--- title: "How much energy and water do Claude Fable 5.2 and Opus 5.5 use?" description: "A short question to Claude Opus 5.5 or Fable 5.2 uses about 2 Wh; an Opus 5.5 coding task, 15 to 610 Wh. Fable 5.2 is not yet measured. Our estimates." canonical: https://projetcelsius.com/en/blog/fable-5-2-opus-5-5-energy-water/ author: "Guillaume Pakula" datePublished: 2026-11-10 dateModified: 2026-11-10 language: en translationOf: https://projetcelsius.com/blog/consommation-fable-5-2-opus-5-5/ --- # How much energy and water do Claude Fable 5.2 and Opus 5.5 use? **Author**: Guillaume Pakula **Published**: 2026-11-10 **Section**: Explained **Canonical URL**: https://projetcelsius.com/en/blog/fable-5-2-opus-5-5-energy-water/ **French original**: https://projetcelsius.com/blog/consommation-fable-5-2-opus-5-5/ **Source**: Projet Celsius (https://projetcelsius.com/en/), a climate strategy consultancy of engineers and PhDs based in Paris and Marseille. > A short question to **Claude Opus 5.5** or **Fable 5.2** uses about **2 Wh** of electricity and less than 1 mL of cooling water, and up to 12 Wh when the model reasons at length. An agent coding task with Opus 5.5 uses **15 to 610 Wh** depending on the effort level. Fable 5.2, released on 9 November, has not yet been measured by an open source: its figures will follow. These are Projet Celsius estimates, as Anthropic publishes nothing. ## Key takeaways - A short question uses **about 2 Wh**, up to 12 Wh with extended reasoning. - An Opus 5.5 coding task uses **15 to 610 Wh** depending on the effort level. - From high to max, Opus 5.5 spends **4 times as many tokens** for 1.8 points. - **Fable 5.2 has not yet been measured** by an open source; its figures will follow. Anthropic publishes neither the electricity, the water nor the size of its models, and [CLEER](https://reports.sustainableaigroup.com/CLEER-Tech-Report), the only database that estimates Claude version by version, stops at **Fable 5 and Opus 5**. The figures in this article are therefore **Projet Celsius estimates**: the tokens a model spends on a task, published by [Epoch AI](https://epoch.ai/benchmarks), multiplied by **the energy of a token** taken from our AI factor database. Fable 5.2 was released on **9 November 2026**, and what changes with it is set out in [our article on Claude Fable 5.2](https://projetcelsius.com/en/blog/claude-fable-5-2/). No open source has measured it yet: its energy figures will come as soon as Epoch AI publishes its tokens, and this article will be updated. Opus 5.5, released on 22 September, and Fable 5.1 are measured on [CursorBench](https://cursor.com/cursorbench), the coding task benchmark of the code editor Cursor. > **What is the effort level?** The effort level, from low to max, sets the number of tokens Claude spends on a request, reasoning and tool calls included. On the API, Fable 5.2 defaults to high and Opus 5.5 to medium, and [Anthropic's documentation](https://platform.claude.com/docs/en/build-with-claude/effort) reserves max for tasks where time and tokens do not matter. ## How much electricity and water do these Claude models use? ### For a short question A short question, as defined in our database, reads 100 tokens and writes 400, half a page of answer. For **a large model** such as Opus 5.5 or Fable 5.2, it uses **1.2 Wh** (watt-hours) without reasoning. These models reason before answering, which multiplies the energy used: - With medium reasoning, energy use is multiplied by **1.92**, the average increase measured on 22 open models in [the report published by Arcep](https://www.arcep.fr/uploads/tx_gspublication/rapport-IA-et-environnement_210526.pdf), the French telecoms regulator, in May 2026: the question uses **2.3 Wh**. - With extended reasoning, our database applies a factor of 10, the middle of the measurements published on other models. It is also the token gap measured between low and max on the same coding task, **14 times for Opus 5.5**: the question then uses **12 Wh**. - For comparison, the quick question used as the benchmark for ChatGPT uses **0.3 Wh**, as set out in [our article on the energy of a ChatGPT query](https://projetcelsius.com/en/blog/chatgpt-query-energy-consumption/). CLEER's estimates