AmazingTurtle

seems like those subs are asking to become the new stackoverflow of reddit

whats the decode tok/s speed?

Whats the model total param size and will you release the weights? What does harness integration look like? Do you have an harness? Is it good at coding? What about tool calls? Do we have to wait a fixed amount of time for every step it takes?

If you have dyslexia and I know it, that brings it down to 20% of people. Combined with some other data, this is a pretty good factor to narrow it down to "who you are", right?

I tried it out today, was the new one: 1017.

so i did some apples to bananas comparison.

i let 4 different agents review the same dirty code base (200+ files changed, c++, game engine):

- deepseek v4.1 flash via deepseek API: took 20m to find one p1 issue that was relevant and a p2 issue that was irrelevant

- glm 5.3 flash NVFP4 via TP2 DGX Sparks: took 1h 5m to find a p3 documentation issue

- gpt 5.6 sol: took 5m30s for one p1 and one p2 issue. both relevant

- gpt 6.1 sol: took 4m30s for two p1 and one p2 issue. both relevant.

Worth to mention: none of those findings overlapped.

I let deepseek v4.1 flash and gpt 6.1 sol both plan fixes for the summary of the findings. in this particular scenario: gpt 6.1 sol planned to increase a buffer size from 128 to 256 to fit the 191 elements that blew past a test scenario. it included some headroom. deepseek v4.1 flash on the other hand decided to make it exactly 191 to satisfy the test, for example.

The TPS decode on deepseek is impressive. I never had a second / feeling of being left aone and though "damn this thing is working". Despite all my efforts, it took ~4x longer in a review, found less and planned worse than GPT 6.1 Sol. Wall clock time. I don't have token counts for comparison. If I were to grade those models from 1-10 (10 = top tier GG), I'd give deepseek a solid 6.5 and 6.1 sol a 7.5-8.0 maybe.

What do I need faster performance for anyway? My existing Apple TV from.. 2019? is still running cool and handles every app without sweating.

yeah the reason why i submitted the EN article and not original spiegel one is because HN isn't a german only platform and i found no english article on this, thought it was important news anyway

> If a story is spam or off-topic, flag it. Don't feed egregious comments by replying; flag them instead. If you flag, please don't also comment that you did.

Interesting, why is this spam or off topic? This is absolutely an AI topic that needs to be discussed. Not off-topic. Moderation? Hello?

Is Robert House involved?

quick reminder: this is a one shot pydantic token guess. if you try to use a model that was trained on reasoning? you're not getting any of the reasoning.

so basically dots is openclaw absorbed into chatgpt?

you can actually leverage 400k and 1M contexts in codex with very little code changes to the harness. note that excess context past the.. 250k or 400k mark (i don't remember) is charged at 2x the price.

regarding the new pro max subscription btw:

it's 500$ for 25x the plus usage, thats pro (max).

this implies that the old 200$ 20x pro (more) is now more like 10x the usage of plus.

they are slashing our subscriptions in half and make it "but we're more efficient!"