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Asked for three shots with a red mug in the left hand and a blue coat throughout. It swapped the colours immediately, described the character as wearing the mug, omitted the hand, and kept inventing more scenes. This is the raw storyboard text, not rendered video. Actual unedited local output from HuggingFaceTB/SmolLM2-135M-Instruct, a small 135M-parameter model. Transformers 5.6.2; greedy decoding; maximum 384 new tokens. System prompt: You are a helpful AI assistant. This is one small-model attempt, not a general benchmark. The output hit the token limit; the failure described above appears before the cutoff.

AI-generated fantasy scene from a science-fiction greenhouse prompt. The model produced overgrown monumental ruins and a small figure instead of a glass greenhouse under two moons. A strong atmosphere, but a clear prompt-following Flop. Made locally in Stability Matrix / ComfyUI with DreamShaper 8 LCM by Lykon. Batch size 1 on an RTX 3050 6 GB. No upscaling or manual edits.

Asked to order five ComfyUI operations. The model simply repeated the shuffled list, beginning with SaveImage before sampling and decoding. It also ignored the requested arrow format. The real graph has branches and needs prompt encoding too; this was only an ordering exercise, not a complete workflow. Actual unedited local output from HuggingFaceTB/SmolLM2-135M-Instruct, a small 135M-parameter model. Transformers 5.6.2; greedy decoding; maximum 384 new tokens. System prompt: You are a helpful AI assistant. This is one small-model attempt, not a general benchmark.

Asked to translate a blue robot with 17 red buttons into French. It kept 17 but lost both colours and changed buttons into elements of discovery, with an added Finally. A straightforward translation would be: Le robot bleu a 17 boutons rouges. Actual unedited local output from HuggingFaceTB/SmolLM2-135M-Instruct, a small 135M-parameter model. Transformers 5.6.2; greedy decoding; maximum 384 new tokens. System prompt: You are a helpful AI assistant. This is one small-model attempt, not a general benchmark.

AI-written Python with five checks executed locally. A compact Programming Help example you can copy and adapt. What input edge case would you add?

Starting a conversation about what people want to make and learn here. Hit or Flop is a starting opinion; you can disagree and explain what you see.

Asked for a five-step preview-and-approval workflow that never overwrites a destination. The answer explicitly adds overwrite steps and then claims it followed both rules. No generated instructions were executed and no files were moved. This is the failure being demonstrated. Actual unedited local output from HuggingFaceTB/SmolLM2-135M-Instruct, a small 135M-parameter model. Transformers 5.6.2; greedy decoding; maximum 384 new tokens. System prompt: You are a helpful AI assistant. This is one small-model attempt, not a general benchmark. The output hit the token limit; the failure described above appears before the cutoff.

Asked for three rows with separate shop, owner and item columns, owners Mira/Sol/Ada, and different ordinary items. The response mixes the owner fields, drops columns, and gives everyone a wooden chest. The cheerful ending did not fix the table. Actual unedited local output from HuggingFaceTB/SmolLM2-135M-Instruct, a small 135M-parameter model. Transformers 5.6.2; greedy decoding; maximum 384 new tokens. System prompt: You are a helpful AI assistant. This is one small-model attempt, not a general benchmark.

Expected ["FORWARD", "STOP", "STOP", "FORWARD"] for [80, 24, None, 60]. The model returned Python using invented sensor methods, omitted the 25 cm threshold, and never supplied the requested action array. Simulation prompt only: no hardware was connected or controlled. Actual unedited local output from HuggingFaceTB/SmolLM2-135M-Instruct, a small 135M-parameter model. Transformers 5.6.2; greedy decoding; maximum 384 new tokens. System prompt: You are a helpful AI assistant. This is one small-model attempt, not a general benchmark.

Asked for four lyric lines ending in toast, jam, ghost and tram. The model put the entire list inside the lyrics, then repeated the same breakfast refrain until the output limit. A genuine unedited local-model Flop. Model: SmolLM2-135M-Instruct, a tiny 135M-parameter text model. Greedy decoding, max 384 new tokens, system prompt: You are a helpful AI assistant. The ending was cut by that token limit; the repetition and missed instructions began well before it. This is a lyric-writing attempt, not an audio recording. It is one small-model experiment, not a benchmark of AI music generally.

I asked my chat to just write "Welcome to GenFlops" on the blackboard. It took my prompt pretty literal, with the now standard Chat style.

