ID

ideogram-performance-tuning

Strategies for reducing latency and costs when using the Ideogram API, covering caching and model throughput optimization.

Install

mkdir -p .claude/skills/ideogram-performance-tuning && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/5342" && unzip -o skill.zip -d .claude/skills/ideogram-performance-tuning && rm skill.zip

Installs to .claude/skills/ideogram-performance-tuning

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Optimize Ideogram API performance with caching, model selection, and
68 charsno explicit “when” trigger
Intermediate

Key capabilities

  • Select Ideogram model and rendering speed based on use case
  • Implement a prompt-based cache layer to prevent duplicate image generations
  • Manage parallel image generation with concurrency limits
  • Upload generated images to a CDN for faster delivery
  • Optimize image generation for speed, cost, and throughput
  • Download generated image URLs immediately to prevent expiration

How it works

The skill optimizes Ideogram image generation by selecting appropriate model speeds, caching results based on prompt hashes, controlling parallel generation concurrency, and uploading images to a CDN.

Inputs & outputs

You give it
Ideogram API key, prompts, desired image styles and aspect ratios
You get back
Optimized image generation, cached images, CDN-hosted images, speed-tiered configurations

When to use ideogram-performance-tuning

  • Optimizing latency for production image generation
  • Implementing caching layers to reduce redundant costs
  • Selecting appropriate model speed tiers
  • Managing concurrency for high-throughput image requests

About this skill

Ideogram Performance Tuning

Overview

Optimize Ideogram image generation for speed, cost, and throughput. Key levers: model and rendering speed selection, prompt-based caching, parallel generation with concurrency limits, and CDN delivery of generated assets.

Performance Baselines

Model / SpeedTypical LatencyRelative CostQuality
V_2_TURBO3-6s~$0.05/imageGood
V_28-15s~$0.08/imageHigh
V3 FLASH2-4sLowestDraft
V3 TURBO4-8sLowGood
V3 DEFAULT8-15sStandardHigh
V3 QUALITY15-25sPremiumHighest

Instructions

Step 1: Speed Tiers by Use Case

const SPEED_CONFIGS = {
  // Preview / draft mode -- fastest, cheapest
  preview: {
    endpoint: "https://api.ideogram.ai/generate",
    model: "V_2_TURBO",
    note: "3-6s, good enough for iteration",
  },
  // Standard production -- balanced
  standard: {
    endpoint: "https://api.ideogram.ai/generate",
    model: "V_2",
    note: "8-15s, high quality for final assets",
  },
  // V3 with speed control
  v3_fast: {
    endpoint: "https://api.ideogram.ai/v1/ideogram-v3/generate",
    rendering_speed: "TURBO",
    note: "4-8s, V3 quality at faster speed",
  },
  v3_quality: {
    endpoint: "https://api.ideogram.ai/v1/ideogram-v3/generate",
    rendering_speed: "QUALITY",
    note: "15-25s, maximum quality",
  },
} as const;

function getConfig(tier: keyof typeof SPEED_CONFIGS) {
  return SPEED_CONFIGS[tier];
}

Step 2: Prompt-Based Cache Layer

import { createHash } from "crypto";
import { existsSync, readFileSync, writeFileSync, mkdirSync } from "fs";
import { join } from "path";

const CACHE_DIR = "./ideogram-cache";

function cacheKey(prompt: string, style: string, aspect: string): string {
  return createHash("sha256")
    .update(`${prompt.toLowerCase().trim()}:${style}:${aspect}`)
    .digest("hex")
    .slice(0, 16);
}

async function cachedGenerate(
  prompt: string,
  options: { style_type?: string; aspect_ratio?: string; model?: string } = {}
) {
  const style = options.style_type ?? "AUTO";
  const aspect = options.aspect_ratio ?? "ASPECT_1_1";
  const key = cacheKey(prompt, style, aspect);
  const metaPath = join(CACHE_DIR, `${key}.json`);
  const imgPath = join(CACHE_DIR, `${key}.png`);

  // Return cached if exists
  if (existsSync(metaPath) && existsSync(imgPath)) {
    console.log(`Cache hit: ${key}`);
    return JSON.parse(readFileSync(metaPath, "utf-8"));
  }

