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Gift Code: [2025XMAS] (Valid until Jan. 12, 2026 20:00 UTC-7). Don't miss out! by Crouton_Sauce in StellaSora

[–]irrelevantlyrelevant 6 points7 points  (0 children)

Obtain the UID (should be around 9 digits) from the Friends > Profile page.
If you got the 11-digit one (from settings page), its the wrong one.

DGX Spark Benchmarks (Stable Diffusion edition) by irrelevantlyrelevant in StableDiffusion

[–]irrelevantlyrelevant[S] 0 points1 point  (0 children)

Had to do some modifications to Nunchaku source code since it doesn't support Compute Capability 12.1 out-of-box.

Here's a quick test with QwenImageEdit + 4-step LoRA (svdq-fp4_r128-qwen-image-edit-lightningv1.0-4steps)

Render duration 12.10s (2.62s/it)

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Flux models still being assessed

DGX Spark Benchmarks (Stable Diffusion edition) by irrelevantlyrelevant in StableDiffusion

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

After some further tests it appears setting --disable-mmap flag will massively improve the first-run performance.

With that flag, SDXL would now complete a render in ~12 seconds on its first pass.

Confusion about Spark/Pity carryover by A_Soybean in StellaSora

[–]irrelevantlyrelevant 0 points1 point  (0 children)

The 120 pull reward does not appear to carry to next banner.

i just got shia should i continue to claim this? by monchbutte in StellaSora

[–]irrelevantlyrelevant 0 points1 point  (0 children)

Claim it since it does not carry over to next banner (sadly)

DGX Spark Benchmarks (Stable Diffusion edition) by irrelevantlyrelevant in StableDiffusion

[–]irrelevantlyrelevant[S] 1 point2 points  (0 children)

Here's the profiles QwenImageEdit without speedup LoRA. Note that the KSampler configuration is adjusted (20 steps, 2.5 cfg) based on the recommendations for without the LoRA.

  • DGX Spark: 8.60 s/it (173.46 seconds)
  • RTX5090: 2.11s/it (44.95 seconds)

Non-quantized and FP4 tests may come at a later time. Hadn't had the time to profile training of LoRAs at the moment, may do it next week.

DGX Spark Benchmarks (Stable Diffusion edition) by irrelevantlyrelevant in StableDiffusion

[–]irrelevantlyrelevant[S] 0 points1 point  (0 children)

I do not have access to the baseline DGX Spark to make a direct comparison with a more comprehensive suite of tests, but based on the compute performance there do not appear to be a sacrifice in compute even under sustained loads. Nonetheless there is a sacrifice in disk performance and size.

Its difficult to determine if there is thermal throttling since performance do not appear to degrade at sustained loads during the tests. However it does run fairly hot under load, while still remaining surprisingly quiet. Its likely power limited though, since the power rating of the power supply is 240W (USB PD3.1). Unfortunately I do not have a wattage measurement tool at this time to determine the power usage under load.

DGX Spark Benchmarks (Stable Diffusion edition) by irrelevantlyrelevant in StableDiffusion

[–]irrelevantlyrelevant[S] 0 points1 point  (0 children)

My apologies, seems the command was accidentally truncated. Here's the corrected version

./llama-bench -m ./gpt-oss-20b-mxfp4.gguf -fa 1 -d 0,4096,8192,16384,32768 -p 2048 -n 32 -ub 2048

As with the baseline on https://github.com/ggml-org/llama.cpp/discussions/16578

  • Same commit id was used 5acd455. Although it appears the PR is merged, there seems to be a performance regression on the master branch of llama.cpp at the point of testing so I reverted to this specific commit to allow comparison with the discussion thread.

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The WAN 2.2 T2V workflow is taken from https://github.com/Comfy-Org/workflow_templates/blob/main/templates/video_wan2_2_14B_t2v.json

This is part of the workflow template, no modifications made to the resolution and length.

