Published rates rank differently once prompt caching, batch discounts and your own input-to-output ratio are applied. Run both against your numbers.
Mistral Large 3 vs GPT-4.1
European hosting against OpenAI's older mid tier.
Mistral retires Mistral Large 3 on 30 Apr 2027; the named replacement is Mistral Large 4. OpenAI retires GPT-4.1 on 14 Jan 2027; the named replacement is GPT-6 Luna.
Monthly cost by workload shape
The same volume costs very different amounts depending on the shape of the traffic. No caching or batch applied.
| Workload | Mistral Large 3 | GPT-4.1 | Difference | |
|---|---|---|---|---|
Support chat 200/day · 1500 in / 300 out | $7.31 | $32.88 | Mistral Large 3saves $25.57 | Model it → |
RAG / search answers 20K/day · 3000 in / 400 out | $1,278.48 | $5,600.96 | Mistral Large 3saves $4,322.48 | Model it → |
Agent / tool-use loop 8.0K/day · 2500 in / 600 out | $523.57 | $2,386.50 | Mistral Large 3saves $1,862.93 | Model it → |
Batch summarization 100K/day · 5000 in / 500 out | $9,893.00 | $42.6K | Mistral Large 3saves $32.7K | Model it → |
Code assistant 15K/day · 2000 in / 800 out | $1,004.52 | $4,748.64 | Mistral Large 3saves $3,744.12 | Model it → |
Frequently asked questions
Which is cheaper, Mistral Large 3 or GPT-4.1?
At a typical 3:1 input-to-output ratio, Mistral Large 3 is cheaper: $0.750 blended per 1M tokens against $3.50. Mistral Large 3 is cheaper at every input and output mix.
What is the price difference between Mistral Large 3 and GPT-4.1?
Mistral Large 3: $0.500 input, $1.50 output per 1M tokens. GPT-4.1: $2.00 input, $8.00 output. That is 4.0x on input and 5.3x on output.
Does prompt caching change the answer?
Mistral Large 3 caches input at $0.050/1M and GPT-4.1 caches at $0.500/1M. For input-heavy workloads with repeated context, caching can matter more than the base rate difference, model both in the calculator rather than comparing rate cards.
This page compares published prices only. It makes no claim about which model performs better on any task; that depends entirely on your evaluations.
Rate cards decide nothing on their own.
Most teams run several models at once. Finitizer Tokenomics shows what each one actually costs you, read from your own bills and exports, which workloads could test a smaller model, what they would cost on an open-weight model, and, for models you serve yourself, the cost per token beside the API price. A routing decision starts from your spend rather than a price page.
See Finitizer Tokenomics