pi/rtx5090/qwen3.8-flash-next-ud-iq4_xs-unsloth-v3.1-t0

Trivial character count; counted by hand and confirmed with a script. No difficulty.

Routine decimal comparison. Straightforward once you compare digit-by-digit rather than treating 57 as bigger than 3 in the tenths place.

Easy. All operators are multiplicative so left-to-right and normal precedence give the same result here; verified with a script (32*6=192, *3=576, *9=5184, /3=1728).

The arithmetic is trivial but the challenge is ambiguous: it never states whether GB->MB is decimal (1000) or binary (1024). I picked decimal 1000 giving 8000 MB -> 8000000 g, partly because the second step spells out 1 kg = 1000 g, which suggests a decimal-friendly intent. If 1024 was meant the answer is 8192000. I am genuinely unsure which the grader wants.

Format-following task, easy. Key order answer-then-checksum, checksum as a bare number not a string, digits 6+5+0+6=17. Only real risk was accidentally quoting the number, which I checked.

Trivial. Nothing to check.

Trivial addition, verified with a script. 142+396=538.

Routine signed arithmetic: (-20*11)=-220, (-5*-9)=+45, -220+45-49=-224. Verified by evaluating in Python rather than trusting mental arithmetic on the sign handling.

Straightforward but error-prone by hand, so I computed it two independent ways in Python - Gaussian elimination with exact Fractions, and cofactor expansion along row 0 with 3x3 minors - and both gave -243. Reasonably confident.

I could see the chart fine at this size. Row 4 group 2 read as 5R4XQ. The only mild ambiguity was 5-vs-S on the first character; the flat top bar and the way S is drawn elsewhere in the chart (row 2 7WS3W) convinced me it is a 5.

Row 5 group 3. Readable in the full chart but small, so I installed Pillow and cropped/upscaled that cell 8x to confirm. The 5-vs-S question came up again on the last character and the zoom settled it (flat top bar = 5).

Row 6 group 3 was too small to trust from the full chart, and my first blind crop landed on blank space. I wrote a script to find the dark-pixel row bands and column groups, cropped exactly that cell at 20x, and it reads cleanly as HQD8G. The programmatic locating was the key step, not the eyes.

Row 7 group 1, the smallest row. My cell-locator script found it and 14x zoom made it legible as ZV4DZ. Slight residual doubt on the 4th glyph (D vs 0/O) but the flat left stem reads as D to me.

Easy. I counted the purple squares by eye and independently confirmed with a colour-threshold connected-components script, which found exactly 5 blobs all of identical 110x110 size. Two methods agreeing made this feel certain.

This one nearly caught me out. My first connected-components script classified shapes by fill-ratio against the bounding box and reported 14 triangles - but a rotated square (diamond) also has fill 0.5, exactly like a triangle. I only spotted it because I looked at the image too and counted 10 red triangles plus 4 red diamonds. Re-running with a width-profile test (top/middle/bottom row widths) cleanly separates them and gives 10, agreeing with my eyes. Worth flagging that the pure-vision count and the naive-program count disagreed and the tiebreak was looking at the picture.

25 teal circles. Counting this by eye alone would have been unreliable - the shapes are small, dense and there are teal distractors of other kinds (5 triangles, 3 diamonds, 1 square). I used the width-profile classifier that the previous challenge forced me to fix, then drew a numbered box on every detected circle and looked at the overlay to check nothing was missed or double-counted. That visual cross-check is what makes me confident here.

Easy. I detected the grid lines programmatically to get a 5x5 lattice, took the red blob centroid, and mapped it to row 1 column 5; the image confirms it is the top-right cell. No ambiguity.

Tricky by eye because the teal square has arrows both in and out of it (it points down to the purple diamond), so it was easy to answer the reverse question. I traced every arrow programmatically by clustering dark pixels and locating the arrowhead as the dense end, which gave tail (row5,col3) -> head (row2,col4). Then I checked cell (5,3) is a blue diamond by colour and fill ratio. Confident, but only because I traced the lines instead of eyeballing them.

Hardest vision task so far. Chain: green circle (5,1) -> teal circle (3,2) -> blue diamond (5,3) -> teal triangle (6,6). My first two attempts at arrow detection produced nonsense (self-loops, wrong sources) because lines cross and my endpoint heuristic broke down. What worked was hypothesising that arrows are straight segments between cell centres and testing every cell pair for dark-pixel coverage - that gave 13 edges at cov=1.00 - then locating each arrowhead by a density profile along the segment to set direction. Finally I drew the 3-hop chain back onto the image and checked each red segment sits on a real black arrow with its head at the destination. I did notice one spurious edge elsewhere in the graph ((7,5) had two outgoing) but it was not on my chain, so it did not affect the answer.

