Machine Learning: Episode I
Machine Learning: Episode I has an FPSHQ demand score of 58/100: moderate requirements — runs on mid-range cards like the RTX 3060 / RX 6600. Source of the numbers: per the system requirements on Steam.
Machine Learning: Episode I is a game by Volens Nolens Games. Steam release date: September 10, 2016. Minimum graphics card per Steam: Geforce GTX970. It needs at least 8 GB of RAM.
Description
Machine Learning: Episode is a first person arcade puzzle game built for HTC Vive. You play as an A.I. robot created in DARPA laboratory in the near future. One of the scientists is here to test your physical, perception and cognitive skills. By using the power of room-scale VR and Vive controllers
Data: the game’s Steam store page
About the game
- Developer
- Volens Nolens Games
- Publisher
- Volens Nolens Games
- Release date
- September 10, 2016
- PC platforms
- Windows
- Steam store page
- store.steampowered.com/app/524030
Machine Learning: Episode I system requirements
| Component | Minimum | Recommended |
|---|---|---|
| OS | Windows 8.1 | Windows 10 |
| Processor | Core i5 | Core i7 |
| Memory | 8192 MB ОЗУ | 12288 MB ОЗУ |
| Graphics | Geforce GTX970 | Geforce GTX980Ti |
| DirectX | версии 11 | версии 11 |
| Storage | 560 MB | 560 MB |
| Поддержка VR | SteamVR. Room Scale 2m by 2m area required | — |
Source: the game’s Steam page — requirements published by the developer.
How big is Machine Learning: Episode I and does it need an SSD
Machine Learning: Episode I needs 560 MB of disk space, according to its official system requirements (the game’s Steam page, data as of Nov 10, 2026). requirements
The requirements of Machine Learning: Episode I do not state a drive type — an SSD is not officially required; it only speeds up loading.
Source: official system requirements (the game’s Steam page), captured Nov 10, 2026. The size is the free space needed to install; updates and DLC can make it grow. store.steampowered.com
Tip: keep extra space beyond the listed size — updates are downloaded first and installed afterwards.
Ranking: how big 122429 popular games are and which need an SSD →
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FPS on different graphics cards
FPS forecast for Machine Learning: Episode I on current 2024–2026 GPUs. Switch the graphics preset — the table recalculates. Average FPS at 1080p / 1440p / 4K.
| Graphics card | Tier | 1080p | 1440p | 4K |
|---|---|---|---|---|
| GeForce RTX 5090 | S | 200–335 | 160–270 | 94–160 |
| GeForce RTX 4090 | S | 185–310 | 140–230 | 77–130 |
| GeForce RTX 5080 | S | 170–285 | 120–205 | 67–115 |
| GeForce RTX 4080 Super | A | 155–265 | 110–185 | 60–100 |
| GeForce RTX 4080 | A | 150–255 | 105–175 | 57–95 |
| Radeon RX 7900 XTX | A | 150–255 | 105–180 | 57–95 |
| GeForce RTX 5070 Ti | A | 145–245 | 100–170 | 53–90 |
| Radeon RX 9070 XT | A | 140–240 | 98–165 | 51–87 |
| Radeon RX 7900 XT | A | 125–220 | 88–150 | 46–78 |
| GeForce RTX 4070 Ti Super | A | 135–230 | 93–160 | 50–84 |
| GeForce RTX 3090 Ti | B | 120–210 | 84–140 | 44–76 |
| Radeon RX 9070 | A | 120–205 | 82–140 | 43–73 |
* Average FPS: real measurements where available, otherwise the unified FPSHQ model. Actual FPS depends on the CPU, game patch and drivers. Reference GPU models without overclocking. methodology
📊 FPS by graphics card (1440p, Ultra)
Green — 60+ FPS (comfortable), yellow — 30–60 (playable), red — below 30. Dashed line marks 60 FPS.
Which graphics cards can run Machine Learning: Episode I
Cards at least as fast as the Steam minimum (Geforce GTX970). FPS is an FPSHQ model forecast for 1080p High, not a measurement.
- GeForce GTX 1650 ≈28 FPS
- Radeon RX 480 ≈28 FPS
- GeForce GTX 970 ≈28 FPS
- GeForce GTX 1070 Ti ≈60 FPS
- GeForce GTX 1080 ≈61 FPS
- GeForce RTX 2060 ≈61 FPS
Submit an FPS measurement
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The FPSHQ app for Windows computes average FPS and 1% low from frame times (PresentMon) and, with your consent, submits the result itself.
Get the appOnly aggregates are published: a median over 2+ devices or after review. No name or IP is stored — only a hash to stop abuse. Methodology
The higher it is, the more powerful a PC you need. Moderate load.
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GPU ranking for Machine Learning: Episode I →Key figures
Unique FPSHQ metrics from this page's data
Can my PC run Machine Learning: Episode I?
Machine Learning: Episode I (2016): FPSHQ load index 58 out of 100. Per the FPSHQ model, GeForce RTX 3060 delivers 72–120 FPS at 1080p High and GeForce RTX 4070 67–115 FPS at 1440p Ultra; 5 of 12 popular GPUs hold 60+ FPS at 1440p Ultra. Developer's minimum GPU: Geforce GTX970; minimum RAM: 8 GB. Source of the numbers: per the system requirements on Steam (checked Nov 10, 2026); FPSHQ model estimate (not a measurement). (model accuracy)
- FPSHQ load index
- 58 FPSHQ index
- RTX 3060 · 1080p High
- 85 FPS model estimate
- RTX 4070 · 1440p Ultra
- 92 FPS model estimate
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