Directory · Model comparison
GPT-5.6 Luna vs Qwen3-Coder-480B-A35B-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 | Qwen3-Coder-480B-A35B-Instruct |
|---|---|---|
| Input cost / 1M | $1.00 | $1.50 |
| Output cost / 1M | $6.00 | $7.50 |
| Context window | 1,050,000 tokens | 262,144 tokens |
| MMLU score | — | — |
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
Qwen3-Coder-480B-A35B-Instruct
- Input: 1M × $1.50 = $1.50
- Output: 1M × $7.50 = $7.50
- Total
- $9.00
Total cost savings
$2.00
GPT-5.6 Luna saves $2.00 per month vs the other model at this volume.
Model routing savings
Uses this page's verified rates. Qwen3-Coder-480B-A35B-Instruct is the premium route (higher combined per-1M cost); GPT-5.6 Luna handles routine traffic.
All premium
Qwen3-Coder-480B-A35B-Instruct
$450.00
100% of input and output on the premium route
Routed stack
80% → GPT-5.6 Luna
20% → Qwen3-Coder-480B-A35B-Instruct
$370.00
- Routine slice
- $280.00
- Premium slice
- $90.00
Monthly savings
$80.00
17.8% lower
Rates pulled from this page's model database entries (qwen3-coder-480b-a35b, gpt-5-6-luna) — same per-1M input/output figures as Tale of the tape. Production routing needs quality gates and monitoring.
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