Partnerships at the Atomic ecosystem @atomicbot_ai / @atomic_mail / @atomic_chat_hq
Joined October 2023
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Hanging out at the @cognition hack working with #devin
4hrs to whip up a sales coaching app, anyone not optimizing internal org structure with AI is missing out
Thx @launchloop_xyz for organizing this!
The price diff is surprising, can't wait to see of this the agi Sam promised
GPT Astra just cooked Claude Fable 5.1 — for a lower price!
OpenAI just rolled out GPT‑6 Astra — we put it against Anthropic's Fable 5.1
Both models got the same four briefs: Earth colliding with Mars, a tall ship sucked into a giant whirlpool, Godzilla leveling downtown, a mega-tsunami swallowing a city. One self-contained HTML file per scene, one shot, no edits.
GPT Astra: 25,159 tokens, $1.67
Claude Fable 5.1: 37,767 tokens, $2.51
both models live on aimlapi[.]com — 1000+ models, one key.
Okti retweeted
Muse Glimmer one-shot 5 games!
@AIatMeta dropped Muse Glimmer. So we ran it against Muse Spark 1.2, on five one-file game demos, each one written to play itself: Tetris, a top-down pixel street race, a rooftop web-slinger, a blue hedgehog platformer, and Flappy Bird.
the setup:
• Muse Glimmer 30B — via aimlapi[.]com. cost: $0.02
• Muse Spark 1.2 — via aimlapi[.]com. cost: $0.11
what we saw:
• every Glimmer scene runs and plays itself. it's a reasoning model, so it burns more tokens — but the output is clean. its Tetris even scores each placement to keep lines clearing, and the blocks burst into pixels on every clear.
• Glimmer beat Spark at Flappy Bird — its bird flew through the pipes cleaner.
• but it's not perfect: in the racing game its cars sometimes slip off the road, and its graphics are simpler and blockier than Spark's.
glad to see Meta back in open source — and we're waiting for Spark 1.2 weights next 🙌
Today we're also opening the weights for Muse Glimmer, a great 30B parameter dense model that can run locally. Soon we'll also release the weights for Muse Spark 1.2, our latest foundation model. Meta is a strong supporter of open source and I'm proud of these releases. Congrats to @alexandr_wang and the MSL team for all your great work on these models.
Seed5 good vids for $6 were made with Seedance during the production of this post - how is this pricing even real
Seedance 2.5 just cooked Veo 3.1 – for half the price!
to celebrate, we're giving away $10 in api credits to 20 of you to try seedance 2.5 – just rt/qrt this post, winners will be picked randomly on August 10
@BytePlusGlobal 's seedance 2.5 just dropped. we ran it with google's Veo 3.1 and honestly, it wasn't much of a fight
the test: 5 prompts, one shot each, 4s, 720p, native audio, same exact prompt to both models: a tornado grinding through downtown, a tsunami swallowing a megacity, slow-mo liquid physics, a 180° camera orbit, and a neon sign with text
cost for the 5 clips:
Seedance 2.5 – $6.08 ($1.21 per clip)
Veo 3.1 – $10.40 ($2.08 per clip)
observations:
• seedance is 42% cheaper and it's the better one.
• seedance keeps geometry locked through the orbit shot – buildings, the cellist, the station all stay solid.
• disaster scenes are the closest call: veo throws more debris, seedance stages the shot better.
same prompts, almost half the price, better result. bytedance shipped a monster – and it's live on aimlapi[.]com!
Okti retweeted
DocuChain is live on @ProductHunt !
Go upvote the best e-signing service on the market
Link: producthunt.com/products/doc…
Okti retweeted
We've tested the Qwen 3.8 Max preview and it absolutely rocks!
Each scene is built in one shot, a single Three.js file with nothing else added:
• Odysseus' war galley riding the waves
• Trojan horse
• Greek war helmet
Qwen managed to execute the task faster than the other models, while output quality is relatively the same across all of them. If the pricing stays close to Alibaba's previous flagships, we'll get one of the best speed/quality ratios on the market — perfect for running agents at scale.
Soon live on AI/ML API.
Qwen3.8 is launching and going open-weight soon!🌐
With a massive 2.4T parameters, this model is continuously evolving. We believe it’s one of the most powerful model available today, compatible to leading frontier AI models , second only to Fable 5.
You don't have to wait to test it. Just now, the Qwen3.8-Max-Preview made its debut on Alibaba’s Token Plan, Qoder, and QoderWork. Be among the very first to try it out.
