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GPT-5.6 Luna vs Ministral 3 14B

Detailed pricing comparison and cost analysis.

Updated September 2026

Cost Simulator

GPT-5.6 Luna Cost
$0.44
Ministral 3 14B Cost
$0.24
Ministral 3 14B is 45% cheaper
FeatureGPT-5.6 LunaMinistral 3 14B
ProviderOpenAIMistral
Input Price (1M)$0.20$0.20
Output Price (1M)$1.20$0.20
Context Window1,000,000262,000

Verdict

GPT-5.6 Luna costs $0.20 per 1M input tokens and $1.20 per 1M output tokens. Ministral 3 14B costs $0.20 per 1M input tokens and $0.20 per 1M output tokens. GPT-5.6 Luna and Ministral 3 14B have identical input token pricing. For output tokens, Ministral 3 14B is the more affordable option at $0.20/1M vs $1.20.

On context window, GPT-5.6 Luna supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.

When to choose GPT-5.6 Luna

  • ✓ You need a larger context window (1,000,000 tokens)
  • ✓ You are already integrated with OpenAI

When to choose Ministral 3 14B

  • ✓ Your workload is output-heavy — Ministral 3 14B generates text cheaper
  • ✓ You are already integrated with Mistral

Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.

Frequently Asked Questions

Is GPT-5.6 Luna cheaper than Ministral 3 14B?

GPT-5.6 Luna and Ministral 3 14B have identical input token pricing at $0.20/1M tokens.

What is the context window of GPT-5.6 Luna vs Ministral 3 14B?

GPT-5.6 Luna has a 1,000,000-token context window. Ministral 3 14B has a 262,000-token context window. GPT-5.6 Luna supports the larger context, suitable for longer documents and agentic workflows.

Which model is better: GPT-5.6 Luna or Ministral 3 14B?

The best choice depends on your use case. For cost efficiency on input tokens, GPT-5.6 Luna is the cheaper option. For maximum context length, GPT-5.6 Luna supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.