Directory · Model comparison
GPT-5.6 Luna vs Llama 3.3 70B Instruct
Side-by-side API economics and benchmarks. Per-1M input and output rates, context window, and verified metrics.
Tale of the tape
Head-to-head specs pulled from each model profile.
| Metric | GPT-5.6 Luna | Llama 3.3 70B Instruct |
|---|---|---|
| Input cost / 1M | $1.00 | $0.10 |
| Output cost / 1M | $6.00 | $0.32 |
| Context window | 1,050,000 tokens | 128,000 tokens |
| MMLU score | — | 86% |
Cost verdict
Enter monthly input and output volumes to see total cost savings.
GPT-5.6 Luna
- Input: 1M × $1.00 = $1.00
- Output: 1M × $6.00 = $6.00
- Total
- $7.00
Llama 3.3 70B Instruct
- Input: 1M × $0.10 = $0.10
- Output: 1M × $0.32 = $0.32
- Total
- $0.42
Total cost savings
$6.58
Llama 3.3 70B Instruct saves $6.58 per month vs the other model at this volume.
Model routing savings
Uses this page's verified rates. GPT-5.6 Luna is the premium route (higher combined per-1M cost); Llama 3.3 70B Instruct handles routine traffic.
All premium
GPT-5.6 Luna
$350.00
100% of input and output on the premium route
Routed stack
80% → Llama 3.3 70B Instruct
20% → GPT-5.6 Luna
$86.80
- Routine slice
- $16.80
- Premium slice
- $70.00
Monthly savings
$263.20
75.2% lower
Rates pulled from this page's model database entries (gpt-5-6-luna, llama-3-3-70b-instruct) — same per-1M input/output figures as Tale of the tape. Production routing needs quality gates and monitoring.
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