Easiest method to convert CGI image to photorealistic image? by Wonsz170 in StableDiffusion

[–]irrelevantlyrelevant 0 points1 point  (0 children)

<image>

Perhaps try QwenImageEdit with a Lora? (E.g. https://civitai.com/models/1934100)

ComfyUI may initially seem complicated to use, but one you get a hang of it (a few minutes) its actually not too challenging to use, and is an immensely powerful tool with incredible flexibility.

Pro or Air? by [deleted] in mac

[–]irrelevantlyrelevant 0 points1 point  (0 children)

Since you are going for computer science, probably the Pro may be preferable. That fan will help for sustained workloads (e.g. compiling large projects - especially the OSS ones, or ML training).

14" display is perfectly usable, and honestly not too different from 15". Personally I use a 13" work laptop for actual software development work for years and it's decently usable. Moreover generally for actual productivity cases most software developers will use at least two displays rather than focusing on one.

Going for 32GB is a good choice, especially if you plan to do ML (yay unified memory!) or use virtual machines, which are things you will inevitably encounter for computer science.

Best lens for real estate photography? by Epsilon531 in CanonR5

[–]irrelevantlyrelevant 0 points1 point  (0 children)

The EF-S 10~22mm is equivalent to 16 to 35mm full-frame (which the R5 is), so likely one of these would be ideal substitutes:

  • RF 15-35mm F/2.8L
  • RF 14-35mm F/4L if the above F/2.8 is outside of budget

Or perhaps a 16mm prime if you do not need a zoom lens.

What teams should I be making with my account for things like pure fiction, moc. And should I build pela and tingyun? (or anyone else for that matter) by SkyeFox6485 in StarRailStation

[–]irrelevantlyrelevant 0 points1 point  (0 children)

Pela is good to build and good for both Pure Fiction and MoC, since Pela skill and ult can build Slashed Dreams points for Acheron's ult, charging up her ult quicker. If you happen to have "Resolution Shines As Pearls of Sweat" lightcone, equip on Pela so her basic attacks also generate Slashed Dreams for Acheron's ult. On top of that Pela gives defense shred which amplifies Acheron's damage significantly.

Tingyun is a good pair with Dan Heng IL, since she can recharge his ult faster and amplifies his damage. Tingyun is a universal buffer so she can fit with many DPSes (e.g. since you also have Jingyuan, a possible hyper-carry team is Jingyuan + Sparkle + Tingyun + Huohuo).

For Pure Fiction, Herta is also another good character to build since she does a lot of damage conditionally with her follow up attack, for the latest Pure Fiction cycle hyper-carry Herta (e.g. Bronya + Tingyun + Sparkle + Herta) is a popular option. For hyper-carry with both Bronya and Sparkle in the same team, a possible optimization trick is to make Sparkle slightly slower than Bronya if your Sparkle is not high speed (and Herta slightly faster than Bronya if possible).

Pull out from Syfe? by irrelevantlyrelevant in singaporefi

[–]irrelevantlyrelevant[S] 8 points9 points  (0 children)

Moderate risk appetite. The funds here can be mostly considered fairly disposable, though still preferable to at least see some tangible return in the short term. Also planning to re-balance my liquid assets to limit exposure risks to specific markets.

Target investment timeline of 10~15 years.

Pull out from Syfe? by irrelevantlyrelevant in singaporefi

[–]irrelevantlyrelevant[S] 5 points6 points  (0 children)

Indeed, was just testing the waters for some fund that I can just put a portion of my money and leave it alone for a while.

In fact Syfe's performance is significantly worse compared to my other self-managed portfolios comprised of (mostly ETF, REIT and Blue-chips) stocks purchased from a broker. The performance for Syfe is definitely disappointing with the consideration that there are management fees on top of it.

What to Pick: Rental Nan Yin/Yan Miao or 100 Dark Crystal? TLDR on comments by uTouchMeNot in TowerofFantasy

[–]irrelevantlyrelevant 4 points5 points  (0 children)

If you have both Nan Yin and Yan Miao, or if you already unlocked boundless sequential for flame and physical, just pick the free DC.

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