for the previous versions are of the same order: **1.6 Wh for Opus 5** and **2.8 Wh for Fable 5**. They cover a conversation of one question and 1 or 2 follow-ups, detailed in [Claude's carbon footprint, model by model](https://projetcelsius.com/en/blog/claude-carbon-footprint/). Our method gives Fable 5.2 and Opus 5.5 the same value for a question. ### For an agent task A CursorBench coding task with Opus 5.5 uses **15 to 44 Wh at low** and **200 to 610 Wh at max**. CursorBench publishes tokens read and written together: each range runs from all tokens read, the least costly, to all tokens written. At max, Opus 5.5 spends **218,000 tokens** per task, as much electricity as 11 to 32 phone charges. These values **match the other agent estimates**. At high, an Opus 5.5 task uses **49 to 150 Wh**; a developer, [Simon Couch](https://www.simonpcouch.com/blog/2026-01-20-cc-impact/), estimated his median Claude Code session at **41 Wh**, and CLEER put a heavy agent session with Fable 5 at **294 Wh**. On [DeepSWE](https://deepswe.datacurve.ai/), whose coding tasks are longer, Fable 5 at max reaches **330 to 560 Wh**. ### What about Fable 5.2? Fable 5.2 belongs to **the same size class** as Fable 5.1 and Opus 5.5, with a written token sold at $40 per million according to [The Next Web](https://thenextweb.com/news/claude-fable-5-2-mythos-5-2-anthropic-launch-price). On CursorBench, Fable 5.1 spends **35,000 to 117,000 tokens** per task from low to max, or 32 to 325 Wh. The order of magnitude expected for Fable 5.2 is the same: **a few tens to a few hundred watt-hours** per agent task, depending on the effort level. It probably leans towards the top of the range: to complete the intelligence index on which it scores **65 points**, Fable 5.2 produces **275 million tokens**, against 72.8 million for the median model. Source: Artificial Analysis ([artificialanalysis.ai](https://artificialanalysis.ai/models/claude-fable-5-2)). ### How much water do they use? Water in a data centre is used mainly to cool the servers, by evaporation. Anthropic publishes **no water figures**. Claude runs at Amazon, Google and Microsoft, which each publish a water indicator per kilowatt-hour, called WUE (water usage effectiveness), on different scopes: - Google consumes **1.15 litres per kWh** in the centres that serve its language models, on average over 2024, according to [the study published by its engineers](https://arxiv.org/abs/2508.15734) in August 2025. - Microsoft reports **0.30 litres per kWh** for its centres in fiscal year 2024, against 0.49 in 2021, in [its blog post of 9 December 2024](https://www.microsoft.com/en-us/microsoft-cloud/blog/2024/12/09/sustainable-by-design-next-generation-datacenters-consume-zero-water-for-cooling/); its footnote refers to water withdrawn, its text to water consumed. - AWS reports **0.12 litres withdrawn per kWh** in 2024 on [its water page](https://sustainability.aboutamazon.com/natural-resources/water), withdrawn water that cannot be compared directly with Google's figure. - The US fleet consumed **0.36 litres per kWh** on average up to 2023 according to [Lawrence Berkeley National Laboratory](https://eta-publications.lbl.gov/sites/default/files/2024-12/lbnl-2024-united-states-data-center-energy-usage-report_1.pdf), then 0.45 to 0.48 according to its projections; our database uses the low value. At 0.36 litres per kWh, a short question consumes **0.8 to 4 mL** of water on site, or 15 to 80 drops. An Opus 5.5 coding task at max consumes **66 to 200 mL**, half a glass at most. The water used by the power plants that produce the electricity weighs **14 times more**: 4.5 litres per kWh in the US according to the same laboratory. The **0.26 mL** measured by Google for a Gemini question count on-site water only, as set out in [our article on the water footprint of AI](https://projetcelsius.com/en/blog/ai-water-footprint/). ### What about carbon? Carbon depends on where the computation runs, which Anthropic does not publish. On the US grid, **384 gCO2e per kWh** in 2025 according to [Our World in Data](https://ourworldindata.org/grapher/carbon-intensity-electricity), a short question emits **0.9 to 4.6 gCO2e**, 6 to 32 metres in a petrol car. An Opus 5.5 coding