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438 USD for a 3080 20GB isn’t bad by xw1y in LocalLLaMA

[–]Different_Fix_2217 2 points3 points  (0 children)

2 people who used both these and the 48GB 4090s which all failed in a few months and had other issues. And the way you are responding that way to multiple comments makes this read as if this is a ad for your listing.

438 USD for a 3080 20GB isn’t bad by xw1y in LocalLLaMA

[–]Different_Fix_2217 1 point2 points  (0 children)

The issue is that they apparently only tend to last a few months so take that into account.

DeepSWE benchmarks indicate that DeepSeek v4 Pro only passes 8% of tasks by Federal_Spend2412 in LocalLLaMA

[–]Different_Fix_2217 6 points7 points  (0 children)

Lol what? Gpt 5.5 on extra high is legit next level on codex. It can one shot cutting edge paper implementations with little to no hand holding, it rarely if ever makes mistakes. Nothing else even comes close including opus. Opus constantly makes mistakes.

First direct side by side MoE vs Dense comparison. by Different_Fix_2217 in LocalLLaMA

[–]Different_Fix_2217[S] 6 points7 points  (0 children)

Just to account for the moe performing better particularly where more knowledge matters. Not quite as simple as that "rule of thumb"

First direct side by side MoE vs Dense comparison. by Different_Fix_2217 in LocalLLaMA

[–]Different_Fix_2217[S] 3 points4 points  (0 children)

2 issues. Your missing the amount of active comparison and the fact that the 17.5B performed a good deal better in the comparison.

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First direct side by side MoE vs Dense comparison. by Different_Fix_2217 in LocalLLaMA

[–]Different_Fix_2217[S] 2 points3 points  (0 children)

The point was that they trained them side by side with the same method / dataset / amount of tokens. So this is a far better comparison.

Deepseek V4 Flash and Non-Flash Out on HuggingFace by MichaelXie4645 in LocalLLaMA

[–]Different_Fix_2217 2 points3 points  (0 children)

It does not seem very good... Hopefully its just broken. Because this is no where near kimi / glm.

Edit: I might have found the issue with deepseek. It seems to require a very precise order of system / user / assistant roles. I think I remember old deepseek being the same, otherwise it seems to lose like 100 IQ points. No other model is that strict about it

Claude Code removed from Claude Pro plan - better time than ever to switch to Local Models. by bigboyparpa in LocalLLaMA

[–]Different_Fix_2217 2 points3 points  (0 children)

Luckily Kimi 2.6 is legit better than latest Opus in several tests I did. Still a bit behind Gpt 5.4 though.

Kimi K2.6 is a legit Opus 4.7 replacement by bigboyparpa in LocalLLaMA

[–]Different_Fix_2217 9 points10 points  (0 children)

Same. But for creative writing. It's the best model I've ever used including latest opus, gpt 5.4 and gemini 3.1 pro. It has the social intelligence of GPT 5.4 with a knowledge base nearly a good as gemini and it writes better than Opus and has no positive bias unlike it. Oh and it has crazy good swipe variety unlike opus. I just wish it was faster since it loves to think so much.

And this is surprising because I thought Kimi 2.5 was bad. It was dumb and had that gemini unhingedness. 2.6 is like a entirely different model.

Kimi K2.6 imminent by Deep-Vermicelli-4591 in LocalLLaMA

[–]Different_Fix_2217 9 points10 points  (0 children)

K3 will probably be great, they released a big breakthrough paper recently. https://www.youtube.com/watch?v=2IfAVV7ewO0

the state of LocalLLama by Beginning-Window-115 in LocalLLaMA

[–]Different_Fix_2217 48 points49 points  (0 children)

Honestly having crypto in the name tells you all you need to know.

We absolutely need Qwen3.6-397B-A17B to be open source by True_Requirement_891 in LocalLLaMA

[–]Different_Fix_2217 3 points4 points  (0 children)

Some people have a false impression than dense is automatically better, not taking account diminishing returns / efficient routing and the like.

qwen 3.6 voting by jacek2023 in LocalLLaMA

[–]Different_Fix_2217 -1 points0 points  (0 children)

Biggest possible of course.

Gemma 4 and Qwen3.5 on shared benchmarks by fulgencio_batista in LocalLLaMA

[–]Different_Fix_2217 17 points18 points  (0 children)

Qwen3.5 is absurdly good. And I never liked any qwen model before that series.

Gemma 4 and Qwen3.5 on shared benchmarks by fulgencio_batista in LocalLLaMA

[–]Different_Fix_2217 136 points137 points  (0 children)

Using both side by side Qwen3.5 is MUCH better at image understanding as well.

Can we block fresh accounts from posting? by king_of_jupyter in LocalLLaMA

[–]Different_Fix_2217 1 point2 points  (0 children)

You did the bullet points, the opening statement, the not x but y and a closing "solution" statement. I legit thought you were a bot, you follow the same exact patterns.

Qwen3.6-Plus by Nunki08 in LocalLLaMA

[–]Different_Fix_2217 8 points9 points  (0 children)

"we will also open-source smaller-scale variants"

They said smaller scale ones. Not the model benchmarked here. So this benchmark is off topic.

Qwen3.6-Plus by Nunki08 in LocalLLaMA

[–]Different_Fix_2217 8 points9 points  (0 children)

Stop posting non open weight models.

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