#Ornith
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aiplanet.bsky.social
📰 Reddit r/LocalLLaMA
Ornith-1.5 DFlash

https://www.reddit.com/r/LocalLLaMA/comments/1wt35c6/ornith15_dflash#IA##AI##ML#ML
September 29, 2026 at 11:01 AM
tijs.org
The short decode TPS for Qwen and Ornith is now 58 and 57 tokens/sec respectively. This is the number you would usually see quoted. For a full multi step process numbers would be lower on average though.
September 29, 2026 at 6:08 AM
tijs.org
Mei was updated to 0.6.1, for the Ornith 1.5 model weighted avg TPS improved slightly, same for TTFT, and total task time was better. Qwen 3.6 only improved on task time and TTFT. Progress has slowed a bit, definitely harder to get gains now without making another metric worse.

github.com/tijs/mei
GitHub - tijs/mei: Native Swift/MLX OpenAI-compatible inference server for Apple Silicon
Native Swift/MLX OpenAI-compatible inference server for Apple Silicon - tijs/mei
github.com
September 29, 2026 at 5:49 AM
rgonv.bsky.social
Ornith Models Automate Agentic Coding With Self-Scaffolding
Ornith, a new family of open source LLM models from the DeepReinforce research collective, takes a novel approach to executing coding and debugging tasks: It generates an architectural framework to give the user’s harness a structured instruction set – a scaffold – to create an agent to complete the job. Available in a set of […]
dlvr.it
September 27, 2026 at 3:32 PM
winsontang.com
Discover the evolution of Ornith-1.5, where self-scaffolding meets self-improvement. This latest update enhances adaptive learning, refining how we harness AI for smarter solutions. Explore the new features and elevate your understanding of AI capabilities!

https://ornith.ai/ornith_1_5.html
September 26, 2026 at 1:10 PM
astralplume.bsky.social
(specifically, the eye colours go:
Larissa (unsundered) ‑ ice-blue
Clio (Source) ‑ amethyst-purple
Amy (First) ‑ dark ocean-blue
Ornith (Ninth) ‑ teal-green
Mhara (Thirteenth) ‑ cold dark brown

I have yet to design her counterpart shard on the Fourth, but they’ll also match the trait!)
September 25, 2026 at 10:17 AM
vietstarwhite.bsky.social
✨✨Hermes dashboardでOrnith-1.0の追加を試すがNG、シンキングモデルでシンキングをオフに出来る最新版に入れ替えて最新のAIであるQwen3.8をインストールして動いた😊!!。
https://vietnamwhite.hatenablog.com/entry/2026/09/24/113000
#はてなブログ #Vietnam #AI
ニーナが暴走！？Hermes AgentとOllamaの謎バグをソネちゃんと退治したよ🔥 - vietstarwhiteのブログ
Hermes AgentとOllamaのthinkingモデルが「Empty response」を起こす原因と、hermes updateで解決するまでの一部始終を、White翁とソネちゃんの掛け合いで解説。
vietnamwhite.hatenablog.com
September 25, 2026 at 12:39 AM
vietstarwhite.bsky.social
✨✨Hermes dashboardでOrnith-1.0の追加を試すがNG、シンキングモデルでシンキングをオフに出来る最新版に入れ替えて最新のAIであるQwen3.8をインストールして動いた😊!!。
https://vietnamwhite.hatenablog.com/entry/2026/09/24/113000
#はてなブログ #Vietnam #AI
ニーナが暴走！？Hermes AgentとOllamaの謎バグをソネちゃんと退治したよ🔥 - vietstarwhiteのブログ
Hermes AgentとOllamaのthinkingモデルが「Empty response」を起こす原因と、hermes updateで解決するまでの一部始終を、White翁とソネちゃんの掛け合いで解説。
vietnamwhite.hatenablog.com
September 24, 2026 at 7:41 AM
vietstarwhite.bsky.social
✨✨新進気鋭のAI、Ornith-1.0とは？、技術の核心「Self-Scaffolding」の仕組み・・・　続編PART2、実際にインストールしてCODEXと組み合わせて使ってみたよ😊!!。
https://vietnamwhite.hatenablog.com/entry/2026/09/21/113000
#はてなブログ #Vietnam #AI
9Bが30Bに1分47秒対10分46秒で圧勝😳ローカルAI「Ornith」をCodexに繋いで電卓対決してみた！ - vietstarwhiteのブログ
話題のオープンウェイトコーディングAI「Ornith-1.0-9B」をWSL2のOllamaに実際にインストールし、日本語対応・Codex連携・電卓プログラム対決（Qwen3-coder-30Bと比較）まで一日で検証した実験レポート第二弾。
vietnamwhite.hatenablog.com
September 21, 2026 at 8:04 AM
vietstarwhite.bsky.social
✨✨新進気鋭のAI、Ornith-1.0とは？、技術の核心「Self-Scaffolding」の仕組みと今後のクラウドAIの発想にも組み込まれる新技術となるのか？😊!!。
https://vietnamwhite.hatenablog.com/entry/2026/09/20/113000
#はてなブログ #Vietnam #AI
AIが自分で手順書を覚える時代へ🔥オープンウェイト「Ornith-1.0」が次のトレンドの芽になるかも！ - vietstarwhiteのブログ
米国発の無名研究チームDeepReinforceが公開したコーディングAI「Ornith-1.0」が注目を集めている。最大397BモデルがオープンウェイトでありながらClaude Opus 4.7に匹敵する性能を発揮。「モデル自身がハーネスを学習する」Self-Scaffoldingという革新的な思想と、ローカル動作の可能性をWhite翁とソネちゃんが徹底解説。
vietnamwhite.hatenablog.com
September 20, 2026 at 7:50 AM
ryutok.bsky.social
llama.cppを最新を追っかけるのからreleaseで動かすのに運用を変えて、RaspberryPi5にMiniCPM5-2B-q8_0とLFM2.5-2.6B-QAD-Q4_0を入れて、母艦にはOrnith-1.5-9B-Q8_0を入れて、llama.cppの-ctk,-ctvをq4_0からiq4_nlに変更して、、、