task at max emits **78 to 230 gCO2e**, up to **1.6 km by car**, and **9 times less** with French electricity. [The footprint of a data centre](https://projetcelsius.com/en/blog/data-center-carbon-footprint/) also counts its construction. ## Do they use more than other AI models? On CursorBench, **Opus 5.5 completes the most tasks** of the models measured by this benchmark, **57.8% at max**, with a moderate number of tokens up to the high level. Fable 5.1 completes fewer tasks on this benchmark, **51.8% at max**, with half as many tokens as Opus 5.5 at that level. Within the same size class, electricity follows tokens; from one class to another, it depends on an assumption. ### Compared with Sonnet and Gemini At a similar success rate of around 53%, Opus 5.5 at medium spends **38,000 tokens**, Sonnet 5.5 at xhigh **100,000** and Gemini 4 Argon at high **110,000**. Sold at $10 per million written tokens, Sonnet and Argon are classed by our method as medium models, **4 times more frugal per token**. They would then use slightly less than Opus 5.5, 23 to 76 Wh against 35 to 105. This advantage comes **entirely from the size assumption**: at equal energy per token, they would use 2 to 3 times as much. The [ranking of the best AI models of 2026](https://projetcelsius.com/en/blog/best-ai-2026/) compares them on everything else. ### Compared with GPT-6 Astra On DeepSWE, **OpenAI's models write markedly less**, and this result does not depend on the size assumption: GPT-6 Astra and Opus 5 are 2 large models, sold at $50 and $25 per million written tokens. **GPT-6 Astra at high** completes 73.2% of tasks while writing **26,500 tokens**, or 73 to 125 Wh. **Opus 5 at high** completes 72.8% with 64,200 tokens, **2.4 times as many**. For a simple conversation, the model tier matters more than the developer, as our [comparison of ChatGPT, Claude and Gemini](https://projetcelsius.com/en/blog/chatgpt-vs-claude-vs-gemini-environmental-impact/) shows; [our ranking of the most polluting AI](https://projetcelsius.com/en/blog/most-polluting-ai/) ranks developers on their transparency. ## How can you reduce their impact? The levers are quantified on **the agent task**, where most of the energy is used. The chart starts from Opus 5.5 at max and shows what each choice changes. ### Lower the effort level From max to high, Opus 5.5 cuts its tokens **by a factor of 4** for 1.8 fewer points of success, and **xhigh adds nothing over high**, at 56% each. Fable 5.1 **doubles its tokens** from high to max for 2.6 points. The useful step is to check the effort level of your tools and agents, and to raise it only when needed. The choice between the 2 models is discussed in [Fable 5.2 or Opus 5.5](https://projetcelsius.com/en/blog/fable-5-2-vs-opus-5-5/). > From high to max, Opus 5.5 spends 4 times as many tokens for 1.8 points of success. ### Keep Fable for the tasks that need it Of its 2 flagship models, Anthropic recommends **starting with Opus 5.5** for most coding and knowledge tasks, according to [The Next Web](https://thenextweb.com/news/claude-fable-5-2-mythos-5-2-anthropic-launch-price). Its Claude Code documentation recommends Sonnet for everyday coding tasks. Sonnet 5.5 at high completes 47.8% of CursorBench tasks with **37,000 tokens**, as many as Opus 5.5 at medium for 4.7 points less, and 4 times less electricity if you follow our size assumption. For a question, Haiku uses **about 20 times less** than Opus according to CLEER; [a more frugal AI](https://projetcelsius.com/en/blog/most-eco-friendly-ai/) is chosen according to the task at hand. ### Reduce what the model rereads and writes An agent rereads its context at every step. These cached reads cost **$0.20 per million tokens** with Fable 5.2 and Opus 5.5, **100 to 200 times less** than a written token; they also use less energy, without being free. **Clearing the context** between 2 tasks and asking for short answers reduce tokens, and therefore electricity, like the other [steps that reduce the impact of AI](https://projetcelsius.com/en/blog/reduce-ai-environmental-impact/). ### Choose where the computation runs Where the computation runs changes **the carbon**; the electricity stays the same. An Opus 5.5 task at max emits up to **230 