Budget Showdown
GPT-5.6 Luna vs Mistral Small 4
Budget vs budget. Which low-cost model gives you more bang for your buck?
Last verified: Jul 13, 2026 · See all 67 models ranked →
| Feature | GPT-5.6 Luna | Mistral Small 4 |
|---|---|---|
| Input price (per 1M tokens) | $1.00 | $0.15 |
| Output price (per 1M tokens) | $6.00 | $0.60 |
| Context window | 1.05M tokens | 128K tokens |
| Standard request cost | $0.0039 | $0.000465 |
| Output-heavy request cost | $0.012 | $0.0012 |
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OpenAI
GPT-5.6 Luna
$0
estimated monthly cost
Input cost$0
Output cost$0
Per request$0
Mistral
Mistral Small 4
$0
estimated monthly cost
Input cost$0
Output cost$0
Per request$0
The Verdict
Mistral Small 4 wins on price. GPT-5.6 Luna wins on context and quality.
Mistral Small 4 ($0.15/$0.60) is 85% cheaper on input and 90% cheaper on output than GPT-5.6 Luna ($1/$6). But Luna has an 8x larger context window (1.05M vs 128K tokens) and generally better performance on complex tasks. The right choice depends on whether you need long-context processing or just cheap, simple inference.
When to Choose Mistral Small 4
- Ultra-high-volume workloads: At $0.15/$0.60 per 1M tokens, Mistral Small is the cheapest option for massive-scale processing. 100K requests/day costs just $14/mo.
- Simple classification tasks: Intent detection, sentiment analysis, content moderation — these don't need large context or premium quality.
- Prototype and MVP development: Build fast, iterate cheap. Upgrade to Luna or higher when you need more capability.
- Budget-constrained projects: When every dollar matters and you can work within the 128K context limit.
When to Choose GPT-5.6 Luna
- Long-document processing: Luna's 1.05M context window handles entire codebases, legal documents, or research papers that Mistral Small's 128K cannot.
- Better quality on complex tasks: Luna generally outperforms Mistral Small on multi-step reasoning, code generation, and nuanced instruction following.
- OpenAI ecosystem: If you're already using OpenAI's API and want to stay in their ecosystem with a budget option.
- Hybrid cost optimization: Use Luna for tasks that need more than 128K context, route simpler tasks to Mistral Small.
Cost Comparison: Real-World Scenarios
Chatbot (1,000 requests/day, 1,500 input, 400 output)
GPT-5.6 Luna$117.00/mo
Mistral Small 4$13.95/mo
Monthly savings$103.05/mo (88%)
Code Generation (200 requests/day, 3,000 input, 1,200 output)
GPT-5.6 Luna$468.00/mo
Mistral Small 4$41.40/mo
Monthly savings$426.60/mo (91%)
RAG Pipeline (500 queries/day, 5,000 input, 800 output)
GPT-5.6 Luna$735.00/mo
Mistral Small 4$83.25/mo
Monthly savings$651.75/mo (89%)
Full Comparison Table
| Model | Input/1M | Output/1M | vs Luna | Context |
|---|---|---|---|---|
| GPT-5.6 Luna | $1.00 | $6.00 | — | 1.05M |
| Mistral Small 4 | $0.15 | $0.60 | 85% cheaper input, 90% cheaper output | 128K |
| DeepSeek V4 Flash | $0.14 | $0.28 | 86% cheaper input, 95% cheaper output | 1M |
| GPT-5.4 nano | $0.20 | $1.25 | 80% cheaper input, 79% cheaper output | 400K |
| Gemini 3.5 Flash | $0.075 | $0.30 | 93% cheaper input, 95% cheaper output | 1M |
| DeepSeek V4 Pro | $0.43 | $0.87 | 57% cheaper input, 85% cheaper output | 1M |
| GPT-5.4 mini | $0.75 | $4.50 | 25% cheaper input, 25% cheaper output | 400K |
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