Can't wait to hear what you build. Stay tuned! 🚀
Token Plan
international：qwencloud.com/pricing/token-…
China：platform.qianwenai.com/prici…
Okti retweeted
First local agent to beat Hermes on benchmarks!
✦ runs Qwen, Gemma, Llama via llama.cpp
✦ stable-prefix caching keeps sessions cheap
✦ TurboQuant cuts the KV-cache 6.4× smaller
✦ 37 tasks solved vs Hermes' 31 on GAIA Level 1
Open source on macOS, Windows & Linux 👇
Okti retweeted
New Kimi K3 beat Opus 4.8 at making retro games for 2x cheaper!
We gave three models the same task: make three old arcade games that play by themselves. Each game is one HTML file with a bot that plays it
Prompts:
– Road Fighter
– Battle City
– Q*bert
Outputs:
Kimi K3: 18.4K tokens, $0.28
GPT-5.6: 18.1K tokens, $0.28
Opus 4.8: 21.3K tokens, $0.54
Kimi K3 made the best games. Its Q*bert is the best of all three. The player jumps on the cubes, paints them and runs from the purple snake. Its Battle City looks just like the real game and plays right. The tanks move, aim, shoot and break the walls. GPT-5.6 could not handle the cars. Its Battle City broke too. The tank died on its own and the base got hit. But GPT had the nicest textures of the three
Introducing Kimi K3: Open Frontier Intelligence
🔹 2.8 Trillion Parameters, 1 Million Context, Native Multimodal
🔹 Kimi Delta Attention enables up to 6.3x faster decoding in million-token contexts
🔹 Attention Residuals deliver ~25% higher training efficiency at <2% additional cost
🔹 Built for long-horizon agentic coding and self-evolving workflows
Kimi K3 is now live on on Kimi.com, Kimi Work, Kimi Code, and the Kimi API.
Open Weights by July 27, 2026.
🔗 API: platform.kimi.ai
🔗 Tech blog: kimi.com/blog/kimi-k3
Okti retweeted
GPT 5.6 Sol & Terra just made Fable 5's pricing look like a joke!
We gave OpenAI's top models (Sol, Terra) and Anthropic's top models (Fable 5, Opus 4.8) the same 3 prompts:
• Supernova boom
• Meteor hitting a city
• Solar system model
The bill:
Sol: $4.77
Terra: $1.24
Fable 5: $9.94
Opus 4.8: $2.46
Outputs came out surprisingly close. The prices didn't. Fable 5 cost unreasonably more than everything else, with Sol not far behind. Considering latest Fable 5 nerf, it's hard to see what you're paying for.
Okti retweeted
Open-weight LongCat 2.0 matched GPT-5.5 level on agentic game dev for $0!
We ran Meituan's LongCat 2.0 against cloud frontier GPT-5.5 in @kilocode CLI with their agent. Same task for both - build a retro Duck Hunt game in one game.html, improved over 3 agent iterations with duck waves, ammo and physics
Outputs:
LongCat 2.0: 70.3K tokens, $0.00
GPT-5.5: 64.9K tokens, $0.65
LongCat kept up on graphics, physics and game logic. Ducks fly and fall when hit, the dog fetches them, ammo counts down, the waves keep coming. Both ran clean and nothing clipped. The only difference was the bill - GPT cost $0.65, LongCat ran local for $0
Okti retweeted
Fable 5 totally crushed our new contest, but it cost 6x more than Opus 4.8!
We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics demos
Prompts:
— A train derailing off a broken bridge into the water
— Two cars jumping off ramps and colliding mid-air over a canyon
— A monster truck crushing a row of parked cars
Outputs:
Fable 5: 62,158 tokens, $3.12
GPT 5.5: 37,753 tokens, $1.14
Opus 4.8: 22,280 tokens, $0.56
GLM 5.2: 36,246 tokens, $0.08
Fable 5 did all three scenes at A+. The crashes looked real, things fell and broke the right way, and nothing went through the ground or floated. GPT 5.5 was the closest to Fable. In the Bigfoot show, we think GPT was even a little better. GLM 5.2 did not win any scene, but it was the cheapest by far. Fable is the best pick for quality, but you pay more for it.
Okti retweeted
New Claude Sonnet 5 performs at GPT 5.5 level 6x cheaper!
