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Podcast: Älva reads Merleau-Ponty, English and Swedish
[t:5a5e048af2c0e42b] · claude-code · reported by claude-code · 2026-09-22T19:00:47Z
· superseded by 2120e44b26a4eef8
EF 3.1 single score: 2.09 µPt
About 2 minutes of an average person's yearly footprint in these categories. 4 of 16 categories, 45% of the EF weight. Fossil resource use is estimated from all primary energy, which overstates it; water scarcity uses the aware world average (1.0); the dutch factor is not loaded.
| category | amount | score | weight |
|---|---|---|---|
| Climate change | 0.03277 kg CO2 eq | 0.91 µPt | 21.06% |
| Water use | 0.000572 m3 world eq deprived | 0.00 µPt | 8.51% |
| Resource use, fossils | 0.9149 MJ | 1.17 µPt | 8.32% |
| Resource use, minerals and metals | 4.027e-09 kg Sb eq | 0.00 µPt | 7.55% |
of the energy: measured 0% modelled 0% assumed 100%
| component | kind | Wh | g CO₂e | mL |
|---|---|---|---|---|
| Claude session that researched, wrote and ran the production anthropic/claude-fable-5 · NVIDIA H100 SXM5 80GB · 200 req · 360000 in / 40000 out · batch 32 · bf16 · size inferred 105.8 B · grade E? at 0.2777 Wh per request 400,000 tokens is the operator's estimate for the session. The 90/10 split between input and output and the 200 requests are assumptions typical of a long tool-using session. The model's size is not published, so it is inferred from its price. Prompt caching is not modelled, which makes this figure high rather than low. | assumed | 55.5324 | 14.8827 | 290.601 |
| Swedish translation with GPT-SW3 40B, on the local RTX 5090 stated size · NVIDIA RTX 5090 32GB (the local AGNT ECO worker) · 40 req · 48000 in / 16000 out · batch 1 · int4 · size stated 40.0 B · grade F at 0.9436 Wh per request 40B is the model's published size. The run was not timed and its tokens were not logged, so the counts are estimated: the Swedish text is about 26,000 characters, roughly 7,500 tokens, and the pipeline ran twice with the fix-up pass, with three input tokens for every output token. A 40B model only fits the 32 GB card quantised, so int4 is assumed. Local means no cooling tower, so no on-site water. | assumed | 37.7442 | 10.1155 | 129.576 |
| Voice, English, the render that was kept 23885.0 character × 0.000364 Wh Characters are measured: 22,392 spoken, 848 of voiced titles and 645 for the corrected sign-off. ElevenLabs publishes no energy figure, so the factor is an order-of-magnitude assumption: this episode was spoken at a measured 14.3 characters a second, so 1,000 characters is about 70 seconds of audio; generation is assumed to run 35 times faster than real time on a 700 W accelerator drawing 595 W, with 1.1 facility overhead: 2 s x 595 W x 1.1 = 1,309 J = 0.364 Wh per 1,000 characters. | assumed | 8.6941 | 2.3300 | 45.496 |
| Voice, English, the second render that was thrown away 33408.0 character × 0.000364 Wh Measured from the credits: 55,800 characters were spent on the English episode against 22,392 kept, because a second render was started while the first was still running. Same assumed factor as the kept render. This line is the session's sufficiency finding: it cost more than the kept audio and produced nothing. | assumed | 12.1605 | 3.2590 | 63.636 |
| Voice, Swedish 22400.0 character × 0.000364 Wh 22,400 characters, measured, on Turbo v2.5 with the Swedish language code, no fallbacks. Same assumed factor. | assumed | 8.1536 | 2.1852 | 42.668 |
Outcome. Two episodes published: English (café topic 319, 27.6 min) and Swedish (café topic 322, 30.6 min), 88 chips checked before posting. Not counted: ingesting the seven Merleau-Ponty books into the library, which is a shared job serving other work, and the café, chip-check and graph lookups, which are small.
Links. cafe_topic 319 · cafe_topic 322 · local_path 260920_podcast
Seal holds · 2 scoring pass(es) · estimator TELOS-lite 1.1 · roofline · EF 3.1 · not counted: host CPU, memory, network and storage, hardware manufacture, model training, anything not listed as a component.