CarbonWatch recognises 74 AI services. Each carries the type of use it serves and the region where it runs its inference — that region sets the carbon intensity applied, not the one you are in.
What the energy is spent on, rather than who profits from it.
What people call a chatbot: a question, a written answer, produced token by token. It is the most common type, and the one whose estimate is the most direct — the bytes arriving are the answer being written.
Completion in the editor, agents that write and run code, automated reviews. Usage is more continuous than in chat: the assistant answers every keystroke, not every question.
A question, an answer written from pages fetched and cited. The model reads far more than it writes, but only the answer crosses the network towards you.
Nothing is counted in tokens here: what arrives is the media itself. A two-megabyte image is two megabytes of payload, not two megabytes of framing around some text.
Ollama, LM Studio, llama.cpp and the others send nothing: the model runs here, and the electricity consumed is this socket's. It is the only case where the grid chosen in the settings applies.
A domain only enters the registry if it shares no IP address with obviously non-AI traffic. Detection works by address, never by hostname — nothing is decrypted. A shared address is therefore not an imprecision: it is foreign traffic billed as inference.
The 93 domains shipped were resolved and checked against a panel of Google, AWS, Cloudflare, Vercel and Akamai witnesses unrelated to AI. The current registry produces no collision, neither with those witnesses nor between two services.
What is deliberately absent, and why →
The registry is a JSON file dropped into the application's data folder on first launch, and openable from its settings. Adding an entry is enough to have a private service recognised — an Azure OpenAI deployment, for instance, whose endpoint is specific to each customer.
Two optional fields refine a service whose type rate would be wrong: bytesPerToken, when its stream framing differs, and whPerKtoken, when the model served is not a frontier one. A translation engine or a style checker runs on a small, specialised model an order of magnitude cheaper: without that second field, widening the registry would amount to billing DeepL like GPT.
The file is served as is, with no account and no key: it is the same list the application reads.
| Service | Type | Inference region | Intensity | 500-token answer |
|---|---|---|---|---|
| Claude | Chat | United States | 380 g/kWh | 0.38 g · 500 tokens |
| ChatGPT / OpenAI | Chat | United States | 380 g/kWh | 0.38 g · 500 tokens |
| Grok / xAI | Chat | United States | 380 g/kWh | 0.38 g · 500 tokens |
| Meta AI | Chat | United States | 380 g/kWh | 0.38 g · 500 tokens |
| Mistral / Le Chat | Chat | France | 50 g/kWh | 0.05 g · 500 tokens |
| DeepSeek | Chat | China | 580 g/kWh | 0.58 g · 500 tokens |
| Microsoft Copilot | Chat | United States | 380 g/kWh | 0.38 g · 500 tokens |
| Poe | Chat | United States | 380 g/kWh | 0.38 g · 500 tokens |
| Perplexity | Search | United States | 380 g/kWh | 0.48 g · 500 tokens |
| OpenRouter | Chat | World | 480 g/kWh | 0.48 g · 500 tokens |
| Groq | Chat | United States | 380 g/kWh | 0.38 g · 500 tokens |
| Together AI | Chat | United States | 380 g/kWh | 0.38 g · 500 tokens |
| Fireworks | Chat | United States | 380 g/kWh | 0.38 g · 500 tokens |
| Replicate | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Cohere | Chat | United States | 380 g/kWh | 0.38 g · 500 tokens |
| Hugging Face Inference | Chat | World | 480 g/kWh | 0.48 g · 500 tokens |
| GitHub Copilot | Coding | United States | 380 g/kWh | 0.57 g · 500 tokens |
| Cursor | Coding | United States | 380 g/kWh | 0.57 g · 500 tokens |
| Windsurf / Codeium | Coding | United States | 380 g/kWh | 0.57 g · 500 tokens |
| Sourcegraph Cody | Coding | United States | 380 g/kWh | 0.57 g · 500 tokens |