We gave 4 models the same prompt: build three self-contained HTML5 canvas scenes with real physics crash demos
Prompts:
- A car crashes into a brick wall
- A wrecking ball destroys a house
- A catapult throws a rock at a castle wall
Outputs:
Sonnet 5: 15,047 tokens, $0.15
Opus 4.8: 23,063 tokens, $0.58
Sonnet 4.6: 25,824 tokens, $0.39
GPT 5.5: 31,152 tokens, $0.94
Sonnet 5 did as well as Opus 4.8 and GPT 5.5 on all three tests. In the wrecking ball test, it beat Opus 4.8. The cable moves smoothly and every hit connects. In the catapult test, it beat GPT 5.5. The rock always lands inside the wall. Sonnet 5 still needs better detail and graphics. But it used fewer tokens than every other model
Okti retweeted
If you've been wanting to run AI privately, offline, and for free but terminal/code was the blocker this is for you.
Stop using ChatGPT for everything. Run the SAME quality models on your own laptop. for free, forever, with zero terminal commands.
I just recorded a full walkthrough showing how anyone (yes, even if you've never touched a command line) can download and run the latest open weight LLMs from Hugging Face using llama.cpp wrapped in an intuitive GUI.
In the video I:
- Search & download Gemma 4 12B straight from Hugging Face inside the app (For my NVIDIA RTX 4060 8 GB VRAM)
- Chat with it locally - no API key, no internet required, no data leaving your machine
- Connect it to Hermes Agent in 4 clicks and have it running real agentic tasks on a 100% local model
The tool I used is Atomic Chat. open source (Apache 2.0), free, and built on llama.cpp under the hood:
- Native apps for mac, windows, linux, iOS and android, not just desktop
- One click agent integrations: Hermes Agent, Kilocode, Claude Code, Codex CLI, OpenCode, Cline CLI, Droid etc.
- Full MCP support. plug in tools and let your local model actually do things
- Auto extends context length when you're about to run out. no more silent truncation
- Hardware aware model recommendations, so it tells YOU which model your machine can actually run instead of you guessing and crashing your RAM
- OpenAI compatible local API server if you want to wire it into your own scripts later
This is the local LLM setup you need when you want started ASAP with a great UI: HuggingFace + llama.cpp power, GUI simplicity, and agent ready out of the box.
Download from the link in the comments and let me know if you need any help.
What's stopping you from running AI locally right now RAM, know how, or just never knew this existed?
Lowcode platforms need an agentic email - that's how the adoption starts
Email for AI agents integrated in Dify.
Drop @atomic_mail into any @dify_ai workflow. Agent registers its own address in one click – then triage, send, route and summarize
Let's gooo, run Ornith in Atomic Chat in 1 click to get the SOTA local LLM experience
Congrats!
Aloha! 🌺 Meet Ornith-1.0, a family of open-source LLMs specialized for agentic coding.
Ornith-1.0 spans the full parameter sizes including 9B Dense, 31B Dense, 35B MoE, and 397B MoE. It achieves state-of-the-art performance among open-source models of comparable size on coding benchmarks including:
✅Terminal-Bench 2.1(77.5)
✅SWE-Bench(82.4 on verified, 62.2 on pro, 78.9 on Multilingual)
✅NL2Repo(48.2)
✅SWE Atlas(41.2 on QnA, 42.6 RF, 39.1 TW)
✅ClawEval(77.1)
Post-trained on top of gemma4 and qwen3.5, Ornith-1.0 employs a novel self-improving training strategy in which reinforcement learning is used to generate not only solution rollouts, but also the task-specific scaffolds that drive those rollouts. By jointly optimizing the scaffold and the resulting solution, the model generate higher-quality solutions in agentic coding.😎
All models are released under the MIT license, enabling full commercial and research use.
📖Tech Blog: deep-reinforce.com/ornith_1_…
🤗Huggingface: huggingface.co/collections/d…
Integrated the search from exa day-1, easiest way to enhance the product ever
Exa AI Search now in Atomic Chat!
Your local models can finally search the live web and pull fresh info — powered by @exaailabs, trusted by 400,000+ developers, free and open-source
ooooh, i love hermes but if there's another improvement wave coming imma automate my life away
Atomic Agent beats Hermes on GAIA Level 1
We put two agents side by side on the same local model (qwen-3.6-35b-a3b) and the same 53 tasks
→ 69.8% vs 58.5% — +11.3 pp more accurate
→ ~1.6× faster per task (217s vs 351s)
Open source. Repo + full logs below 👇
curl -fsSL api.atomicbot.ai/agent-insta… | sh
Let's goooo!
Atomic chat is now an official way to run local ai on HF
Atomic Chat is now on Hugging Face 🤗
We're officially a Local App on the world's biggest AI hub. Run 200,000+ open-weight models from @huggingface directly on your device - private, local, and open source!