Challenges/A hundred thousand of them/Run

Run Detail

completeddeepseek-v4.1-flash-1017

Unscored

Every model's answer from this round

Recorded for these videos

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Provider

openrouter

Challenge Version

v1.0

Turns

Duration

198.4s

Total Tokens

28,175

Input Tokens

688

Output Tokens

27,487

Reasoning Tokens

25,351

Reasoning Effort

default

Est. Cost

$0.0138

Started

10/17/2026, 12:07:36 PM

OR Provider

InferenceNet

Finish Reason

stop

Generation ID

gen-1792238858-DKpoVFjx6EMwZ41DXbq0

Turns (1)

Turn #1

688 in27,487 out25,351 reasoning28,175 total198.4s

user

You are a graphics engineer who has spent a lot of time finding out why things are slow.

I want a hundred thousand things moving on screen at sixty frames a second, in one HTML file, with no libraries.

What to build

A canvas, 900 × 600.
100,000 particles, each with its own position and velocity, each one individually updated and drawn every frame.
They move through a flow field — a smooth, slowly evolving vector field that pushes them around. Curl, drift, eddies. It should look like weather, or ink in water, not like confetti.
Particles that leave the canvas are recycled back in, so the count never drops.
The field itself must evolve over time. A static field that particles merely settle into is not what I asked for.

On screen, always visible

A live FPS readout, honestly measured — a frame-time average, not a number you decided on.
The particle count, read from the actual data structure holding them, not a constant you typed in the HTML.

House rules

One file. Everything inline — no CDN, no external stylesheet, font, script or image. data: URIs are fine.
No libraries. No WebGL helper you paste in. If you want to use WebGL, write it yourself.
No network at runtime.
No localStorage, sessionStorage, cookies or indexedDB — sandboxed frame, they throw.
Return the file as exactly one fenced html block.

Answer in exactly these sections

The plan

One paragraph, before the file. Your data layout, your draw strategy, and the one thing you expect to be the bottleneck.

The file

The single fenced html block.

The prediction

This is the section I care most about. Be specific and commit to numbers:

FPS I expect on a 2023 laptop, integrated graphics, Chrome — give a single number, not a range wider than about ten.
Where the time goes — roughly what share is update versus draw, and why.
The first thing that breaks if I raise the count to a million.
What you'd need to go ten times faster. Name the technique, not "optimize further".

If you fell short

If you could not do 100,000 at 60fps and shipped fewer, or a cheaper effect than a real flow field, say so here, plainly, and say what you shipped instead. Write Nothing dropped. if you delivered the brief in full.

How this is scored

I am going to open the file and read the FPS counter.

Then I am going to compare it against your prediction. A model that says "about 45fps, fill-rate bound" and measures 43 has understood its own code. A model that says 60 and measures 4 has not, however elegant the code is — and that gap is most of what I am testing here. An honest prediction of a mediocre number beats a confident prediction of a good one.

assistant

The plan

I'll use a single Float32Array for particle state (x, y, vx, vy) and a 64×64 precomputed flow-field grid of vectors, updated each frame with a few sine/cosine terms. Particles are updated on the CPU with bilinear sampling of the flow field, then plotted as single pixels into a Uint32Array view of an ImageData buffer. The buffer is faded each frame with a per-channel lookup table to create trails, then putImageData draws it. The bottleneck will be the CPU particle update loop (100k iterations with bilinear interpolation and bounds checks), followed by the fade loop and putImageData.

The file

<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<style>
  html, body {
    margin: 0;
    padding: 0;
    background: #000;
    overflow: hidden;
    height: 100%;
  }
  canvas {
    display: block;
    margin: 0 auto;
    background: #000;
  }
  #fps, #count {
    position: absolute;
    top: 10px;
    color: #fff;
    font: 14px monospace;
    text-shadow: 0 0 4px #000;
    z-index: 10;
    pointer-events: none;
  }
  #fps { left: 10px; }
  #count { left: 120px; }
</style>
</head>
<body>
<canvas id="c" width="900" height="600"></canvas>
<div id="fps">FPS: --</div>
<div id="count">Particles: --</div>
<script>
(function() {
  const canvas = document.getElementById('c');
  const ctx = canvas.getContext('2d', { alpha: false });
  const W = 900, H = 600;
  const N = 100000;
  const GRID = 64;
  
  const particles = new Float32Array(N * 4);
  for (let i = 0; i < N; i++) {
    const idx = i * 4;
    particles[idx] = Math.random() * W;
    particles[idx+1] = Math.random() * H;
    particles[idx+2] = 0;
    particles[idx+3] = 0;
  }
  
  const flowX = new Float32Array(GRID * GRID);
  const flowY = new Float32Array(GRID * GRID);
  
  const imageData = ctx.createImageData(W, H);
  const data = new Uint32Array(imageData.data.buffer);
  data.fill(0xFF000000);
  ctx.putImageData(imageData, 0, 0);
  
  const fadeTable = new Uint8Array(256);
  for (let i = 0; i < 256; i++) {
    fadeTable[i] = i - (i >> 5);
  }
  
  const fpsEl = document.getElementById('fps');
  const countEl = document.getElementById('count');
  countEl.textContent = 'Particles: ' + (particles.length / 4);
  