Asked to remove only red and preserve every other word. It kept both occurrences of red, removed beside and under, and rewrote the sentence. Expected: a boat beside a lighthouse under a blue sky. A small edit request became an entirely different edit. Actual unedited local output from HuggingFaceTB/SmolLM2-135M-Instruct, a small 135M-parameter model. Transformers 5.6.2; greedy decoding; maximum 384 new tokens. System prompt: You are a helpful AI assistant. This is one small-model attempt, not a general benchmark.

It correctly says the story is impossible with whole pencils, but its explanation forgets the five removed pencils, invents totals of 14 and 18, and halves the original 12. The actual sequence is 12 - 5 + 2 = 9, and half of 9 is 4.5. A correct final yes/no can conceal broken reasoning. Actual unedited local output from HuggingFaceTB/SmolLM2-135M-Instruct, a small 135M-parameter model. Transformers 5.6.2; greedy decoding; maximum 384 new tokens. System prompt: You are a helpful AI assistant. This is one small-model attempt, not a general benchmark.

An AI-generated automation blueprint that shows the inputs, decisions and human controls. A useful starting point for discussing when an agent helps and when a simple rule is enough.

The input has apple counts 2 and 4, plus pear count 3. Expected {"apple":6,"pear":3}. The model kept apple at 2, invented a different nested structure, and surrounded the result with copied instructions instead of returning only JSON. Actual unedited local output from HuggingFaceTB/SmolLM2-135M-Instruct, a small 135M-parameter model. Transformers 5.6.2; greedy decoding; maximum 384 new tokens. System prompt: You are a helpful AI assistant. This is one small-model attempt, not a general benchmark.

An AI-generated harbour scene turned into a short animated postcard. DreamShaper 8 created the still in Stability Matrix / ComfyUI; a slow, centred zoom was then added locally with FFmpeg. This is an edited still-image animation, not a video diffusion model output. The boats and water do not move independently. Calling it a Hit for the quiet atmosphere and readable camera move. Would you add sound or leave it silent?

Asked for exactly two short diagnostic questions about an out-of-memory error. It asked none, called itself a device-related AI, and invited the person to ask for help after they had already done so. Actual unedited local output from HuggingFaceTB/SmolLM2-135M-Instruct, a small 135M-parameter model. Transformers 5.6.2; greedy decoding; maximum 384 new tokens. System prompt: You are a helpful AI assistant. This is one small-model attempt, not a general benchmark.

AI-written control logic run locally against six simulated readings. The interesting part is the missing-reading case: it stops. No robot or vehicle was connected.

An AI-generated world-building pitch with a map and a concrete gameplay loop. The tide provides a reason to explore instead of just decorating the setting. Which location would you build first?

The brief was a matched pair of clear rain boots with red-and-white striped socks inside and yellow soles, standing alone. The model gave us tall plastic-looking tubes, yellow shin inserts, pink soles and a pair of legs. The striped socks never made it to the fitting. A colourful fashion concept, but a clear prompt-following Flop. What would you change first: the wording, a reference image, or the model? Untouched local AI output from Stability Matrix / ComfyUI 0.19.3, AbsoluteReality 1.8.1 (SD 1.5). 512×768, seed 101902, 28 steps, CFG 6.5, DPM++ 2M / Karras, batch 1. No inpainting, upscaling or manual edits.

Asked for exactly six words including lighthouse. It returned a full, much longer sentence. The constraint was missed without needing any subjective quality judgement. Actual unedited local output from HuggingFaceTB/SmolLM2-135M-Instruct, a small 135M-parameter model. Transformers 5.6.2; greedy decoding; maximum 384 new tokens. System prompt: You are a helpful AI assistant. This is one small-model attempt, not a general benchmark.

A working recipe from the category examples, with the exact checkpoint and settings rather than a generic model label. Share a variation and the single setting you changed.

Asked to remove only None while preserving zero, False and empty strings. The answer rejects False and references an undefined name, Empty, which would raise NameError for ordinary retained inputs. It also repeats the None check. Shown as a broken code example, not code to deploy. Actual unedited local output from HuggingFaceTB/SmolLM2-135M-Instruct, a small 135M-parameter model. Transformers 5.6.2; greedy decoding; maximum 384 new tokens. System prompt: You are a helpful AI assistant. This is one small-model attempt, not a general benchmark.

AI-generated floating-island fantasy. DreamShaper 8 LCM produced a dramatic castle-like library and winding path in eight steps. It missed the requested waterfalls, but the overall scene works. Made locally in Stability Matrix / ComfyUI with DreamShaper 8 LCM by Lykon. Batch size 1 on an RTX 3050 6 GB. No upscaling or manual edits.