Llama 3 8B on RTX 5060 Ti 16GB – Monthly Cost Analysis

For Llama 3 8B on the RTX 5060 Ti 16GB at our dedicated hosting, the monthly economics are favourable at modest utilisation. Here is the full math.

Contents

• Monthly throughput capacity
• API equivalent spend
• Break-even utilisation
• Extra capacity you get
• Scaling path

Monthly Capacity

FP8 Llama 3 8B on 5060 Ti at sustained batch 8:

• Aggregate: ~540 tokens/sec
• Peak (batch 16): ~820 tokens/sec
• Hours in month: 720 (24 × 30)

At 50% average utilisation over the month:

• Output tokens: 540 × 3600 × 720 × 0.5 / 1000 ≈ 700 million/month
• Input tokens (assuming 3:1 ratio): ~2.1 billion/month

Realistic production throughput assumes traffic spikes and idle periods averaging out to 50%. For always-busy services, 70-80% sustained is achievable.

API Equivalent

Llama 3 8B competes on quality with GPT-4o-mini for many tasks. That’s the most relevant comparison for break-even.

Break-Even

Dedicated 5060 Ti monthly: ~£300 (~$380). Break-even versus:

• GPT-4o-mini at full 50% util: dedicated wins at ~35% utilisation
• Together.ai Llama 3 8B: dedicated wins at ~45-50% utilisation
• Anthropic Haiku class traffic: dedicated wins at ~10% utilisation

For production workloads running any real volume, dedicated hosting pays back.

Extra Capacity Included

Your £300/month buys more than just Llama 3 8B serving:

• Co-hosted BGE-M3 embedder (free headroom)
• Whisper Turbo transcription on the same card
• Small reranker or classifier
• Overnight QLoRA fine-tuning runs

API pricing requires paying per task. Dedicated hosting is flat-rate for everything the card can run.

Scaling

When you exceed the 5060 Ti’s concurrency:

• Add second 5060 Ti in data-parallel (~2x throughput, 2x cost)
• Upgrade to 5080 (~1.7x throughput, ~2.5x cost)
• Upgrade to 5090 (~3x throughput on same model, ~3x cost)

See broader break-even analysis.

See also: vs OpenAI API, ROI analysis.