iTechGuides is reader-supported. When you buy through links on our site, we may earn an affiliate commission. As an Amazon Associate I earn from qualifying purchases. Learn more
Elon Musk reportedly said Tesla plans to cut AI5 memory from 144 GB to 72 GB of LPDDR5 and reduce AI6 memory by one-third, to 144 GB of LPDDR6. He said the changes should help secure enough chips for Optimus production and lower cost, with a “negligible effect on Optimus performance.” That is Musk’s assessment as reported by Benzinga, not a result confirmed by independent benchmarks or tests on production robots.
What Tesla reportedly changed
Reports published October 1 and 2, 2026, say Musk described reductions to the planned memory capacity of two Tesla inference chips. The figures below are reported statements about planned configurations, not specifications in a Tesla-published datasheet.
| Chip | Previously planned memory | Reported revised memory | Reported change |
|---|---|---|---|
| AI5 | 144 GB | 72 GB LPDDR5 | Capacity cut in half |
| AI6 | Not stated in the cited reports | 144 GB LPDDR6 | Reduced by one-third |
Benzinga’s account attributes the production rationale to Musk’s statement that the cuts were “the only way to get enough volume for Optimus production.” It also reports that he expects lower costs. The original X post was not independently retrieved, so the figures and quotations remain attributed claims in secondary reporting.
Why Musk says less memory should not matter much
Musk reportedly argued that memory bandwidth—the rate at which data can move to and from memory—matters more to performance than total memory capacity. Capacity is how much information can be held at once; bandwidth is how quickly the chip can access it. A chip with less memory may still perform adequately if its workloads fit and data can be moved fast enough, but that does not establish that every Optimus task or configuration will do so.
#1 Best Overall
- ESP32-S3-ePaper-1.54 development board onboard 1.54inch e-paper display, 200 × 200 resolution, features high contrast and wide viewing angle. Onboard audio codec chip, supports voice capture and playback, enabling AI voice interaction applications
- ESP32-S3 1.54inch e-Paper AIoT development board adopts high-performance 32-bit LX7 dual-core processor, up to 240MHz main frequency. Supports 2.4GHz Wi-Fi (802.11 b/g/n) and Bluetooth 5 (LE), with onboard antenna
- Onboard PCF85063 RTC chip and SHTC3 temperature & humidity sensor for accurate RTC management and environmental monitoring
- Built-in 512KB Static RAM, 384KB ROM, with integrated 8MB Flash and 8MB PSRAM
- Onboard TF card slot for external storage of images or files. Onboard programmable PWR and BOOT side buttons for customized function development. Reserved 2 × 6 2.54mm pitch pin header for convenient external expansion
The reported “negligible effect” is therefore a prediction, not a demonstrated comparison. The reviewed reports do not provide benchmarks contrasting the earlier and revised AI5 or AI6 configurations, nor do they show reduced-memory chips operating in production Optimus robots. Actual impact would depend on the robot’s full system design and workloads, not just the memory number.
How the cuts fit Tesla’s production constraints
Tesla had already described chip supply as a possible constraint on scaling Optimus. On the company’s Q2 2026 earnings call, Musk said Tesla would need to “solve memory, logic, and packaging” to scale production, and identified AI5 as initially intended for Optimus. He thanked TSMC, Samsung, and Micron for support. Those comments provide supply-chain context; they do not independently confirm the October capacity figures.
Rank #2
- This is is 1.54inch e-Paper AIoT development board. Onboard 1.54inch e-paper display, 200 x 200 resolution, features ultra-low power consumption and ambient light readability, suitable for portable devices and long-battery-life scenarios. Supports 2.4GHz Wi-Fi (802.11 b/g/n) and Bluetooth 5 (LE), with onboard antenna.
- Integrated with an RTC chip, SHTC3 temperature and humidity sensor, TF card slot, low-power audio codec chip circuit, and Lithium battery recharge management circuit. Reserved interfaces including USB, UART, I2C, and GPIO for easy functionality expansion and sensor connectivity, providing a flexible and reliable development platform for IoT terminals, electronic tags, portable displays, and other applications.
- Supports AI Speech Interaction: Allows access to online large model platforms such as ChatGPT, DeepSeek, Doubao, etc. Onboard audio codec chip, supports voice capture and playback, enabling AI voice interaction applications.
- Built-in 512KB Static RAM, 384KB ROM, with integrated 8MB Flash and 8MB PS RAM. Onboard PCF85063 RTC chip and SHTC3 temperature & humidity sensor for accurate RTC management and environmental monitoring.
- Onboard TF card slot for external storage of images or files. Onboard programmable PWR and BOOT side buttons for customized function development. Reserved 2 × 6 2.54mm pitch pin header for convenient external expansion.
