OPENAI VS MISTRAL

GPT-5.6 Sol vs Mistral Large 3

Mistral Large 3 is about 15x cheaper than GPT-5.6 Sol on a blended 3:1 input:output rate — the same 10K-in/2K-out request costs $0.008 vs $0.11. GPT-5.6 Sol has the larger context window (1,047,576 vs 262,144 tokens).

Pricing verified

API pricing per 1M tokens

ModelInput / 1M tokensOutput / 1M tokensBlended (3:1 mix)
GPT-5.6 Sol$5.00$30.00$11.25
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.

ModelPer request (10K in / 2K out)Per month (100K requests)Monthly delta
GPT-5.6 Sol$0.11$11,000+$10,200
Mistral Large 3$0.008$800—

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

SpecGPT-5.6 SolMistral Large 3
ProviderOpenAIMistral
Context window1,047,576 tokens262,144 tokens
Model classGeneral textGeneral text
Tokenizero200k_base (exact, public)Proprietary (counts estimated)

Count tokens for each model on its own page: GPT-5.6 Sol 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 Sol vs Mistral Large 3 FAQ

Which is cheaper, GPT-5.6 Sol or Mistral Large 3?

Mistral Large 3 is cheaper. At rates checked 2026-08-11, GPT-5.6 Sol costs $5.00 input / $30.00 output per 1M tokens, while Mistral Large 3 costs $0.50 input / $1.50 output — about a 15x difference on a typical 3:1 input-heavy workload.

How much does a real request cost on GPT-5.6 Sol vs Mistral Large 3?

A request with 10,000 input tokens and 2,000 output tokens costs about $0.11 on GPT-5.6 Sol and $0.008 on Mistral Large 3. At 100,000 such requests per month that is $11,000 vs $800 — a difference of $10,200 per month.

Which has the bigger context window, GPT-5.6 Sol or Mistral Large 3?

GPT-5.6 Sol. It supports 1,047,576 tokens of context versus 262,144 tokens — roughly 786,000 English words in one request.

Do GPT-5.6 Sol and Mistral Large 3 count tokens the same way?

Not exactly. GPT-5.6 Sol 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.