OPENAI VS MISTRAL
GPT-5.6 Luna vs Mistral Large 3
GPT-5.6 Luna is about 1.7x cheaper than Mistral Large 3 on a blended 3:1 input:output rate — the same 10K-in/2K-out request costs $0.0044 vs $0.008. GPT-5.6 Luna has the larger context window (1,047,576 vs 262,144 tokens).
Pricing verified
API pricing per 1M tokens
| Model | Input / 1M tokens | Output / 1M tokens | Blended (3:1 mix) |
|---|---|---|---|
| GPT-5.6 Luna | $0.20 | $1.20 | $0.45 |
| Mistral Large 3 | $0.50 | $1.50 | $0.75 |
Rates from official OpenAI pricing and official Mistral pricing, checked 2026-08-11.
What a real workload costs
Example: one request with 10,000 input tokens and 2,000 output tokens, then that request at 100,000 runs per month.
| Model | Per request (10K in / 2K out) | Per month (100K requests) | Monthly delta |
|---|---|---|---|
| GPT-5.6 Luna | $0.0044 | $440 | — |
| Mistral Large 3 | $0.008 | $800 | +$360 |
Model your own prompt sizes and volumes in the token cost analyzer, or check caching savings with the prompt caching calculator.
Specs side by side
| Spec | GPT-5.6 Luna | Mistral Large 3 |
|---|---|---|
| Provider | OpenAI | Mistral |
| Context window | 1,047,576 tokens | 262,144 tokens |
| Model class | General text | General text |
| Tokenizer | o200k_base (exact, public) | Proprietary (counts estimated) |
Count tokens for each model on its own page: GPT-5.6 Luna token counter and Mistral Large 3 token counter. All OpenAI models are on the OpenAI Token Counter. All Mistral models are on the Mistral Token Counter.
FAQ
GPT-5.6 Luna vs Mistral Large 3 FAQ
Which is cheaper, GPT-5.6 Luna or Mistral Large 3?
GPT-5.6 Luna is cheaper. At rates checked 2026-08-11, GPT-5.6 Luna costs $0.20 input / $1.20 output per 1M tokens, while Mistral Large 3 costs $0.50 input / $1.50 output — about a 1.7x difference on a typical 3:1 input-heavy workload.
How much does a real request cost on GPT-5.6 Luna vs Mistral Large 3?
A request with 10,000 input tokens and 2,000 output tokens costs about $0.0044 on GPT-5.6 Luna and $0.008 on Mistral Large 3. At 100,000 such requests per month that is $440 vs $800 — a difference of $360 per month.
Which has the bigger context window, GPT-5.6 Luna or Mistral Large 3?
GPT-5.6 Luna. It supports 1,047,576 tokens of context versus 262,144 tokens — roughly 786,000 English words in one request.
Do GPT-5.6 Luna and Mistral Large 3 count tokens the same way?
Not exactly. GPT-5.6 Luna uses the published o200k_base tokenizer and Mistral Large 3 uses a proprietary tokenizer (counts are estimates). The same prompt will tokenize differently, which shifts effective cost per word.