>
  );
};