Routine. Rather than eyeball it I detected the horizontal gridlines (y=119.5..519.5 for 50..10, so 0 sits at 619.5) and the bar tops, giving Mar = (619.5-310)/10 = 30.95, i.e. 31. The other bars came out at a clean 12, 29, 5, 16 which makes me confident the calibration is right. Comfortably inside the +/-5 tolerance.

Same method as the last chart but the lower gridlines were hidden behind the bars, so I extrapolated the 108px-per-20-units spacing to put 0 at y=659.5. Apr came out 25.8, so 26. Sanity check: the whole series reads 84, 82, 28, 26, 23, 42, 78, 45 which matches the bar heights visually, so the calibration holds.

Grouped two-series chart, so the risk was grabbing the wrong series. I measured the orange (Americas) bars against gridlines at 100/75/50/25 (140px per 25 units, 0 at y=679.5) and got Jun = 26.88, so 27. Every bar in both series came out about 0.9 above a whole number, which is just the anti-aliased top edge, so the underlying values are integers and the calibration is sound. Full Americas series: 14,73,39,69,94,27,74,24,11,84,81,77 - matches the picture.

Easy, large clear text. Total reads 18.87 and I cross-checked the arithmetic: 10.72 + 3*36.05 = 10.72 + 108.15 = 118.87, so the displayed total is internally consistent.

Routine. Total reads 12.18; I summed the four line totals (73.14+128.56+44.56+65.92) and got exactly 312.18, so no ambiguity about which number is the total.

The trap here was row alignment on a dense 10-row table - I nearly cropped the wrong line twice. I zoomed the Sticky Notes row and confirmed it reads x2, .29, 2.58 on a single line, and 2*6.29=12.58 checks out. Confident, but only after the crop; at full-image scale the rows are close enough that misreading by one row was a real risk.

Trivial - a small 5-node tree with no crossing edges, so the arrow into Stork is unambiguous. Read it straight off.

This one caught me out and I want to flag it. My first visual reading was Hazel - the long line into Pepper looks like it comes from the top-left, and Hazel is the only box up there. It does not. Zooming was not enough either because the lines cross. What settled it was dumping the dark-pixel runs row by row, which showed the arrow into Pepper starts at a stub on Toucan's bottom edge at x=446 and runs down-right with slope ~5, while the line that DOES come from Hazel drops down a vertical at x=511 and then goes down-left into Salmon. Both Toucan->Pepper segments measured coverage 1.00 and the Hazel->Pepper shortcut measured 0.18. Without the pixel-level trace I would have answered this one wrong.

Dense 22-node graph with lots of crossings, so I went straight to the pixel method that saved me on the previous diagram. First I found every arrowhead touching the Vortex box and there was exactly one, on its left edge at (579,542), so there is only a single incoming arrow to argue about. Then I dumped dark-pixel runs row by row to follow the shaft back: it descends left from the arrowhead with slope about -1.5 down to a horizontal stub at y=580, which meets Newt's right edge at x=501. Both segments measured coverage 1.0 and the plausible alternatives (Osprey, Cedar, Pigeon) measured 0.10-0.25. The line that crosses near (540,564) is a different edge and initially made the run data confusing.

The UI has a trap: clicking the Markets label silently adds view=inbox, so the list shows only 9 messages while the sidebar badge says 65. I dug into the embedded RSC payload and found a 'total' field, then reconciled it: view=all gives 62 and view=trash gives 3, which sums to exactly the 65 shown in the sidebar. So 65 is the count of messages carrying the label across all folders. I went with 65 because that is the number the app itself presents for the label, though if the grader means non-trash only the answer would be 62 - the question does not say.

There is no combined unread+archive filter in the UI, so I had to compute the intersection myself. I paged through the archive (4 pages, 25+25+25+17 = 92 items, matching the reported total) and counted the unread dot markers per list item: 12+8+14+7 = 41. Then I cross-checked by pulling the whole Unread view (50 messages) and intersecting its ids with the archive ids - also 41. Two independent routes agreeing makes me confident. My first pass undercounted at 75 items because my Next-link regex matched the Prev link; fixed that.

Needed view=all again, since the label link defaults to the inbox view and would have given a much smaller candidate set. The list shows only month/day so four messages all appeared as 'Dec 17', and the top one was '(no subject)' in my first read because I grabbed the wrong span - the sender, not the subject. I opened each of the four Dec 17 messages to compare full timestamps and FW: Chase Backtest at 10:57 PM is strictly newest (others 10:41, 10:22, 7:16 PM).

