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In the pico8 console, do load #prof, then edit the third tab with some code:

  local _=sqrt(x)   -- code to measure
  local _=x^0.5     -- some other code to measure
end,{ locals={9} }) -- "locals" (optional) are passed in as args

Run the cart: it will tell you exactly how many cycles it takes to run each code snippet.

what is this?

The wiki is helpful to look up CPU costs for various bits of code, but I often prefer to directly compare two larger snippets of code against each other. (plus, the wiki can get out of date sometimes)

For the curious, here's how I'm able to calculate exact cycle counts
(essentially, I run the code many times and compare it against running nothing many times, using stat(1) and stat(2) for timing)

-- slightly simplified from the version in the cart
function profile_one(func)
  local n = 0x1000

  -- we want to type
  --   local m = 0x80_0000/n
  -- but 8𝘮𝘩z is too large a number to handle in pico-8,
  -- so we do (0x80_0000>>16)/(n>>16) instead
  -- (n is always an integer, so n>>16 won't lose any bits)
  local m = 0x80/(n>>16)

  -- given three timestamps (pre-calibration, middle, post-measurement),
  --   calculate how many more 𝘤𝘱𝘶 cycles func() took compared to noop()
  -- derivation:
  --   𝘵 := ((t2-t1)-(t1-t0))/n (frames)
  --     this is the extra time for each func call, compared to noop
  --     this is measured in #-of-frames (at 30fps) -- it will be a small fraction for most ops
  --   𝘧 := 1/30 (seconds/frame)
  --     this is just the framerate that the tests run at, not the framerate of your game
  --     can get this programmatically with stat(8) if you really wanted to
  --   𝘮 := 256*256*128 = 8𝘮𝘩z (cycles/second)
  --     (𝘱𝘪𝘤𝘰-8 runs at 8𝘮𝘩z; see https://www.lexaloffle.com/bbs/?tid=37695)
  --   cycles := 𝘵 frames * 𝘧 seconds/frame * 𝘮 cycles/second
  -- optimization / working around pico-8's fixed point numbers:
  --   𝘵2 := 𝘵*n = (t2-t1)-(t1-t0)
  --   𝘮2 := 𝘮/n := m (e.g. when n is 0x1000, m is 0x800)
  --   cycles := 𝘵2*𝘮2*𝘧
  local function cycles(t0,t1,t2) return ((t2-t1)-(t1-t0))*m/30 end

  local noop=function() end -- this must be local, because func is local
  local atot,asys=stat(1),stat(2)
  for i=1,n do noop() end -- calibrate
  local btot,bsys=stat(1),stat(2)
  for i=1,n do func() end -- measure
  local ctot,csys=stat(1),stat(2)

  -- gather results
  local tot=cycles(atot,btot,ctot)
  local sys=cycles(asys,bsys,csys)
  return {

how do I use it?

Here's an older demo to wow you:

Cart #cyclecounter-2 | 2022-01-16 | Code ▽ | Embed ▽ | License: CC4-BY-NC-SA

This is neat but impractical; for everyday usage, you'll want to load #prof and edit the last tab.

The cart comes with detailed instructions, reproduced here for your convenience:

 ★ usage guide ★ 

웃: i have two code snippets;
    which one is faster?

🐱: edit tab 2 with your
    snippets, then run.
    it will tell you precisely
    how much cpu it takes to
    run each snippet.

    the results are also copied
    to your clipboard.
    (for ease of use, consider
    integrating this cart into
    your own cart during dev)

웃: what do the numbers mean?

🐱: the cpu cost is reported
    as lua and system cycle
    counts. look up stat(1)
    and stat(2) for more info.

    if you're not sure, just
    look at the sum -- lower
    is faster (better)

웃: why "{locals={3,5}}"
    do in the example?

🐱: accessing local variables
    is faster than global vars.

    /!\     /!\     /!\     /!\
    "local" values outside
    the current scope are also
    slower to access!
    /!\     /!\     /!\     /!\

    so if the scenario you're
    trying to test involves
    local variables, simulate
    this by passing them in:

        local _=sqrt(a)
      end,{ locals={9} })

    note: you can profile many
    functions at once, or just
    one. also, passing options
    at the end isn't required:


웃: can i do "prof(myfunc)"?

