Computer performance by orders of magnitude

This list compares various amounts of computing power in instructions per second organized by

• 2×10⁻³: average human multiplication of two 10-digit numbers using pen and paper without aids[1]

• 1×10⁻¹: multiplication of two 10-digit numbers by a 1940s electromechanical desk calculator^[1]
• 3×10⁻¹: multiplication on
  digital computers
  , 1941 and 1945 respectively
• 5×10⁻¹: computing power of the average human mental calculation^{[clarification needed]} for multiplication using pen and paper

• 1.2 OP/S: addition on Z3, 1941, and multiplication on Bell Model V, 1946
• 2.4 OP/S: addition on Z4, 1945

• 1.8×10¹: ENIAC, first programmable electronic digital computer, 1945^[2]
• 5×10¹: upper end of serialized human perception computation (light bulbs do not flicker to the human observer)
• 7×10¹: Whirlwind I 1951 vacuum tube computer and IBM 1620 1959 transistorized scientific minicomputer^[2]

• 1.3×10²: PDP-4 commercial minicomputer, 1962^[2]
• 2×10²: IBM 602 electromechanical calculator (then called computer), 1946^{[citation needed]}
• 6×10²: Manchester Mark 1 electronic general-purpose stored-program digital computer, 1949^[3]

• 2×10³: UNIVAC I, first American commercially available electronic general-purpose stored program digital computer, 1951^[2]
• 3×10³: PDP-1 commercial minicomputer, 1959^[2]
• 15×10³: IBM Naval Ordnance Research Calculator, 1954
• 24×10³: AN/FSQ-7 Combat Direction Central, 1957^[2]
• 30×10³: IBM 1130 commercial minicomputer, 1965^[2]
• 40×10³: multiplication on Hewlett-Packard 9100A early desktop electronic calculator, 1968
• 53×10³:
  Lincoln TX-2 transistor-based computer, 1958^[2]
• 92×10³: Intel 4004, first commercially available full function CPU on a chip, released in 1971
• 500×10³: Colossus computer vacuum tube cryptanalytic supercomputer, 1943

• 1×10⁶: computing power of the Motorola 68000 commercial computer introduced in 1979.^{[citation needed]}
• 1.2×10⁶: IBM 7030 "Stretch" transistorized supercomputer, 1961
• 5×10⁶: CDC 6600, first commercially successful supercomputer, 1964^[2]
• 11×10⁶: Intel i386 microprocessor at 33 MHz, 1985
• 14×10⁶: CDC 7600 supercomputer, 1967^[2]
• 40×10⁶: i486 microprocessor at 50 MHz, 1989
• 86×10⁶: Cray 1 supercomputer, 1978^[2]
• 100×10⁶: Pentium (i586) microprocessor, 1993
• 400×10⁶: Cray X-MP, 1982^[2]

• 1×10⁹: ILLIAC IV 1972 supercomputer does first computational fluid dynamics problems
• 1.4×10⁹:
  Intel Pentium III
  microprocessor, 1999
• 1.6×10⁹: PowerVR MBX Lite 3D GPU on iPhone 1, 2007
• 8×10⁹: PowerVR SGX535 GPU on iPad 1, 2010
• 136×10⁹: PowerVR GXA6450 GPU on iPhone 6 and iPhone SE, 2014
• 148×10⁹: Intel Core i7-980X Extreme Edition commercial computing 2010^[4]

• 1.34×10¹²:
  Intel ASCI Red
  1997 supercomputer
• 1.344×10¹² GeForce GTX 480 in 2010 from Nvidia at its peak performance
• 2.15×10¹²:
  A17 Pro
  processor
• 4.64×10¹²:
  AMD
  (under ATI branding) at its peak performance
• 5.152×10¹²: S2050/S2070 1U GPU Computing System from Nvidia
• 11.3×10¹²: GeForce GTX 1080 Ti in 2017
• 13.7×10¹²:
  Radeon RX Vega 64
  in 2017
• 15.0×10¹²: Nvidia Titan V in 2017
• 80×10¹²:
  IBM Watson^[5]
• 170×10¹²:
  Nvidia DGX-1 The initial Pascal based DGX-1 delivered 170 teraflops of half precision processing.^[6]
• 478.2×10¹² IBM
  BlueGene/L
  2007 Supercomputer
• 960×10¹²
  teraflops.^[7]