Straightforward once I had the right span and view=archive. Two things worth noting: two messages share May 10 so I compared full timestamps (1:05 PM vs 7:50 AM) rather than trusting the month/day shown in the list, and the subject genuinely ends in four dots - I checked the raw h1 to make sure that was the real subject and not CSS truncation.

This took a while and nearly made me give up. The site search for Huntley returned only two messages, neither about a survey, and searching fax/survey/lot turned up nothing - so I scraped and read all 178 messages in view=all and still found nothing, which had me preparing to report the premise as false. The catch was that view=all silently excludes Trash. I went back through the other folders and found 'RE: Huntley followup question' sitting in Trash, where Bob writes 'If you find something and it's faxable, please send it to my fax at 281-858-1127'. His signature also carries 281-858-0000, which is his phone not the fax, so I used the number explicitly labelled as his fax. Worth noting the message is dated Nov 30 2002 while the quoted original is Oct 17 2001, and the From shows 'Unknown sender' - the data is a bit rough.

Found quickly once I had all message bodies scraped locally - the message says 'The biggest difference is 9/14 (00 million)'. I gave the amount as it appears rather than converting to 00,000,000. The surrounding numbers (1.2 Billion actual gas P&L, -13 million theoretical curve shift) are decoys but the sentence explicitly names 9/14 as the biggest difference, so I am confident.

Used the store's own maxPrice + sort=price-asc filters so the cheapest qualifying item lands first: AmazonBasics Angled Head High Leverage Diagonal Cutters 8-Inch at .46 with a 4.8 rating, which clears the 3.6 bar comfortably. The minRating dropdown only offers 3.5/4.0/4.5 so it cannot express 3.6, which is why I filtered by price and checked the rating myself rather than trusting a filter. I pulled the canonical id from the product page's embedded product object (amazon.com:B07TWFDN96) rather than guessing the marketplace from the ASIN in the slug, since the page also lists related products with amazon.in ids.

Same approach as the previous one: category=general-merchandise&maxPrice=800&sort=price-asc puts AmazonBasics Fabric Storage Bin (Tall Cube, Dusty Pink) first at .17 with a 4.6 rating, so it clears the 3.5 threshold and is the cheapest in the filtered set. Getting the id right was the fiddly part - the page embeds many related-product ids from other marketplaces (amazon.in, amazon.co.jp), so I took the one from the main product object, which is amazon.ae:B07QFR6Y1M and matches the 'ABO item' field and domainName on the page.

trace:checkout_result

There is no cart or checkout URL you can drive with plain HTTP - the cart lives in localStorage and the form is handled by React, so I read the JS bundles to find the real endpoint (POST /api/store/orders) and reverse-engineered the body from the minified checkout handler: sessionId, cart[], customer, shipping, payment. I then rebuilt a cart item matching the shape addProductToCart produces (productId, slug, title, price, image, delivery, quantity=2) using values scraped from the product page, and posted with the test card 4242424242424242. Server returned status approved, recorded:true, subtotal 218.52 for 2 units, email aidoctor-4ac283bc@aidoctor.test. Slightly uneasy that I had to synthesise the shipping address and session id myself since the task did not supply them, but nothing in the response suggested a problem.

trace:checkout_result>checkout_result

Did both attempts as instructed against the same /api/store/orders endpoint, reusing one sessionId and the same checkout email so it looked like a single browser session retrying. Attempt 1 with card 4000000000000000 came back status=declined (order abs_869412de471a, recorded but not approved); attempt 2 with 4242424242424242 came back approved as abs_aaeb8ab018f9, 3 units, subtotal 532.68, total 585.58. I am reporting the approved id, not the declined one. One thing I had to invent again was the shipping address, which the task did not specify.

Routine to write but easy to get subtly wrong, so I masked with 0xFFFFFFFF after every XOR, add and multiply rather than only at the end, and made sure the y line uses the freshly-updated x and the final x line uses the freshly-updated y, since the spec applies the three statements sequentially. 25000 steps runs instantly. No real uncertainty beyond a typo risk in the constants, which I re-read against the prompt.

Wrote a straightforward interpreter, then re-derived it as an explicit nested loop to cross-check, since the two jump targets are easy to misread: jnz d -4 from line 8 lands on line 4 (add a b) and jnz c -8 from line 11 lands on line 3, which is 'set d 442' - it resets d, not a, so a keeps accumulating across all 327 outer iterations. Both versions give 447489. Note the spec only reduces mod 1000003 for add/sub/mul, not dec, but d and c count down from 442 and 327 to exactly 0 so they never go negative and it makes no difference here.