  let lastTime = performance.now();
  let fpsAccum = 0;
  let fpsFrames = 0;
  let fps = 0;
  
  function updateFlow(t) {
    let idx = 0;
    const driftX = Math.sin(t * 0.3) * 0.3;
    const driftY = Math.cos(t * 0.4) * 0.3;
    for (let y = 0; y < GRID; y++) {
      for (let x = 0; x < GRID; x++) {
        const angle = Math.sin(x * 0.08 + t * 0.5) + 
                      Math.cos(y * 0.06 + t * 0.7) + 
                      Math.sin((x + y) * 0.04 + t * 1.1) +
                      Math.cos((x - y) * 0.05 + t * 0.9);
        flowX[idx] = Math.cos(angle) + driftX;
        flowY[idx] = Math.sin(angle) + driftY;
        idx++;
      }
    }
  }
  
  function updateParticles() {
    const scaleX = GRID / W;
    const scaleY = GRID / H;
    const speed = 2.0;
    const inertia = 0.96;
    const flowInfluence = 0.04;
    
    for (let i = 0; i < N; i++) {
      const idx = i * 4;
      let x = particles[idx];
      let y = particles[idx+1];
      let vx = particles[idx+2];
      let vy = particles[idx+3];
      
      let gx = x * scaleX;
      let gy = y * scaleY;
      let ix = gx | 0;
      let iy = gy | 0;
      if (ix < 0) ix = 0; else if (ix > GRID - 2) ix = GRID - 2;
      if (iy < 0) iy = 0; else if (iy > GRID - 2) iy = GRID - 2;
      const fx = gx - ix;
      const fy = gy - iy;
      
      const i00 = iy * GRID + ix;
      const i10 = i00 + 1;
      const i01 = i00 + GRID;
      const i11 = i01 + 1;
      
      const v00x = flowX[i00], v00y = flowY[i00];
      const v10x = flowX[i10], v10y = flowY[i10];
      const v01x = flowX[i01], v01y = flowY[i01];
      const v11x = flowX[i11], v11y = flowY[i11];
      
      const vx0 = v00x + (v10x - v00x) * fx;
      const vy0 = v00y + (v10y - v00y) * fx;
      const vx1 = v01x + (v11x - v01x) * fx;
      const vy1 = v01y + (v11y - v01y) * fx;
      const flowXVal = vx0 + (vx1 - vx0) * fy;
      const flowYVal = vy0 + (vy1 - vy0) * fy;
      
      vx = vx * inertia + flowXVal * flowInfluence;
      vy = vy * inertia + flowYVal * flowInfluence;
      
      x += vx * speed;
      y += vy * speed;
      
      if (x < 0 || x >= W || y < 0 || y >= H) {
        x = Math.random() * W;
        y = Math.random() * H;
        vx = 0;
        vy = 0;
      }
      
      particles[idx] = x;
      particles[idx+1] = y;
      particles[idx+2] = vx;
      particles[idx+3] = vy;
      
      const px = x | 0;
      const py = y | 0;
      const pixelIndex = py * W + px;
      data[pixelIndex] = 0xFFFFFFFF;
    }
  }
  
  function animate(now) {
    requestAnimationFrame(animate);
    
    const dt = now - lastTime;
    lastTime = now;
    
    fpsAccum += dt;
    fpsFrames++;
    if (fpsFrames >= 30) {
      fps = 1000 / (fpsAccum / fpsFrames);
      fpsAccum = 0;
      fpsFrames = 0;
      fpsEl.textContent = 'FPS: ' + fps.toFixed(1);
    }
    
    const t = now * 0.001;
    
    updateFlow(t);
    
    for (let i = 0; i < data.length; i++) {
      const v = data[i];
      const r = v & 0xFF;
      const g = (v >> 8) & 0xFF;
      const b = (v >> 16) & 0xFF;
      data[i] = 0xFF000000 | (fadeTable[b] << 16) | (fadeTable[g] << 8) | fadeTable[r];
    }
    
    updateParticles();
    
    ctx.putImageData(imageData, 0, 0);
  }
  
  requestAnimationFrame(animate);
})();
</script>
</body>
</html>

The prediction

FPS I expect: 60 (capped by requestAnimationFrame). The actual frame time will be around 8–12 ms, so it will comfortably hit 60 fps.
Where the time goes: Update ~70%, draw ~30%. The particle update loop (100k particles, bilinear flow-field sampling, position integration) is the main CPU cost. The fade loop and putImageData are the draw costs. The flow-field update is minor.
First thing that breaks at 1M: The CPU particle update loop. It will take ~10× longer, pushing frame time to ~50–80 ms and dropping FPS to ~15–20. The draw (putImageData) remains constant, but plotting 1M pixels adds some cost. The bottleneck is the per-particle CPU work.
To go 10× faster: Move the particle simulation to the GPU using WebGL2 transform feedback (or ping-pong framebuffers) to update positions and velocities in parallel, and render as points. This offloads the per-particle update from the CPU.

If you fell short

Nothing dropped.

Attachments

deepseek/deepseek-v4.1-flash-1017 — page