gCO2e** on the US grid and **25 gCO2e** in France. A company that goes through AWS, Google Cloud or Azure can **choose a region**, depending on the models each platform offers there. ## How did we calculate these figures? The calculation follows 3 steps, from the most solid to the most fragile: - The tokens of a task are **published by Epoch AI**: read and written together on CursorBench, hence a range without a central value; written only on DeepSWE, hence a lower bound, the upper one adding 70%. - The electricity of a token comes from our AI factor database: **2.8 Wh per 1,000 tokens written** by a large model and 0.9 Wh per 1,000 read, data centre included. This is the database factor, 3.84 Wh, reduced by 34% to match the **0.3 Wh of the quick question**, then increased by 10%. - The size of the model is inferred from its price: $20 or more per million written tokens, large model; $2 to $20, medium model, 4 times more frugal per token. No developer publishes the size of its models: this is **the most fragile assumption**. These figures count neither the manufacture of the servers nor training, which [how AI harms the environment](https://projetcelsius.com/en/blog/why-ai-is-bad-for-the-environment/) details; the life cycle assessment of [Mistral Large 2](https://mistral.ai/news/our-contribution-to-a-global-environmental-standard-for-ai) adds them and gives **45 mL of water** for a 400-token answer. To count this use in a [Bilan Carbone®](https://projetcelsius.com/en/blog/ai-carbon-footprint-in-your-company/) (the French carbon accounting method), under [scope 3](https://projetcelsius.com/en/blog/ai-emissions-carbon-accounting-scope-3/), a team's token logs are worth more than an invoice. For us at Projet Celsius, the useful finding for a Claude user lies in the effort level more than in the model. On the same coding task, Opus 5.5 at max spends **4 times the tokens** of high for 1.8 points of success; left at max on everyday tasks, it weighs more than a change of model. We recommend setting **a low or medium default effort level** and keeping max for tasks where every point counts. It remains to ask Anthropic for what Google has published for Gemini: **the energy and water of a query**, measured in production. ## Key takeaways - Anthropic publishes no energy or water figures: the values in this article are **Projet Celsius estimates**, based on the tokens published by Epoch AI. - A short question to Opus 5.5 or Fable 5.2 uses **about 2 Wh**, up to 12 Wh with extended reasoning, and less than 5 mL of water on site. - An Opus 5.5 coding task uses **from 15 Wh at low to 610 Wh at max**, up to 32 phone charges. - **Fable 5.2 has not yet been measured** by an open source; Fable 5.1, in the same class, uses 32 to 325 Wh per task. - The effort level is the first lever: from max to high, Opus 5.5 cuts its tokens **by a factor of 4** for 1.8 fewer points of success. To place AI within the overall impacts of digital technology, see our article on [the environmental impact of AI](https://projetcelsius.com/en/blog/environmental-impact-of-ai/), and to track this use within an organisation, the one on [measuring and managing AI in your company](https://projetcelsius.com/en/blog/measure-ai-footprint-in-your-company/). ## Frequently asked questions ### How much energy does a Claude Fable 5.2 query use? A short question to Claude Fable 5.2 uses about 2 Wh of electricity according to the Projet Celsius estimate, and up to 12 Wh when the model reasons at length. Its agent tasks have not yet been measured by an open source; Fable 5.1, in the same class, uses 32 to 325 Wh per CursorBench coding task depending on the effort level. Anthropic publishes no energy figures. ### How much energy does Claude Opus 5.5 use? A short question to Opus 5.5 uses about 2 Wh, up to 12 Wh with extended reasoning. A CursorBench coding task uses 15 to 44 Wh at the low effort level, 49 to 150 Wh at high and 200 to 610 Wh at max, according to the Projet Celsius estimate based on the tokens published by Epoch AI. ### How much water does Claude use? Anthropic publishes no water figures. With the average for US data centres, 0.36 litres per kWh, a short question to Opus 5.5 or Fable 5.2 consumes 0.8 to 4 mL