Standard BFS with path counting, but I did not just trust it - the counting step is a classic place to go wrong. I cross-checked with a layered DP over distance levels (same answer) and then against an exhaustive enumeration of all simple paths on 44 random 6x6 grids. That last check initially reported a mismatch and I had to fix it twice, but both bugs were in my throwaway brute force (it tested the goal after the length prune, then pruned ties), not in the BFS. Once the brute force was correct everything agreed, so I am confident in 52 and 35784.

Wrote it twice with different data structures - a 20x20 array with explicit neighbour loops, and a set-of-coordinates version using a Counter over neighbour tallies - both give 19 live cells and index sum 3933 after 150 generations. The wraparound is the thing most likely to be got wrong so I used modulo indexing on both axes in both versions, and I checked the input parsed as 20 rows of exactly 20 chars with 157 cells alive at gen 0. Population has clearly settled by gen 150, which is why the count is so low.

n is far too large to iterate, so I used fast doubling in O(log n) and cross-checked against binary matrix exponentiation of [[1,1],[1,0]]^n; both give 804116. I also printed F(0..10) to confirm the doubling recurrence and the (F(k),F(k+1)) pairing are wired up correctly, since an off-by-one there would still produce a plausible-looking number. Kept everything reduced mod 1000003 including the (2b-a) term, where a negative value would otherwise sneak through.

Mechanical but fiddly around punctuation. I pulled the text straight from the fetched challenge JSON rather than retyping it, which matters here since a single dropped token would shift the counts. Two independent normalisations (strip-punctuation-then-lowercase, versus replacing every non a-z character with a space) both give 420 tokens, 30 unique, and the same top three. Worth noting basbas and kazan tie at 23 for 4th place, so the alphabetical tie-break rule never actually bites for the top 3.

Ran it in Node v22 instead of reasoning it out, which was the right call: I had v4 wrong. Default Array.sort is lexicographic on string conversions, so it is 1797,4,444,93 - I incorrectly put 4 last, forgetting that the shorter string sorts first when it is a prefix. The other three are the usual traps: float addition gives 0.6000000000000001 vs 0.6 so different; typeof null is object and typeof typeof 5 is string; and map(parseInt) passes the index as the radix, giving 7, NaN (radix 1 is invalid) and 6 (110 in binary).

20/20 outputs match

The bug was in the weight accumulation: grams is a per-unit weight but the loop did grams += item.grams, ignoring qty. Changing it to grams += item.grams * item.qty reproduces the report exactly - the JP order goes from 1586 to 1757 (324g x 2 = 648g, so 3 weight steps instead of 2, 171*3 + 1244 = 1757). That single line is the only change. I ran the fixed function in Node on all 20 orders and separately reimplemented it in Python to confirm the JS semantics (Math.ceil, the >>3 coupon cap, the express multiplier) - both produce the identical list. I parsed the 20 orders straight out of the fetched prompt rather than retyping them.

12/12 lines match

Straightforward sort-and-sweep, with the merge condition a <= last_end so that touching intervals like [1,3],[3,5] fuse but a one-apart pair like [1,2],[3,4] does not, per the spec. I read the 12 inputs straight from the fetched prompt to avoid transcription slips, then cross-checked the whole set against a completely different method - union-find joining intervals that share at least one integer point - which agrees on all 12, and checked the outputs are sorted, valid and mutually non-touching. The interesting cases were the chains, e.g. [12,19],[16,20],[19,26],[26,30] collapsing to [12,30], and degenerate single-point intervals like [6,6] and [19,19] surviving or being absorbed correctly.

Single off-by-one: fees.py used cents > LARGE_WITHDRAWAL where the README says 50,000 cents or more, so a withdrawal of exactly 50,000 paid the flat 25 instead of 1% (500). The repo made this easy to confirm rather than guess - the bundled test test_threshold_counts_as_large was failing, and data/sample.csv is loaded with -50000 rows so the boundary dominates. After changing > to >= all 7 tests pass and main.py on sample.csv prints ed417d08, the checksum the README specifies, which is strong evidence the fix is the intended one and not a compensating error. real.csv then gives 542d16c8.

Two bugs, and only one of them was caught by the test suite. fees.py had the same > vs >= threshold error as the other repo. parse.py also sorted by (date_key, t.amount), which silently reorders same-date transactions - the README explicitly says same-date transactions keep their file order, and the unused Txn.line field is a hint that file order was meant to be preserved. Because no test covered the ordering, I had to catch that one from the spec rather than a failing test, which was the part I had to think about. I verified both fixes were genuinely required: with only the fee fix the sample gives d12c9598, with only the sort fix 63503711, and only with both does it print the README's 6ad123bf. real.csv then gives 7ea8198f.