Hacker News: ekojs

New comment by ekojs in "Kimi K3 is now live"

ekojs — Thu, 16 Jul 2026 15:39:05 +0000

I copied that from https://platform.kimi.ai/docs/guide/kimi-k3-quickstart but it seems they updated the page to remove the benchmark score now.

New comment by ekojs in "Kimi K3: Open Frontier Intelligence"

ekojs — Thu, 16 Jul 2026 15:36:00 +0000

Yeah, bad wording it seems. Though a charitable interpretation is that Fable 5 and GPT 5.6 Sol are joint 1st place in the measurement.

New comment by ekojs in "Kimi K3: Open Frontier Intelligence"

ekojs — Thu, 16 Jul 2026 15:23:46 +0000

> In our evaluations, Kimi K3 delivers frontier-level performance. Among the models tested, its overall intelligence ranks second only to Claude Fable 5 and GPT-5.6 Sol. For the complete benchmark results, see our tech blog. The full model weights of Kimi K3 will be released in the coming days. More details on the architecture, training, and evaluation will be published together with the Kimi K3 technical report.

> K3 pushes the boundary of end-to-end knowledge work. On the GDPval-AA v2 leaderboard, Kimi K3 scores 1687. The benchmark evaluates AI models on real-world tasks across 44 occupations and 9 major industries; Kimi K3 ranks behind only Claude Fable 5 Max and GPT-5.6 Sol Max, and ahead of Claude Opus 4.8 Max at 1600.

> On AA-Briefcase, Kimi K3 scores 1527, ranking second among all models — behind only Claude Fable 5 Max and ahead of GPT-5.6 Sol Max (1495). AA-Briefcase is a private agentic knowledge-work benchmark developed by Artificial Analysis to evaluate frontier agentic capability in long-horizon knowledge work.

Really good benchmark score it seems. Maybe another DeepSeek moment right here.

New comment by ekojs in "Gemini 3.5 Flash"

ekojs — Tue, 19 May 2026 18:40:27 +0000

Seems like the only good thing about 3.5 Flash is its speed. Not cost-competitive or benchmark-leading by any means.

New comment by ekojs in "Apple Silicon costs more than OpenRouter"

ekojs — Sun, 17 May 2026 15:08:42 +0000

Not disagreeing with your argument, but:

> If you want a good dense model, use qwen3.6 27B instead, speed will be up, and if you don't take my word for it being smarter, take openrouter's prices of it against the bigger, slower and less memory-efficient gemma do the talking.

Don't know if this is the correct read. I think those providers are simply taking cue from Alibaba's first-party pricing for the 27B Dense. It's kinda overpriced imo. Perhaps it can be explained by how 'reasoning-inefficient' (relative to frontier models or even Gemma) the Qwen models are and longer sequence lengths are expensive to serve.

New comment by ekojs in "How to make SSE token streams resumable, cancellable, and multi-device"

ekojs — Fri, 08 May 2026 07:03:16 +0000

> HTTP is just not a good transport for streaming LLM tokens and for building async agentic applications

I don't know if I agree if this is a problem with SSE or HTTP. Something like a Redis Streams-backed SSE would solve most of the 'challenges' presented in the post.

New comment by ekojs in "Qwen3.6-27B: Flagship-Level Coding in a 27B Dense Model"

ekojs — Wed, 22 Apr 2026 16:04:10 +0000

> You cannot run these models at 8-bit on a 32GB card because you need space for context

You probably can actually. Not saying that it would be ideal but it can fit entirely in VRAM (if you make sure to quantize the attention layers). KV cache quantization and not loading the vision tower would help quite a bit. Not ideal for long context, but it should be very much possible.

I addressed the lossless claim in another reply but I guess it really depends on what the model is used for. For my usecases, it's nearly lossless I'd say.

New comment by ekojs in "Qwen3.6-27B: Flagship-Level Coding in a 27B Dense Model"

ekojs — Wed, 22 Apr 2026 15:55:57 +0000

Yeah, figure the 'nearly lossless' claim is the most controversial thing. But in my defense, ~97% recovery in benchmarks is what I consider 'nearly lossless'. When quantized with calibration data for a specialized domain, the difference in my internal benchmark is pretty much indistinguishable. But for agentic work, 4-bit quants can indeed fall a bit short in long-context usecase, especially if you quantize the attention layers.

New comment by ekojs in "Qwen3.6-27B: Flagship-Level Coding in a 27B Dense Model"

ekojs — Wed, 22 Apr 2026 15:46:10 +0000

Not at all, I actually run ~30B dense models for production and have tested out 5090/3090 for that. There are gotchas of course, but the speed/quality claims should be roughly there.