| ElevenLabs | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Midjourney | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Suno | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Runway | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Goose (agent) | Coding | World | 480 g/kWh | 0.72 g · 500 tokens |
| Aider (agent) | Coding | World | 480 g/kWh | 0.72 g · 500 tokens |
| Ollama (local) | Local models | this machine | — | 0.75 Wh/min · on this machine |
| LM Studio (local) | Local models | this machine | — | 0.75 Wh/min · on this machine |
| llama.cpp (local) | Local models | this machine | — | 0.75 Wh/min · on this machine |
| Jan (local) | Local models | this machine | — | 0.75 Wh/min · on this machine |
| Sora | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Luma / Dream Machine | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Pika | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Kling | Image, audio, video | China | 580 g/kWh | 2.32 g · 2 MB image |
| HeyGen | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Synthesia | Image, audio, video | European Union | 250 g/kWh | 1 g · 2 MB image |
| Ideogram | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Recraft | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Leonardo | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Stability AI | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Black Forest Labs / Flux | Image, audio, video | European Union | 250 g/kWh | 1 g · 2 MB image |
| Civitai | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Udio | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Adobe Firefly | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Krea | Image, audio, video | United States | 380 g/kWh | 1.52 g · 2 MB image |
| Qwen / Tongyi | Chat | China | 580 g/kWh | 0.58 g · 500 tokens |
| Kimi / Moonshot | Chat | China | 580 g/kWh | 0.58 g · 500 tokens |
| Zhipu / GLM | Chat | China | 580 g/kWh | 0.58 g · 500 tokens |
| Ernie / Baidu | Chat | China | 580 g/kWh | 0.58 g · 500 tokens |
| Doubao / ByteDance | Chat | China | 580 g/kWh | 0.58 g · 500 tokens |
| Z.ai | Chat | China | 580 g/kWh | 0.58 g · 500 tokens |
| Character.AI | Chat | United States | 380 g/kWh | 0.38 g · 500 tokens |
| Pi / Inflection | Chat | United States | 380 g/kWh | 0.38 g · 500 tokens |
| You.com | Search | United States | 380 g/kWh | 0.48 g · 500 tokens |
| Phind | Search | United States | 380 g/kWh | 0.48 g · 500 tokens |
| AWS Bedrock (US) | Chat | United States | 380 g/kWh | 0.38 g · 500 tokens |
| AWS Bedrock (UE) | Chat | European Union | 250 g/kWh | 0.25 g · 500 tokens |
| Continue | Coding | United States | 380 g/kWh | 0.57 g · 500 tokens |
| Tabnine | Coding | United States | 380 g/kWh | 0.57 g · 500 tokens |
| Zed AI | Coding | United States | 380 g/kWh | 0.57 g · 500 tokens |
| Bolt.new | Coding | United States | 380 g/kWh | 0.57 g · 500 tokens |
| Lovable | Coding | World | 480 g/kWh | 0.72 g · 500 tokens |
| Devin | Coding | United States | 380 g/kWh | 0.57 g · 500 tokens |
| Amp / Sourcegraph | Coding | United States | 380 g/kWh | 0.57 g · 500 tokens |
| DeepL | Chat | European Union | 250 g/kWh | 0.06 g · 500 tokens |
| Grammarly | Chat | United States | 380 g/kWh | 0.1 g · 500 tokens |
| vLLM (local) | Local models | this machine | — | 0.75 Wh/min · on this machine |
| LocalAI (local) | Local models | this machine | — | 0.75 Wh/min · on this machine |
| GPT4All (local) | Local models | this machine | — | 0.75 Wh/min · on this machine |
| Msty (local) | Local models | this machine | — | 0.75 Wh/min · on this machine |
| AnythingLLM (local) | Local models | this machine | — | 0.75 Wh/min · on this machine |
| ComfyUI (local) | Local models | this machine | — | 0.75 Wh/min · on this machine |
| KoboldCpp (local) | Local models | this machine | — | 0.75 Wh/min · on this machine |
| RamaLama (local) | Local models | this machine | — | 0.75 Wh/min · on this machine |