WeSearch

Open-weights AI models have become good enough

Senko Rašić· ·3 min read · 0 reactions · 0 comments · 2 views
#open-weights#models#become#good#enough
Open-weights AI models have become good enough
TL;DR · WeSearch summary

Open-weights AI models have become good enoughJuly 22, 2026Over the past week I've played around with Kimi K3 by Moonshot AI and Qwen 3.8 Max by Alibaba. Both are large Chinese open-weight models (weights promised to be released soon) and tout benchmarks showing they're as capable as the frontier western models (Fable 5 by Anthropic and GPT-5.5 Sol by OpenAI). I wouldn't go that far, but these are really capable models.

Key facts
About this source

Hacker News (AI / LLM) files mainly under ai. We currently carry 2,875 of its stories.

Original article
Senko Rašić · Senko Rašić
Read full at Senko Rašić →

Story provenance

Source · retrieval · rights · ranking — open for full record
inspect →

Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.

Record

Original publisherSenko Rašić
Canonical URLhttps://blog.senko.net/open-weights-ai-models-have-become-good-enough
Publication timeThu, 30 Jul 2026 09:57:16 +0000
Retrieval time2026-07-30T10:07:01.703Z
Last seen2026-07-30T10:07:01.703Z
Headline sourcePublisher (no WeSearch rewrite)
Excerpt sourcepublisher body
Excerpt methodFirst ~120 words (~800 chars) of extracted publisher body, fair-use limited.
SummaryWeSearch · cerebras-chat (WeSearch summarizer)
Summary source textcontentText
Citation coverageSummary is a WeSearch-generated derivative; primary citation is the original publisher URL.
ClusterXiPq1zYtJHPx · 1 stories
Cluster logicGrouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison.
Ranking reasonStory pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking.
Publisher visitYes — open original
Substitutes article?No — link-out required for full text

Rights status (four layers)

Publisher-declared
No publisher-confirmed rights record for this source yet.
Machine-readable
No source-specific machine-readable restriction detected beyond the public feed.
WeSearch interpretation
WeSearch declared handling (basis: Derived from the published RSS/Atom feed). This is WeSearch policy, not a legal grant on the publisher's behalf.
Unknown
Retrieval and training permissions are not asserted unless the publisher confirms them.

WeSearch handling by dimension

Indexing May the item be indexed (stored, ranked, made findable)? Allowed
Snippet May a short excerpt of the publisher's text be shown? Allowed
AI summary May WeSearch generate its own short summary of the article? Limited
Retrieval / RAG May the content be exposed for third-party retrieval-augmented generation? Not asserted
Model training May the content be used to train AI models? Not asserted
Commercial reuse May the content be reused commercially? Not permitted

Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.

Opening excerpt (first ~120 words) tap to expand

Open-weights AI models have become good enoughJuly 22, 2026Over the past week I've played around with Kimi K3 by Moonshot AI and Qwen 3.8 Max by Alibaba. Both are large Chinese open-weight models (weights promised to be released soon) and tout benchmarks showing they're as capable as the frontier western models (Fable 5 by Anthropic and GPT-5.5 Sol by OpenAI). I wouldn't go that far, but these are really capable models. In my AI-coding tests, both have performed really well. Compare the test mini-games on my vibe-coding benchmark generated by Fable, Sol, K3 and Qwen. In a more serious test, building a web app to a provided spec, K3, Qwen and Fable generated very similar results.

Excerpt limited to ~120 words for fair-use compliance. The full article is at Senko Rašić.

Anonymous · no account needed
Share 𝕏 Facebook Reddit LinkedIn Threads WhatsApp Bluesky Mastodon Email

Discussion

0 comments

More from Senko Rašić