Tesla’s Q1 2026 investor update said the final design of its next-generation AI5 inference processor was completed in April. It also described plans with SpaceX for a fab combining logic, memory, and advanced packaging in response to anticipated demand beyond existing and planned chip capacity. That is evidence of a stated supply strategy, not confirmation that the revised-memory chips are being manufactured or installed in robots.
Free tools Windows power users keep installed
One-click scans. No signup required.
Does Optimus need more than 200 GB of memory?
Not on the evidence available here. Benzinga reported that Micron CEO Sanjay Mehrotra forecast more than 200 GB of memory and multiple terabytes of storage per humanoid robot. That is a broad industry expectation, not a Tesla Optimus requirement or specification. It also is not established as directly comparable to the per-chip AI5 and AI6 figures: a robot’s total system memory and storage can differ from the memory attached to one processor.
Rank #3
- 【Flagship performance, extremely fast response】Equipped with a 1.6GHz main frequency chip, the KPU computing power is 13.7 times that of the K210 visual module, and the CPU computing power is 8.5 times that of the K210. It supports real-time operation of complex AI models and can easily cope with high-load tasks such as image recognition and voice processing.
- 【Flexible expansion development】A new 12Pin GPIO interface is added, which is compatible with a variety of sensors and modules; pre-installed GUI program, a large program based on the RTSmart system, contains 30+ functional gameplay, integrates most of the core functions, and each function comes with instructions, so you can experience the fun of AI without programming basics.
- 【Multi-controller compatibility】Equipped with a serial communication interface, it can be seamlessly connected to various controllers, and supports connection to PC computers, MSPM0, STM32, ESP32, PICO, Raspberry Pi, UNO, Microbit, Jetson, RDK and other mainstream controller development. You can easily output the visual recognition results to an external controller through the serial port without delving into complex visual algorithms, making it easy to create innovative AI projects.
- 【Multi-function AI visual camera】The K230 visual module is equipped with a 2.4-inch LCD capacitive touch screen with clear display and a 2MP camera for quick debugging and control. The module integrates a serial port, which can easily connect various sensors to expand functions. , with color recognition, road sign recognition, visual line patrol, face recognition, label recognition, QR code and barcode recognition, feature detection, digital recognition and other functions.
- 【Developers from entry to mastery】Provides original model training tutorials+self-developed upper computer toolkits, compatible with ESP32 ecology, suitable for education, maker and industrial visual project development. Yahboom provides technical Q&A + lifetime firmware updates to help your AI project from prototype to landing without worry!
Tesla’s AI webpage discusses the scale of its self-driving neural-network training, stating that one full build involves 48 networks and 70,000 GPU hours. Those figures concern training Tesla’s self-driving networks, not Optimus hardware or an AI5/AI6 performance test, so they do not resolve what memory capacity Optimus requires.
Quick Recap
Rank #4
- High-Performance AI Voice Interaction Development Board: Features a dual-core RISC-V processor (up to 160MHz), onboard dual microphone array, speakers, and an ES8311 audio codec chip, supporting noise reduction and echo cancellation. It can easily connect to large online models like DeepSeek for intelligent voice dialogue.
- Integrating Advanced Wireless Connectivity: ESP32-C6 supports Wi-Fi 6, Bluetooth 5.0, and Zigbee 3.0/Thread protocols, boasting excellent RF performance and multi-protocol compatibility, making it suitable for wireless communication development in IoT and wearable devices.
- Equipped with a 1.83-inch capacitive touchscreen LCD: (240×284 resolution, 65K colors), it offers high responsiveness and light transmittance. Combined with an onboard six-axis sensor (accelerometer + gyroscope) and RTC chip, it supports motion monitoring, step counting, and low-power real-time clock applications.
- Low Power Design: built-in Batt. recharge chip, a Type-C interface, and supports flexible clock and power control, enabling low-power operation in various scenarios, making it convenient for carrying around and long-term use.
- Rich Interfaces: It offers a wealth of expansion interfaces and customization features, including GPIO, I2C, and UART pads, two programmable side buttons, support for external sensors and debugging, and facilitates rapid prototyping and functional verification.
What is known—and what remains open
- Reported plan: AI5 is said to move from 144 GB to 72 GB LPDDR5; AI6 is said to have 144 GB LPDDR6 after a one-third reduction.
- Stated rationale: Musk reportedly linked the cuts to chip volume for Optimus production and lower costs, while saying bandwidth is more important than capacity for performance.
- Not established: Tesla has not published, in the sources cited here, a specification sheet verifying the revised capacities, and no independent benchmark or production-robot test confirms the performance claim.
- Manufacturing status: The available company statements describe supply challenges and plans, but do not establish that the revised configurations are operating in Optimus units.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
