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OpenAI O3-Mini

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Re: OpenAI O3-Mini

#281

Post by margalabargala »

Euphorbium wrote: post #213
sho_hn wrote: post #12

Earlier quoted context omitted.

I think OpenAI really needs to rethink its product naming, especially now that they have a portfolio where there's no such clear hierarchy, but they have a place along different axis (speed, cost, reasoning, capabilities, etc). Your summary attempt e.g. also misses o3-mini vs o3-mini-high. Lots of trade-ofs.

They can still do models o3o, oo3 and 3oo. Mini-o3o-high, not to be confused with mini-O3o-high (the first o is capital).

They should just start encoding the model ID in trinary using o, O, and 0.

Model 00oOo is better than Model 0OoO0!

Re: OpenAI O3-Mini

#282

Post by [deleted] »

brookst wrote: post #249
jen729w wrote: post #211

> Testers preferred o3-mini's responses to o1-mini 56% of the time I hope by this they don't mean me, when I'm asked 'which of these two responses do you prefer'. They're both 2,000 words, and I asked a question because I have something to do. I'm not reading them both ; I'm usually just selecting the one that answered first. That prompt is pointless. Perhaps as evidenced by the essentially 50% response rate: it's a…

Those prompts are so irritating and so frequent that I’ve taken to just quickly picking whichever one looks worse at a cursory glance. I’m paying them, they shouldn’t expect high quality work from me.

[deleted]

Re: OpenAI O3-Mini

#283

Post by rsanek »

othello wrote: post #201
chad1n wrote: post #196

I think that OpenAI should reduce the prices even further to be competitive with Qwen or Deepseek. There are a lot of vendors offering Deepseek R1 for $2-2.5 per 1 million tokens output.

Would you have specific recommendations of such vendors?

If you want reliable service you're going to pay more around $7~8 per million tokens. Sister commenters mention providers that are considered unstable https://openrouter.ai/deepseek/deepseek-r1

Re: OpenAI O3-Mini

#284

Post by margalabargala »

scarface_74 wrote: post #272

This took 1:53 in o3-mini https://chatgpt.com/share/679d310d-6064-8010-ba78-6bd5ed3360... The 4o model without using the Python tool https://chatgpt.com/share/679d32bd-9ba8-8010-8f75-2f26a792e0... Trying to get accurate results with the paid version of 4o with the Python interpreter. https://chatgpt.com/share/679d31f3-21d4-8010-9932-7ecadd0b87... The share link doesn’t show the output for some reason. But it did work…

The 4o model's output is blatantly wrong. I'm not going to look up if it's the order or the ages that are incorrect, but:

36. Abraham Lincoln – 52 years, 20 days (1861)

37. James Garfield – 49 years, 105 days (1881)

38. Lyndon B. Johnson – 55 years, 87 days (1963)

Basically everything after #15 in the list is scrambled.

Re: OpenAI O3-Mini

#285

Post by withinboredom »

jsk2600 wrote: post #223
sss111 wrote: post #41

Earlier quoted context omitted.

Deepseek V3 is equivalent to 4o. Deepseek R1 is equivalent to o1 (if not better) I think someone should just build an AI model comparing website at this point. Include all benchmarks and pricing

This one is good: https://artificialanalysis.ai/

Looks like this only compares commercial models, and not the ones I can download and actually run locally.

Re: OpenAI O3-Mini

#286

Post by WiSaGaN »

GaggiX wrote: post #204
Oras wrote: post #90

200k context window $1.1/m for input $4.4/m for output I assume thinking medium and hard would consume more tokens. I feel the timing is bad for this release especially when deepseek R1 is still peaking. People will compare and might get disappointed with this model.

The model looks quite a bit better in the benchmarks so unless they overfit the model on them it would probably perform better than deepseek.

My vibe question checking suggests otherwise. Even o3-mini-high is not as good as r1, even though it's faster than r1. Considering o3-mini is more expensive per token. It's not clear o3-mini-high is cheaper than r1 either even r1 probably consumes more token per answer.

Re: OpenAI O3-Mini

#287

Post by mrbungie »

sumedh wrote: post #273
mrbungie wrote: post #254

Earlier quoted context omitted.

That's like making a second reading and appealing to authority. The naming is bad. Other people already said it you can "google" stuff, you can "deepseek" something, but to "chatgpt" sounds weird. The model naming is even weirder, like, did they really avoid o2 because of oxigen?

> but to "chatgpt" sounds weird. People just say it differently, they say "ask chatgpt"

Obviously they do. That's the whole point.

Re: OpenAI O3-Mini

#288

Post by apparent »

brookst wrote: post #249
jen729w wrote: post #211

> Testers preferred o3-mini's responses to o1-mini 56% of the time I hope by this they don't mean me, when I'm asked 'which of these two responses do you prefer'. They're both 2,000 words, and I asked a question because I have something to do. I'm not reading them both ; I'm usually just selecting the one that answered first. That prompt is pointless. Perhaps as evidenced by the essentially 50% response rate: it's a…

Those prompts are so irritating and so frequent that I’ve taken to just quickly picking whichever one looks worse at a cursory glance. I’m paying them, they shouldn’t expect high quality work from me.

Have you considered the possibility that your feedback is used to choose what type of response to give to you specifically in the future?

I would not consider purposely giving inaccurate feedback for this reason alone.

Re: OpenAI O3-Mini

#289

Post by simonw »

I just pushed a new release of my LLM CLI tool with support for the new model and the reasoning_effort option: https://llm.datasette.io/en/stable/changelog.html#v0-21

Example usage:

  llm -m o3-mini 'write a poem about a pirate and a walrus' \
    -o reasoning_effort high
Output (comparing that with the default reasoning effort): https://github.com/simonw/llm/issues/728#issuecomment-262832...

(If anyone has a better demo prompt I'd love to hear about it)

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