model
Model reported as deterministic (3 of 3 identical responses) with code_first unknown rates of 0.94 in English and 0.54 in Russian prompts.
No evidence-backed relationships are recorded.
A dev.to post scores ten coding models on five real tasks and divides by price. The method is cheap to copy; the vendor plumbing it recommends deserves more scrutiny than the arithmetic.
Reality
Per-token prices fell about 200x since GPT-4's launch while US enterprise AI spend tripled to $37 billion. Tokenizer variance, reasoning tokens and tier discounts are where the bill diverges.
Reality
Prompt cache is scoped per upstream endpoint, so round-robin routing turns every agent turn into a full-price cache miss. One gateway writeup puts the sticky-routing saving at 50-70%.
Reality
Two Nvidia workstations behind a bar in Zhongguancun self-host DeepSeek V4 Flash and hand out inference like bar snacks. Read it as a pricing signal, not a novelty.
Reality
One engineer's home lab tally: $1,400 a month for two A100s running 40% idle, against open-weight models he measured inside noise of GPT-4o. The break-even is real, and it sits high.
Reality
Composio ran the leaderboard-topping model through 240 agent runs against live Gmail, GitHub and Slack tools, and 129 passed. Harness choice moved the outcome more than price did.
Reality
A verify-on-read experiment rerun across 14 live models on a fingerprinted 50-fact set found false-accept rates up to 0.38, and run-to-run noise wide enough to swallow a prompt fix.
Reality