• 1.026×10¹⁵:
  IBM Roadrunner
  2009 Supercomputer
• 1.32×10¹⁵:
  Nvidia GeForce 40 series' RTX 4090 consumer graphics card achieves 1.32 petaflops in AI applications, October 2022^[8]
• 2×10¹⁵:
  Nvidia DGX-2 a 2 Petaflop Machine Learning system (the newer DGX A100
  has 5 Petaflop performance)
• 11.5×10¹⁵:
  TPU pod containing 64 second-generation TPUs, May 2017^[9]
• 17.17×10¹⁵:
  IBM Sequoia's LINPACK performance, June 2013^[10]
• 20×10¹⁵: roughly the hardware-equivalent of the human brain according to Ray Kurzweil. Published in his 1999 book: The Age of Spiritual Machines: When Computers Exceed Human Intelligence^[11]
• 33.86×10¹⁵: Tianhe-2's LINPACK performance, June 2013^[10]
• 36.8×10¹⁵: 2001 estimate of computational power required to simulate a human brain in real time.^[12]
• 93.01×10¹⁵: Sunway TaihuLight's LINPACK performance, June 2016^[13]
• 143.5×10¹⁵: Summit's LINPACK performance, November 2018^[14]

• 1×10¹⁸: Fugaku 2020 Japanese supercomputer in single precision mode^[15]
• 1.1x10¹⁸: Frontier 2022 U.S. supercomputer
• 1.88×10¹⁸: U.S. Summit achieves a peak throughput of this many operations per second, whilst analysing genomic data using a mixture of numerical precisions.^[16]
• 2.43×10¹⁸: Folding@home distributed computing system during COVID-19 pandemic response^[17]
• 1.72×10¹⁸: operations per second of El Capitan, the fastest non-distributed supercomputer in the world as of November 2024^[18]

• 1×10²¹: Accurate global weather estimation on the scale of approximately 2 weeks.^[19] Assuming Moore's law remains applicable, such systems may be feasible around 2035.^[20]

A zettascale computer system could generate more single floating point data in one second than was stored by any digital means on Earth in the first quarter of 2011.^{[citation needed]}

• 1.12×10³⁶: Estimated computational power of a Matrioshka brain, assuming 1.87×10²⁶ watt power produced by solar panels and 6 GFLOPS/watt efficiency.^[21]
• 4×10⁴⁸: Estimated computational power of a Matrioshka brain whose power source is the
  Carnot engine
• 5×10⁵⁸: Estimated power of a galaxy equivalent in luminosity to the Milky Way converted into Matrioshka brains.

• Futures studies – study of possible, probable, and preferable futures, including making projections of future technological advances
• History of computing hardware (1960s–present)
• List of emerging technologies – new fields of technology, typically on the cutting edge. Examples include genetics, robotics, and nanotechnology (GNR)
  • Artificial intelligence – computer mental abilities, especially those that previously belonged only to humans, such as speech recognition, natural language generation, etc.
    • History of artificial intelligence (AI)
    • Strong AI – hypothetical AI as smart as a human
  • Quantum computing
    • Timeline of quantum computing and communication
• Moore's law – observation (not actually a law) that, over the history of computing hardware, the number of transistors on integrated circuits doubles approximately every two years. The law is named after Intel co-founder Gordon Moore, who described the trend in his 1965 paper.^[22]
• Supercomputer
  • History of supercomputing
• Superintelligence
• Timeline of computing
• Technological singularity – hypothetical point in the future when computer capacity rivals that of a human brain, enabling the development of strong AI — artificial intelligence at least as smart as a human
  • Raymond Kurzweil
    dealing with the progression and projections of development of computer capabilities, including beyond human levels of performance
• TOP500 – list of the 500 most powerful (non-distributed) computer systems in the world