Top Tweets for #MultiModel
Moving away from monolithic models toward multi-model orchestration like @kwindla describes is where the real utility lies for my workflow, even if chaining prompts together introduces plenty of brittle failure points.
#AI #MultiModel
https://t.co/p6JxIsaXzy
The big themes I've been working on this year are: multi-model systems, specializing models for specific tasks, "thinking fast and slow" using multiple models/loops/prompts together in one application, and co-design of harnesses/tooling and models.
The big release today from @typesafeai touches on all of these! Their new model, Jev, fills a big, big gap in our multi-model toolkit.
I'm obsessed with building realtime systems. Voice agents, physical AI, new kinds of human-in-the-loop software.
We often build voice agent front-end loops that need to drive a variety of backend systems, ranging from extremely big and slow (for example, coding agents) to super-fast and specialized (think vision systems and classifiers).
When we're doing things like updating a dynamic user interface, we want to generate small bundles of error-free, strongly typed, structured data ... many times a second. But we also want to leverage the flexibility and natural language abilities of LLMs.
I think of this as pulling out a subset of the context from the long-running human interaction (voice and text conversation), combining that context with other state the application is managing, prompting an LLM, and getting back structured data. We build with this pattern a lot. (There's a whole section of the Pipecat docs about the `UIWorker` pattern.)
But even small-ish, fast LLMs take a few hundred milliseconds to generate ~100 tokens of structured data one token at a time. However, this is a parallelizable operation and it's right in Jev's wheelhouse.
This is the first model release in a while that feels to me like a genuinely new architecture solution to one of our big, interesting, hairy, real-world pain points as we figure out how to design new, AI-native systems.
I also really love the fact that the second post in the thread below starts out: "The gains arenβt free: Jev can't generate text".
One of the things that drives me crazy about some of the scaling-is-all-you-need discourse around models is that there are *always* systems engineering trade-offs, and they *really* matter.
There are lots and lots of exciting things to build in this new era of LLMs and generative AI. Making things that are fast enough, reliable enough, and affordable enough that people will actually use them is going to require creative exploration of a very wide design space!
I'm super-excited about Jev. Congratulations to the Typesafe team.
@kimmonismus Last year's SOTA is a tombstone. Opus 4.1, Gemini 2.5 Pro, GPT-5 High aging out in twelve months is why a one-model bet is a calendar. Multi-model is how the stack survives the next funeral.
#AI #MultiModel
https://t.co/7VsBOGZ4eG
π New Model Support in MCP Playground
β‘ Qwen 3.8 Flash
β‘ GLM 5.3 Flash
Excited to see how they perform across MCP tasks, tool use, and agent workflows. π§ͺ
More models, more experiments. π
#MCP #AI #LLM #Qwen #GLM #AIAgent #BuildInPublic #MultiModel
June keeps getting better. β‘
With Gemini 3.7 Flash and Grok 4.6 now live, @askjuneai is bringing more powerful models into one smooth AI experience.
Faster responses. Stronger reasoning. Better tools.
One place. Multiple models. Your choice. π
#AskJune #AI #MultiModel
June makes AI feel simple. π
Privacy by default, a smooth experience, multiple AI models, and Chat Branching to explore ideas without losing context.
A cleaner way to question everything.
Built by @blockchain . π
#JuneAI #AI #Privacy @askjuneai
New model drops every three weeks now.
You can either restructure your whole workflow every time, or use the app where new models just... appear.
Models are seasonal. Your setup shouldn't be. #MultiModel
Most people use 1 AI Model
One platform. Every top model @askjuneai π
No data stored. No ads. No selling your data
Built by @blockchain π
#JuneAI #Privacyfirst #MultiModel #Blockchain
Multi-model access = pick the best model for the job, ship apps faster, and avoid vendor lock-in. Do it with governance so data stays secure. #MultiModel #AI #BuildInPublic #aitools #aiassistants
JUNE Al
You can now enable Multi-Model Mode inside the app.
Ask one question and get answers from two AI models instantly π€
Compare the responses and choose the best one for you.
Smarter answers. Faster insights.
Try it now in the June AI app.
#JuneAI #AI #CryptoAI #MultiModel
Prediction: by end of 2026, "orchestrate multiple models" becomes baseline. Claude for reasoning, Gemini for research, Grok for speed. Single-model lock-in is dead. The skill isn't picking oneβit's knowing when to use which and chaining them together.
#AI #Prediction #MultiModel
AWS and Hugging Face Launch Multi-Model Agentic AI Framework with smolagents
Follow Bricks for Daily News Updates.
@BricksAInews
@BricksAInews
@BricksAInews
#ai #ainews #technews #AWS #face #launch #multimodel #agentic #futureofai #startups #gpt #openai #bricksai #fewtoneai
ArcadeDB v26.2.1 is full of surprises. Did you know we introduced a new SQL parser, built with ANTLR (instead of JavaCC) that is 75.9% faster?
https://t.co/9R2j4DX3fu
#multimodel #graphdb #sql
ArcadeDB 26.2.1 is out! Biggest highlights:
- @Neo4j Bolt protocol support - use standard Neo4j drivers
- Full @openCypher TCK compliance
- New SQL parser
- SQL Triggers (SQL, JS, Java)
- Scheduled Backups
200+ issues closed
https://t.co/vvBckoM6sW
#graphdb #multimodel
Step 2οΈβ£ β Use It on a Third-Party Platform (LobeChat Example)
RouterLink models are OpenAI-compatible and can be used on external platforms.
LobeChat integration guide:
π https://t.co/CsI2pofrDI
#WORLD3AI #RouterLink #MultiModel #LobeChat #Qwen3
2025 was a year of massive growth for ArcadeDB! π From boosting performance to expanding connectivity, weβve taken multi-model databases to the next level.
Read our full Year in Review here: https://t.co/mKfgO4qScP
#MultiModel #GraphDatabase #NoSQL
Built MMRDS - a multi-model research & debate system where specialized agents analyze, challenge, innovate, and synthesize in parallel.
Designed for high-stakes reasoning where single-model thinking breaks.
This is reasoning governance, not prompt engineering.
#MultiModel #AI
@coingecko $Polyphonic
Other AI platforms farm your data. Polyphonic puts it on-chain and lets every major model talk together. This is multi-mind AI. #Solana #Crypto #AI #Web3 #AIFreedom #MultiModel #PumpFun #Polyphonic
Andrej Karpathyβs "LLM Council" is simple: Multiple models anonymously critique each other, then a "Chairman" synthesizes the best answer.
At QSynaptiX, weβre actively following this shift toward orchestrated reasoning and LLM council.
#LLMCouncil #AndrejKarpathy #MultiModel
De berekende sneeuwval en verdeling adhv #multimodel tm zondagochtend. Een groot voordeel van het multimodel is dat extreme resultaten van één model de prognose niet vertekenen. Het multimodel zal daarom nooit een afwijkende variant van deze parameters weergeven en kan dienen als een goed startpunt voor meer gedetailleerde analyses.
Zie ook https://t.co/RkFZhe0fYe
Arcade 25.10.1 is out! Python Bindings for embedded use, significant query and indexing enhancements, bug fixes, SQL/Cypher compatibility, and much more #multimodel #graphdb https://t.co/5n82rc8NDz
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