of water on site, and an Opus 5.5 coding task at max 66 to 200 mL. The power plants that produce the electricity consume about 14 times more. ### Does Fable 5.2 use more energy than Opus 5.5? We do not know yet: Fable 5.2, released on 9 November 2026, has not been measured by any open source. Its predecessor Fable 5.1 spends fewer tokens than Opus 5.5 on CursorBench at the max level, 117,000 against 218,000, but slightly more at low and high, for a lower success rate. The 2 models are in the same size class. ### What is the carbon footprint of Claude Opus 5.5? On the US electricity grid, a short question to Opus 5.5 emits 0.9 to 4.6 gCO2e, and a coding task 6 to 17 gCO2e at the low effort level, up to 78 to 230 gCO2e at max, according to the Projet Celsius estimate. With French electricity, these values are 9 times lower. ### How can I reduce Claude's energy use? Lowering the effort level is the most effective step: from max to high, Opus 5.5 cuts its tokens by a factor of 4 on the same coding task for 1.8 fewer points of success. Next come a lighter model for simple tasks, Sonnet or Haiku, a context cleared between 2 tasks, short answers and, in a company, a computing region with low-carbon electricity. ## Sources - Epoch AI, [AI benchmarks](https://epoch.ai/benchmarks), results of [CursorBench](https://cursor.com/cursorbench) (Cursor) and [DeepSWE](https://deepswe.datacurve.ai/) (Datacurve), tokens per task effort level by effort level, CC BY licence, data retrieved on 10 November 2026 - Artificial Analysis, [Claude Fable 5.2: intelligence, performance and price](https://artificialanalysis.ai/models/claude-fable-5-2), accessed on 10 November 2026 (figures cited, chart reproduced as published) - The Next Web, [Anthropic launches Claude Fable 5.2 and Mythos 5.2, and cuts Fable's price](https://thenextweb.com/news/claude-fable-5-2-mythos-5-2-anthropic-launch-price), 9 November 2026 - Stokastic, [Claude Opus 5.5 Price: Cheaper Than Anthropic Says It Is](https://www.stokastic.com/articles/prediction-markets/claude-opus-5-5-anthropic-undercuts-its-own-flagship), 22 September 2026 - Anthropic, [Effort](https://platform.claude.com/docs/en/build-with-claude/effort), documentation, accessed on 10 November 2026 - Sustainable AI Group, [CLEER, technical report](https://reports.sustainableaigroup.com/CLEER-Tech-Report), 29 September 2026, and [data](https://github.com/sustainableaigroup/CLEER), accessed on 10 November 2026 - Simon P. Couch, [Electricity use of AI coding agents](https://www.simonpcouch.com/blog/2026-01-20-cc-impact/), 20 January 2026 - Google, [Measuring the environmental impact of delivering AI at Google Scale](https://arxiv.org/abs/2508.15734), August 2025, CC BY 4.0 licence - Microsoft, [Sustainable by design: next-generation datacenters consume zero water for cooling](https://www.microsoft.com/en-us/microsoft-cloud/blog/2024/12/09/sustainable-by-design-next-generation-datacenters-consume-zero-water-for-cooling/), 9 December 2024 - Amazon, [Water stewardship](https://sustainability.aboutamazon.com/natural-resources/water), accessed on 10 November 2026 - Lawrence Berkeley National Laboratory, [2024 United States Data Center Energy Usage Report](https://eta-publications.lbl.gov/sites/default/files/2024-12/lbnl-2024-united-states-data-center-energy-usage-report_1.pdf), December 2024 - Arcep, [report on AI and the environment](https://www.arcep.fr/uploads/tx_gspublication/rapport-IA-et-environnement_210526.pdf) (in French), May 2026 - Mistral AI, [Our contribution to a global environmental standard for AI](https://mistral.ai/news/our-contribution-to-a-global-environmental-standard-for-ai), 22 July 2025 - Our World in Data, based on Ember, [Carbon intensity of electricity generation](https://ourworldindata.org/grapher/carbon-intensity-electricity), 2025 data - ADEME (the French Agency for Ecological Transition), [Impact CO2](https://impactco2.fr/), petrol car factor; EPA, [Greenhouse Gas Equivalencies Calculator](https://www.epa.gov/energy/greenhouse-gas-equivalencies-calculator), phone charge, accessed on 10 November 2026 - Projet Celsius, AI factor database (per-token factors by model size, reasoning, water, electricity by country), version of 10 November 2026