🐱: no, this will give wrong
    results! always use inline

        -- code for myfunc here

    as an example, "prof(sin)"
    reports "-2" -- wrong! but
    correctly reports "4"

    (see the notes at the start
    of the next tab for a brief
    technical explanation)

 ★ alternate method ★

this cart is based on code by

if you do this method, be very
careful with local/global vars.
it's very easy to accidentally
measure the wrong thing.

here's an example of how to
measure cycles (ignoring this
cart and using the old method)

  local a=11.2 -- locals

  local n=1024
  local tot1,sys1=stat(1),stat(2)
  for i=1,n do  end -- calibrate
  local tot2,sys2=stat(1),stat(2)
  for i=1,n do local _=sqrt(a) end -- measure
  local tot3,sys3=stat(1),stat(2)

  function cyc(t0,t1,t2) return ((t2-t1)-(t1-t0))*128/n*256/stat(8)*256 end
  local lua = cyc(tot1-sys1,tot2-sys2,tot3-sys3)
  local sys = cyc(sys1,sys2,sys3)
  print(lua.."+"..sys.."="..(lua+sys).." (lua+sys)")

run this once, see the results,
then change the "measure" line
to some other code you want
to measure.

misc results

(these may be out of date now, but they were interesting)

poke4 v. memcopy

  profile("memcpy     ", function() memcpy(0,0x200,64)       end)
  profile("poke4/poke4", function() poke4(0,peek4(0x200,16)) end)

> memcpy : 7 +64 = 71 (lua+sys)
> poke4/poke4 : 7 +60 = 67 (lua+sys)

Copying 64 bytes of memory is very slightly faster if you use poke4 instead of memcpy -- interesting!
(iirc this is true for other data sizes... find out for yourself for sure by downloading and running the cart!)

edit: this has changed in 0.2.4b! the memcpy in this example now takes 7 +32 cycles

constant folding

I thought lua code was not optimized by the lua compiler/JIT at all, but it turns out there are some very specific optimizations it will do.

  profile("     +", function() return 2+2 end)
  profile("   +++", function() return 2+2+2+2+2+2+2+2 end)

These functions both take a single cycle! That long addition gets optimized by lua, apparently. @luchak found these explanations:

> Since Lua often compiles source code into byte code on the fly, it is designed to be a fast single-pass compiler. It does do some constant folding

A No Frills Introduction to Lua 5.1 VM Instructions (book)
> As of Lua 5.1, the parser and code generator can perform limited constant expression folding or evaluation. Constant folding only works for binary arithmetic operators and the unary minus operator (UNM, which will be covered next.) There is no equivalent optimization for relational, boolean or string operators.

constant folding...?

One further test case:

  profile("tail add x3", function() local a=2 return 2+2+2+2+2+2+2+a end)
  profile("head add x3", function() local a=2 return a+2+2+2+2+2+2+2 end)

> tail add x3 : 2 + 0 = 2 (lua+sys)
> head add x3 : 8 + 0 = 8 (lua+sys)

These cost different amounts! Constant-folding only seems to work at the start of expressions. (This is all highly impractical code anyway, but it's fun to dig in and figure out this sort of thing)


Cart by pancelor.

Thanks to @samhocevar for the initial snippet that I used as a basis for this profiler!

Thanks to @freds72 and @luchak for discussing an earlier version of this with me!

Thanks to thisismypassword for updating the wiki's CPU page!



  • simpler BBS post, friendlier cart instructions


  • rewrite; recommend using load #prof instead now


  • added: press X to copy to clipboard
  • added: can pass args; e.g. profile("lerp", lerp, {args={1,4,0.3}})


  • intial release
P#104795 2022-01-11 03:31 ( Edited 2023-03-13 09:35)


the profiler is missing an input variable somehow - the current pattern forces declaration of a local (or global) to mimic real life usage

qol request: copy results to clipboard

P#105134 2022-01-15 12:57 ( Edited 2022-01-15 12:59)

good points -- added! passing input variables is slightly awkward, but it's at least possible now

P#105168 2022-01-16 06:35

I've updated the description + cart (load #prof) to be a lot clearer

P#127068 2023-03-13 09:34

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