  // Generate and cache
  const response = await fetch("https://api.ideogram.ai/generate", {
    method: "POST",
    headers: {
      "Api-Key": process.env.IDEOGRAM_API_KEY!,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      image_request: {
        prompt,
        model: options.model ?? "V_2",
        style_type: style,
        aspect_ratio: aspect,
        magic_prompt_option: "AUTO",
      },
    }),
  });

  if (!response.ok) throw new Error(`Generate failed: ${response.status}`);
  const result = await response.json();
  const image = result.data[0];

  // Download and cache
  const imgResp = await fetch(image.url);
  const buffer = Buffer.from(await imgResp.arrayBuffer());

  mkdirSync(CACHE_DIR, { recursive: true });
  writeFileSync(imgPath, buffer);
  writeFileSync(metaPath, JSON.stringify({
    ...image,
    localPath: imgPath,
    cachedAt: new Date().toISOString(),
  }));

  return { ...image, localPath: imgPath };
}

Step 3: Parallel Generation with Concurrency Control

import PQueue from "p-queue";

// 8 concurrent (under Ideogram's 10 in-flight limit)
const queue = new PQueue({ concurrency: 8 });

async function parallelGenerate(
  prompts: string[],
  options: { style_type?: string; model?: string } = {}
) {
  const start = Date.now();

  const results = await Promise.all(
    prompts.map(prompt =>
      queue.add(() => cachedGenerate(prompt, options))
    )
  );

  const elapsed = ((Date.now() - start) / 1000).toFixed(1);
  console.log(`Generated ${results.length} images in ${elapsed}s`);
  console.log(`Throughput: ${(results.length / (elapsed as any)).toFixed(2)} img/s`);

  return results;
}

// Generate 20 images -- queue manages concurrency automatically
const prompts = Array.from({ length: 20 }, (_, i) => `Product design variant ${i + 1}`);
await parallelGenerate(prompts, { style_type: "DESIGN", model: "V_2_TURBO" });

Step 4: CDN Upload for Fast Delivery

import { S3Client, PutObjectCommand } from "@aws-sdk/client-s3";

const s3 = new S3Client({ region: "us-east-1" });

async function generateWithCDN(prompt: string, options: any = {}) {
  const result = await cachedGenerate(prompt, options);

  // Upload to S3 for CDN delivery
  const key = `ideogram/${result.seed}.png`;
  const buffer = readFileSync(result.localPath);

  await s3.send(new PutObjectCommand({
    Bucket: process.env.S3_BUCKET!,
    Key: key,
    Body: buffer,
    ContentType: "image/png",
    CacheControl: "public, max-age=31536000, immutable",
  }));

  return {
    cdnUrl: `https://${process.env.CDN_DOMAIN}/${key}`,
    seed: result.seed,
    resolution: result.resolution,
  };
}

Performance Tips

  1. Use TURBO for drafts -- V_2_TURBO is 2-3x faster than V_2 at lower cost
  2. Cache by prompt hash -- identical prompts produce cacheable results
  3. Batch with num_images -- 4 images in 1 call is faster than 4 separate calls
  4. Download immediately -- URLs expire; download in the same function
  5. Set CDN headers -- images are immutable once generated; cache forever
  6. Use V3 FLASH for previews -- fastest option for UI thumbnails

Error Handling

IssueCauseSolution
Rate limit 429Concurrency too highReduce queue concurrency to 5-8
Slow generationQUALITY speed or complex promptUse TURBO for drafts, simplify prompts
Expired URLDelayed downloadDownload immediately in same function
Cache stalePrompt changed slightlyNormalize prompts before hashing

Output

  • Speed-tiered configuration for different use cases
  • Prompt-based cache layer preventing duplicate generations
  • Parallel generation with concurrency control
  • CDN integration for fast image delivery

Resources

Next Steps

For cost optimization, see ideogram-cost-tuning.

When not to use it

  • When Ideogram API URLs are stored without immediate download
  • When using V3 FLASH for final high-quality assets

Limitations

  • Ideogram API URLs are temporary and expire
  • Rate limits can be hit with high concurrency
  • Complex prompts or QUALITY speed can lead to slow generation

How it compares

This skill provides specific strategies for Ideogram API performance, such as model speed tiers and prompt-based caching, which differ from general API optimization techniques.

Compared to similar skills

ideogram-performance-tuning side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
ideogram-performance-tuning (this skill)127dCautionIntermediate
chrome-devtools417moReviewIntermediate
bullmq-specialist256moNo flagsIntermediate
perf-lighthouse135moReviewIntermediate

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