Why Is Local Translation Slow on My Device?

Local AI translation speed varies dramatically based on your hardware. This article explains why and what you can do about it.

The Short Answer

Local translation runs entirely on YOUR computer’s CPU and memory. Faster hardware = faster translations. Unlike DeepL (which uses powerful cloud servers), local AI is limited by your system’s capabilities.

Performance Expectations

Key Performance Factors

1. CPU Speed and Generation

Why It Matters:

• Translation is computationally intensive
• Requires billions of mathematical operations
• Newer CPUs have better AI instructions (AVX2, etc.)

Impact:

• Modern CPUs (Intel 10th gen+, AMD Ryzen 3000+): 10-20 t/s
• Mid-range CPUs (Intel 6-9th gen, AMD Ryzen 1000-2000): 5-10 t/s
• Older CPUs (Intel 4th gen and below): 2-5 t/s

What You Can Do:

• Use CPU-optimized models (Rosetta 4B CPU)
• Close background applications
• Consider hardware upgrade if very old

2. Available RAM

Why It Matters:

• Models need 2-4GB RAM just to load
• Translation needs additional RAM for processing
• Low RAM causes system to swap to disk (very slow)

Impact:

• 16GB+ RAM: Excellent, no slowdowns
• 8-12GB RAM: Good, occasional slowdowns if many apps open
• 4-8GB RAM: Fair, MAITO auto-reduces context window
• <4GB RAM: Poor, constant swapping, very slow

What You Can Do:

• Close other applications before translating
• Restart computer to clear memory
• Add more RAM (biggest performance boost!)

3. GPU Availability

Why It Matters:

• GPUs are designed for parallel processing
• Can accelerate AI workloads dramatically
• DirectML models leverage GPU hardware

Impact:

• Dedicated GPU (NVIDIA/AMD): 2-3x faster with DML models
• Integrated GPU: Some improvement with DML models
• No GPU: CPU models work fine, just slower

What You Can Do:

• Try Rosetta 4B DML model if you have a GPU
• Benchmark both CPU and DML models to compare
• CPU models often better on older/integrated GPUs

4. Model Choice

Why It Matters:

• Different models have different optimization levels
• Some models better suited for specific hardware

Performance by Model:

• Rosetta 4B CPU: Best for CPU-only systems
• Rosetta 4B DML: Best for GPU systems
• Phi models: Comparable, try both

What You Can Do:

• Download multiple models
• Benchmark each
• Keep the fastest one for your system

5. System Load

Why It Matters:

• Translation competes with other applications for resources
• Background apps reduce available CPU/RAM

Impact:

• Clean system: Full performance
• Browser open: 10-20% slower
• Many apps running: 30-50% slower
• Heavy background tasks: 50%+ slower

What You Can Do:

• Close web browsers (Chrome is RAM-hungry)
• Quit unnecessary applications
• Check Task Manager for resource hogs
• Disable startup programs

6. Thermal Throttling

Why It Matters (Especially Laptops):

• CPUs slow down when overheating
• Laptops throttle more aggressively than desktops
• Extended translation sessions generate heat

Impact:

• First translation: Full speed
• After 5-10 minutes: May slow 20-30%
• Overheated laptop: Can slow 50%+

What You Can Do:

• Ensure good ventilation
• Use laptop cooling pad
• Clean dust from vents
• Let system cool between long translations

Real-World Examples

Example 1: Developer Laptop

• System: Dell XPS 15, Intel i7-11800H, 16GB RAM, NVIDIA GTX 1650
• Model: Rosetta 4B DML
• Performance: 18-22 tokens/sec
• Experience: Excellent, smooth, no complaints

Example 2: Budget Laptop

• System: HP 14, Intel i3-1005G1, 4GB RAM, integrated GPU
• Model: Rosetta 4B CPU
• Performance: 3-4 tokens/sec
• Experience: Slow but usable for short texts

Example 3: Gaming Desktop

• System: Custom build, Ryzen 9 5900X, 32GB RAM, RTX 3070
• Model: Rosetta 4B DML
• Performance: 25-30 tokens/sec
• Experience: Near-instant, exceptional

Example 4: Old Office PC

• System: Dell Optiplex 7010, Intel i5-3470 (2012), 8GB RAM
• Model: Rosetta 4B CPU
• Performance: 4-6 tokens/sec
• Experience: Functional but slow, DeepL recommended

Optimization Tips

Quick Wins (No Cost)

1. Close Background Apps

   • Especially web browsers
   • Check Task Manager for hidden programs

2. Restart Computer

   • Clears memory leaks
   • Frees cached resources

3. Try Different Models

   • Benchmark Rosetta CPU vs DML
   • Keep the fastest

4. Plug In Laptop

   • Battery mode limits performance
   • Full power when charging

5. Cool Your System

   • Avoid direct sunlight
   • Ensure airflow around vents
   • Pause if system is hot

Medium Effort

1. Clean Up Startup Programs

   • Disable unnecessary auto-start apps
   • Reduces background load

2. Update Drivers

   • Graphics drivers especially
   • Windows updates

3. Clean Dust from Computer

   • Improves cooling
   • Prevents thermal throttling

Hardware Upgrades

1. Add RAM (Biggest Impact)

   • 8GB → 16GB upgrade typically under $50
   • Biggest performance improvement
   • Recommended upgrade

2. Upgrade CPU

   • More expensive
   • May require motherboard change
   • Consider if PC is very old

3. Add GPU

   • Desktop only (laptops can’t upgrade)
   • Moderate improvement with DML models
   • Expensive, only for enthusiasts

When to Use DeepL Instead

Consider using DeepL if:

• Your system consistently gets <5 tokens/sec
• You find local translation too slow for your needs
• You have an older computer (<8GB RAM, old CPU)
• Waiting frustrates you
• You don’t translate frequently (cost is low)

DeepL Advantages:

• Consistently fast regardless of your hardware
• No performance variability
• Works great on any system

Remember: You can configure both engines and switch based on the situation!

What’s Next?

Learn more about performance:

• Device Assessment - Understand your hardware
• Benchmark Performance - Test your system
• Performance Optimization - Advanced tips
• Model Selection - Choose the right model