GPT-4.1 mini API pricing (August 2026)
What it costs at real volumes
A chat-shaped workload: 800 input tokens and 300 output tokens per request, no caching, no batch.
Specifications
- Provider
- OpenAI
- Context window
- 1.0M tokens
- Max output
- 33K tokens
- Tier
- small
- Status
- GA
- Blended $/1M (3:1)
- $0.700
- Cache break-even hit rate
- 0% — caching always saves
- Prices verified
- 4 Aug 2026
Source: OpenAI pricing. Finitizer is not affiliated with OpenAI.
Similar models
Other gpt models
- GPT-5+$2.74
- GPT-5 mini$-0.013
- GPT-5 nano$-0.563
- GPT-4.1+$2.80
- GPT-4.1 nano$-0.525
- GPT-4o+$3.68
- GPT-4o mini$-0.438
- o3+$2.80
- o4-mini+$1.23
Closest prices elsewhere
- Mistral Large 3+$0.050
- Llama 3.3 70B (Groq)$-0.060
- Gemini 2.5 Flash+$0.150
- DeepSeek V4 Pro$-0.156
Frequently asked questions
How much does GPT-4.1 mini cost per 1M tokens?
GPT-4.1 mini costs $0.400 per million input tokens and $1.60 per million output tokens at OpenAI list prices. Output is 4.0x the input rate, so the input:output ratio of your workload drives the real cost more than the headline price.
Does GPT-4.1 mini support prompt caching?
Yes. Cached input is billed at $0.100 per million tokens, 4x cheaper than uncached input. There is no cache-write premium, so caching is never a net loss.
What is the batch discount for GPT-4.1 mini?
Requests submitted through the asynchronous batch endpoint are billed at 50% off both input and output rates, bringing input to $0.200 and output to $0.800 per million tokens.
What is GPT-4.1 mini's context window?
1.0M tokens of context with up to 33K output tokens per request. A larger context window raises the ceiling on what you can send, not the price per token — but filling it on every request is one of the most common causes of an unexpected bill.
Running GPT-4.1 mini in production?
Finitizer TokenOps attributes real token spend to teams, features, and prompts — so you find out which workload moved the bill before the invoice does.