Mistral Saba vs GPT-5.6 Luna: cost comparison
Prices updated 2026-11-06 · computed from live provider data
Short answer: Mistral Saba is cheaper on a
3:1 input/output blend — $0.300 per million tokens versus
$0.450, a 33% difference.
GPT-5.6 Luna offers the larger context window at 200,000 tokens, against 32,768 for Mistral Saba.
Head to head
| Mistral Saba | GPT-5.6 Luna | |
|---|---|---|
| Input, per 1M tokens | $0.200 | $0.200 |
| Output, per 1M tokens | $0.600 | $1.20 |
| Blended 3:1, per 1M | $0.300 | $0.450 |
| Context window | 32,768 | 200,000 |
| Vendor | mistralai | github_copilot |
Monthly cost at real volumes
| Workload (input / output) | Mistral Saba | GPT-5.6 Luna |
|---|---|---|
| 1M in / 250K out | $0.350 | $0.500 |
| 10M in / 2.5M out | $3.50 | $5.00 |
| 100M in / 25M out | $35.00 | $50.00 |
Which should you pick?
Pick GPT-5.6 Luna when you need the longer context window (200,000 vs 32,768 tokens). Pick Mistral Saba when price per token dominates your workload — high-volume classification, extraction, or batch summarisation.