Frankly, I don’t understand how OAI remain solvent. They’re eating a lot of shit in their “undercut the competition to take over the market” phase. But hey, if they’re giving it away, sure, I’ll take it.
The only reason they’re still around is the massive, huge amounts of cash they’re given every couple months, which goes right into the furnace. It’s just a matter of time until they implode in spectacular fashion. We’re at the point right now where we can take advantage of VC-funded free shit, like how Uber rides were way cheap at the beginning. Difference is, there’s still no path to profitability for OAI and there never will be.
Opus is heavily throttled outside enterprise tiers. I was regularly blowing through weekly usage limits by Tuesday using Opus. 5.3 on the higher thinking profiles match or exceed Opus capabilities, and I have yet to hit a single limitation.
If I need to process via API I will run tests against Anthropic Haiku or Sonnet before trying Gpt5-mini, If I need to use 5.3, and what I’m doing isn’t time critical I’ll use batch processing. Smaller token batches complete very quickly, often in under 2 hours. And at a 50% discount, provides serious cost savings.
It’s very content specific, what are you processing with the API?
One of my little side projects right now is translating Russian fiction, specifically a genre over there called ‘boyar-anime’ which is essentially fantasy set in imperial russia. I do most my heavy translation using Anthropic Haiku which is very cheap and unlike the higher end models it tends to dumb down some of the more complex parts of Imperial Russian aristocracy so it’s more in line with similar fiction over here. When I take the source book, I chunk it down into small segments that I translate individually so I don’t get context bleed, then I mechanically process to find anything that didn’t translate very well. I combine roughly 40 of these weirdly translated segments into a jsonl file and submit the file through the API. OpenAI Batch API can accept up to 900k tokens, but you’ll wait close to 11 hours for something that large. 40 segments is around 30k tokens and that usually processes in a few mins to an hour depending.
The jsonl file is essentially made up of smaller json blocks
{"custom_id":"SEGMENT-NUM","method":"POST","url":"/v1/responses","body":{"model":"gpt-5.3","input":[{"role":"system","content":[{"type":"input_text","text":"You are a meticulous English language proofreader."}]},{"role":"user","content":[{"type":"input_text","text":"PROMPT - SUBMITTED SEGMENT"}]}],"max_output_tokens":8192}}
I then setup polling to check back with the API every few mins, when the submitted queries are completed, I send more automatically until everything has been processed.
deleted by creator
The only reason they’re still around is the massive, huge amounts of cash they’re given every couple months, which goes right into the furnace. It’s just a matter of time until they implode in spectacular fashion. We’re at the point right now where we can take advantage of VC-funded free shit, like how Uber rides were way cheap at the beginning. Difference is, there’s still no path to profitability for OAI and there never will be.
deleted by creator
Opus is heavily throttled outside enterprise tiers. I was regularly blowing through weekly usage limits by Tuesday using Opus. 5.3 on the higher thinking profiles match or exceed Opus capabilities, and I have yet to hit a single limitation.
If I need to process via API I will run tests against Anthropic Haiku or Sonnet before trying Gpt5-mini, If I need to use 5.3, and what I’m doing isn’t time critical I’ll use batch processing. Smaller token batches complete very quickly, often in under 2 hours. And at a 50% discount, provides serious cost savings.
deleted by creator
It’s very content specific, what are you processing with the API?
One of my little side projects right now is translating Russian fiction, specifically a genre over there called ‘boyar-anime’ which is essentially fantasy set in imperial russia. I do most my heavy translation using Anthropic Haiku which is very cheap and unlike the higher end models it tends to dumb down some of the more complex parts of Imperial Russian aristocracy so it’s more in line with similar fiction over here. When I take the source book, I chunk it down into small segments that I translate individually so I don’t get context bleed, then I mechanically process to find anything that didn’t translate very well. I combine roughly 40 of these weirdly translated segments into a jsonl file and submit the file through the API. OpenAI Batch API can accept up to 900k tokens, but you’ll wait close to 11 hours for something that large. 40 segments is around 30k tokens and that usually processes in a few mins to an hour depending.
The jsonl file is essentially made up of smaller json blocks
{ "custom_id": "SEGMENT-NUM", "method": "POST", "url": "/v1/responses", "body": { "model": "gpt-5.3", "input": [ { "role": "system", "content": [ { "type": "input_text", "text": "You are a meticulous English language proofreader." } ] }, { "role": "user", "content": [ { "type": "input_text", "text": "PROMPT - SUBMITTED SEGMENT" } ] } ], "max_output_tokens": 8192 } }I then setup polling to check back with the API every few mins, when the submitted queries are completed, I send more automatically until everything has been processed.