New comment by ekojs in "Qwen3.6-27B: Flagship-Level Coding in a 27B Dense Model"

ekojs — Wed, 22 Apr 2026 15:41:14 +0000

As this is a dense model and it's pretty sizable, 4-bit quantization can be nearly lossless. With that, you can run this on a 3090/4090/5090. You can probably even go FP8 with 5090 (though there will be tradeoffs). Probably ~70 tok/s on a 5090 and roughly half that on a 4090/3090. With speculative decoding, you can get even faster (2-3x I'd say). Pretty amazing what you can get locally.

Show HN: Linux Nvidia GPU V/F Curve Editor for Undervolting/OC

ekojs — Fri, 20 Mar 2026 13:35:09 +0000

Article URL: https://github.com/ekojsalim/nvcurve/tree/main

Comments URL: https://news.ycombinator.com/item?id=47454289

Points: 4

# Comments: 1

Gemini API Down

ekojs — Mon, 29 Sep 2025 18:36:14 +0000

Article URL: https://twitter.com/OfficialLoganK/status/1972729571868086327

Comments URL: https://news.ycombinator.com/item?id=45417196

Points: 3

# Comments: 0

New comment by ekojs in "Gemini API Billing Bug Causing Erroneous Charge for 'Image Generation'"

ekojs — Mon, 25 Aug 2025 10:58:58 +0000

Seems pretty widespread. We got mistakenly charged for ~$800 over the weekend.

Other Sources:

[0]: https://aistudio.google.com/status

[1]: https://www.reddit.com/r/GeminiAI/comments/1mycmtk/google_cl...

[2]: https://www.reddit.com/r/GeminiAI/comments/1myg04q/gemini_25...

Gemini API Billing Bug Causing Erroneous Charge for 'Image Generation'

ekojs — Mon, 25 Aug 2025 10:58:58 +0000

Article URL: https://discuss.ai.google.dev/t/gemini-api-cost-suddenly-skyrocketed/99479

Comments URL: https://news.ycombinator.com/item?id=45012503

Points: 4

# Comments: 1

New comment by ekojs in "Gemini with Deep Think achieves gold-medal standard at the IMO"

ekojs — Mon, 21 Jul 2025 17:28:06 +0000

> Btw as an aside, we didn’t announce on Friday because we respected the IMO Board's original request that all AI labs share their results only after the official results had been verified by independent experts & the students had rightly received the acclamation they deserved

> We've now been given permission to share our results and are pleased to have been part of the inaugural cohort to have our model results officially graded and certified by IMO coordinators and experts, receiving the first official gold-level performance grading for an AI system!

From https://x.com/demishassabis/status/1947337620226240803

Was OpenAI simply not coordinating with the IMO Board then?

New comment by ekojs in "How I Use Kagi"

ekojs — Thu, 17 Jul 2025 17:05:21 +0000

Maybe not a popular sentiment here on HN but I cancelled my Kagi subscription (9+ months) just recently. Increasingly, most of my queries/search have been through LLMs and Google search is just fine (and even better for restaurants, places, and the like). I don't think the improved search experience is worth the subscription anymore.

New comment by ekojs in "GCP Outage"

ekojs — Thu, 12 Jun 2025 18:53:25 +0000

https://status.cloud.google.com/incidents/ow5i3PPK96RduMcb1S...

> Multiple GCP products are experiencing impact due to Identity and Access Management Service Issue

IAM issue huh. The post-mortem should be interesting at least.

New comment by ekojs in "GCP Outage"

ekojs — Thu, 12 Jun 2025 18:29:46 +0000

Super duper frustrating having the status page being green. Why can't Google do this properly?

New comment by ekojs in "Next.js 15.1 is unusable outside of Vercel"

ekojs — Thu, 12 Jun 2025 10:50:19 +0000

I share the sentiment. I think we will only be using Next.js for static sites/prebuilt SPA in the future.

New comment by ekojs in "Meta got caught gaming AI benchmarks"

ekojs — Tue, 08 Apr 2025 16:58:45 +0000

I think it's most illustrative to see the sample battles (H2H) that LMArena released [1]. The outputs of Meta's model is too verbose and too 'yappy' IMO. And looking at the verdicts, it's no wonder by people are discounting LMArena rankings.

[1]: https://huggingface.co/spaces/lmarena-ai/Llama-4-Maverick-03...