なんとなく、賢くなった気がするｗ（おっさんの感想
September 20, 2026 at 4:43 AM
cynthb.bsky.social
What I wanted: something to retrieve local crime stats from the local police public DB of reports and format it, running Ollama locally.

My system: Pop! OS Linux (Ubuntu based), Core I7-14700KF, 32Gb, RTX 4060, Ollama running ornith-1.5:9b (Qwen based), and KIT as the interface.
September 19, 2026 at 2:23 PM
bsky.shibadogcap.com
私もローカルLLMしたいなあ！と思ってエージェントにゴネたらOrnith-1.5-35B-A3Bが0.3tok/sで動いて神

Original: https://x.com/4ba_ba_baba/status/2100131227407921346
September 16, 2026 at 7:58 AM
og-programmer.bsky.social
Been testing neohorse-1 because their benchmarks show they better than ornith-1.5, but goodness, neohorse gets lost for simple things like looking at server logs or simple code base inspection. Benchmarkmaxing is real... #AI #LLM #LocalLLM
September 15, 2026 at 12:29 PM
cenewman0.bsky.social
Actually, I will keep in mind! I buy the shirts every year now that Ornith started that up again, but I'd love to support in additional ways.
September 15, 2026 at 12:32 AM
refinement.systems
ornith-1.5-35b-a3b is a post-trained qwen, and a straightforward replacement to try (it has higher benchmark scores and does seem to be better in my tests. though I've only used it to diagnose issues, not to write anything)
September 14, 2026 at 11:07 AM
tijs.org
With the release of Mei 0.5.0 it has become much easier to run things. You can brew install and all the important settings have good defaults now. Also; Ornith 1.5 is no longer the front runner, my text only version of Qwen 3.6 27B beats it in my benchmarks.

github.com/tijs/mei
GitHub - tijs/mei: Native Swift/MLX OpenAI-compatible inference server for Apple Silicon
Native Swift/MLX OpenAI-compatible inference server for Apple Silicon - tijs/mei
github.com
September 13, 2026 at 8:16 AM
nanome19.bsky.social
試しにornithの35bで試した時も賢いなと思ったけど、これはclineが良く出来てるのもあるんだろうな。
September 12, 2026 at 8:30 PM
grenoble.ninja
Aujourd'hui nous utilisons Ornith-1.5-35B (chat, code) et Whisper/Whisper Turbo (transcription). Pas de mesure pour l'instant concernant les requêtes (seulement une 10aine d'utilisateurs en test), mais le dimensionnement a été prévu pour ~300 utilisateurs quotidiens.
September 12, 2026 at 6:37 PM
rhosoi.bsky.social
なんだかんだでqwen3.8よりornith-1.5:35Bのが軽いしいいな〜ってことで試してた
MLX版にしたらプロンプトの評価も1.4倍ぐらい速くなって8bit版にしたら文字化けもほとんどしないし、相当いい感じだわ

huggingface.co/ornith-ai/Or...
ornith-ai/Ornith-1.5-35B-A3B-MLX-8bit · Hugging Face
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
huggingface.co
September 11, 2026 at 4:48 AM
francois-berube.bsky.social
Hello, est ce que tu as testé ornith 1.5 ? En 9b dense ou 35b moe ?
September 9, 2026 at 6:30 PM
hrbrmstr.mastodon.social.ap.brid.gy
@timbray @simon Ornith and qwen are great local models and there are quite a few task-specific other ones. None are gonna match foundation models/infra but we rly shld not be investing in those anyway.

You can also fan out very large open weights models across the studios. Apple’s new kit has […]
Original post on mastodon.social
mastodon.social
September 7, 2026 at 9:58 PM
lizthegrey.com
I've been pretty impressed with Ornith 1.5 for local work, but also it is nowhere near smart enough I'd trust it anywhere near production.
September 7, 2026 at 4:53 PM
tijs.org
.. stick with Qwen 3.6, it scores about as well as Ornith and the full model still fits in 32GB, just 10% slower. Still trying to find paths to run Qwen 3.8 on this Mac but it's hard to make it faster. The new dense FFN makes them slow, it's just too many weights to calculate on 'low end' hardware.
September 7, 2026 at 2:46 PM
tijs.org
I'm basically left with Ornith 1.5 and Qwen 3.6 as viable models for this machine. Since Ornith is text only i also tested a version of Qwen without vision which is a nice boost to memory usage. So if you don't need vision that's a nice option. If you *do* want your local model to have vision..
September 7, 2026 at 2:46 PM