Wondering about how the OpenAI GPT and other AI model pricing works?
Here's a pricing calculator for OpenAI GPT API, Anthropic Claude API, Mistral API, Google Gemini API and others.
Provider | Model | Context Window | Best For | Input price per million |
Output price per million |
Price per API call |
Total price |
---|---|---|---|---|---|---|---|
o1 | 200k | Complex reasoning in science, coding, and mathematics | $15.00 | $60.00 | $((llms.o1.per)) | $((llms.o1.tot)) | |
o1-mini | 200k | Cost-effective reasoning in STEM fields | $1.10 | $4.40 | $((llms.o1mini.per)) | $((llms.o1mini.tot)) | |
o3-mini | 200k | Cost-effective reasoning in STEM fields | $1.10 | $4.40 | $((llms.o3mini.per)) | $((llms.o3mini.tot)) | |
GPT-4o | 128k | Complex language understanding and generation | $2.50 | $10.00 | $((llms.gpt4o.per)) | $((llms.gpt4o.tot)) | |
GPT-4o mini | 128k | Summarization and simple extraction task | $0.15 | $0.60 | $((llms.gpt4omini.per)) | $((llms.gpt4omini.tot)) | |
Claude 3.5 Sonnet | 200k | Advanced coding & real-world engineering tasks | $3.00 | $15.00 | $((llms.sonnet.per)) | $((llms.sonnet.tot)) | |
Claude 3.5 Haiku | 200k | Rapid data extraction and automated labeling | $0.80 | $4.00 | $((llms.haiku.per)) | $((llms.haiku.tot)) | |
Claude 3 Opus | 200k | Reasoning and human-like understanding | $15.00 | $75.00 | $((llms.opus.per)) | $((llms.opus.tot)) | |
Gemini 2.0 Flash | 1M | Low-latency general purpose tasks | $0.10 | $0.40 | $((llms.flash2.per)) | $((llms.flash2.tot)) | |
Gemini 2.0 Flash-Lite | 1M | Cost-efficient large-scale text based tasks | $0.075 | $0.30 | $((llms.flash2l.per)) | $((llms.flash2l.tot)) | |
Gemini 1.5 Flash | 1M | Rapid-response tasks like summarization | $0.075 | $0.30 | $((llms.flash15.per)) | $((llms.flash15.tot)) | |
Gemini 1.5 Flash-8B | 1M | Cost-effective chat, transcription, and translation | $0.0375 | $0.15 | $((llms.flalsh158.per)) | $((llms.flalsh158.tot)) | |
Gemini 1.5 Pro | 2M | Complex tasks requiring extensive context | $1.25 | $5.00 | $((llms.pro15.per)) | $((llms.pro15.tot)) | |
Mistral Large 24.11 | 128k | Complex reasoning tasks | $2.00 | $6.00 | $((llms.mlarge.per)) | $((llms.mlarge.tot)) | |
Mistral Small 3 | 32k | Low-latency tasks like chat | $0.10 | $0.30 | $((llms.msmall.per)) | $((llms.msmall.tot)) | |
Ministral 8B 24.10 | 128k | On-device computing and edge applications | $0.10 | $0.10 | $((llms.m8b.per)) | $((llms.m8b.tot)) | |
Ministral 3B 24.10 | 128k | On-device computing and edge applications | $0.04 | $0.04 | $((llms.m3b.per)) | $((llms.m3b.tot)) | |
deepseek-chat | 64k | Precise, concise responses in specialized fields | $0.07 | $1.10 | $((llms.chat.per)) | $((llms.chat.tot)) | |
deepseek-reasoner | 64k | Complex reasoning tasks in STEM fields | $0.14 | $2.19 | $((llms.reasoner.per)) | $((llms.reasoner.tot)) |
This are the estimates we are considering before calculating the price and other things.
1 word = ~1.30 tokens and 1 word = ~5.14 characters.
Please feel free to change the estimates to match it for your calculation manually.
Deploy LLM on your own server :)
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