Together AI
@togethercompute
Accelerate inference, model shaping, and pre-training on a research-optimized platform.
277 Following64.7K Followers3.2K Posts
- Together AI@togethercomputetogether gpu clusters can now take a node from gpu fault to healthy again automatically health checks identify the failure, the platform chooses the lightest repair, and you decide what can run unattended, down to individual xid codes here’s how it works41132.5K
- Together AI@togethercomputeTwo companies, one goal: open models that work for builders at any scale. @jmorgan of @ollama and @vipulved of Together AI on where open models win, how to spend tokens wisely, and what developers want next. 📽️:
33144.6K - Together AI@togethercomputethe open model stack is becoming composable model → inference → gateway/router → harness → tools each layer can evolve independently, so you can swap in better models, providers + tools as the ecosystem moves we broke down the full stack ↓
72232.7K - Together AI@togethercomputeminimax m3.1 flash beats opus 5.5 on agentic automation at ~27x lower cost the model has a 1m context window + vision support, and is built for coding, computer use + cybersecurity
144413.1K - Together AI@togethercomputeWe are LIVE with @AIatMeta to dive into Muse Spark Open!Together AI @togethercomputeEverything you need to know about Muse Spark Open: A conversation with Meta and Together AI11152.3K
- Together AI@togethercomputeEverything you need to know about Muse Spark Open: A conversation with Meta and Together AI45234.4K
- Together AI@togethercomputepost-training gets better the faster you can iterate multiple lora experiments can share the same gpu capacity on together post-training, so you can test more ideas without spinning up new infrastructure for every run
81192.1K - Together AI@togethercomputeminimax m3.1 flash is now available for post-training on together ai run sft or rl with your own data, rewards + environments, while keeping the training loop in your own python code take m3.1 flash and shape it for the agentic workload you need
389828.2K - Together AI@togethercomputeOpen models in production. Inference at real scale. Cost per token that makes finance smile. That was the energy at GTC Berlin. Customer and partner sessions, Kaffee Inferenz, Open Haus Berlin, and a night at Untergrund. Thanks to every builder who came through.214453.2K
- Together AI@togethercomputeTogether AIRT @zhyncs42: Great to see Factory using Reflection’s Beam model through Together AI. A win-win for all three teams, and a great example of the open AI ecosystem working together.Together AI @togethercomputefactory got early access to beam through together before launch they used that window to test @reflection_ai's model on real coding + agentic workflows, including tool-error recovery, conflict handling + final repo verification by day 0, @FactoryAI already knew how beam behaved on the work that matters to their customers040492
- Together AI@togethercomputefactory got early access to beam through together before launch they used that window to test @reflection_ai's model on real coding + agentic workflows, including tool-error recovery, conflict handling + final repo verification by day 0, @FactoryAI already knew how beam behaved on the work that matters to their customers
96336.2K - Together AI@togethercomputeTogether AIRT @nutlope: Everything you need to know about MiniMax M3.1 Flash → Now live on @togethercompute!MiniMax (official) @MiniMax_AIMiniMax M3.1 Flash weights are now public. 428B parameters total, 23B activated per token. Agentic performance: A generational leap in agentic tasks, coding, and cybersecurity — 76.2 on BankerToolBench, 73.7% on DeepSWE v1.1, 61.7 on OSWorld V2, 29.6 on Agents' Last Exam, and 82.2 on CyberGym. Efficient by design: MiniMax Sparse Attention and DSpark speculative decoding improve inference efficiency. Hugging Face: ModelScope: API: M Plan: MCode for desktop:030439
MiniMax (official)@MiniMax_AIMiniMax M3.1 Flash weights are now public. 428B parameters total, 23B activated per token. Agentic performance: A generational leap in agentic tasks, coding, and cybersecurity — 76.2 on BankerToolBench, 73.7% on DeepSWE v1.1, 61.7 on OSWorld V2, 29.6 on Agents' Last Exam, and 82.2 on CyberGym. Efficient by design: MiniMax Sparse Attention and DSpark speculative decoding improve inference efficiency. Hugging Face: ModelScope: API: M Plan: MCode for desktop:1742653.9K416K- Together AI@togethercomputeminimax m3.1 flash is now live on together ai we’re excited to be a day-0 launch partner for the model, aka space bunny m3.1 flash is built for agentic tasks, coding, computer use + cybersecurity, with a 1m context window and vision support try it now
1273716.5K - Together AI@togethercomputeTogether AIRT @deel: Better AI for global work starts with better training. Deel’s Pangaea K1 model is trained on 43,500+ pages of expert knowledge and fine-tuned on @togethercompute. The result: faster, more accurate answers for teams everywhere. Thanks for the partnership.Together AI @togethercompute.@deel’s data science team went from setup to real rl experiments on together post-training in a couple of hours they then ran up to five experiments at once on the same gpu capacity more experiments per gpu means a much faster iteration loop070486
- Together AI@togethercompute.@deel’s data science team went from setup to real rl experiments on together post-training in a couple of hours they then ran up to five experiments at once on the same gpu capacity more experiments per gpu means a much faster iteration loop
65235.3K - Together AI@togethercomputetogether post-training keeps the training loop in your hands your code defines the data, rewards, loss, optimizer + lora or full weights. gpu setup and the hard infrastructure are already handled start from a recipe 👇
123352.8K - Together AI@togethercomputeMuse Spark Open is the most capable US open-weight model to date, and it’s live on Together AI. Join @AIatMeta and Together for a live technical deep dive: what Meta built, and how we serve it in production. 🗓 Mon, Oct 26 · 12 PM PT / 3 PM ET Register →
43162.3K - Together AI@togethercomputegreptile wants to validate every piece of software on the planet as more code gets written by ai, the first review pass needs to be independent + fast. greptile’s v5 agent spins up sub-agents on every pr, pairing open + frontier models so one model’s blind spots don’t decide what gets caught together ai powers part of the inference behind those open models, helping reviews come back faster and at lower cost watch how @greptile does it164567.6K
- Together AI@togethercomputesf, join us this thursday for step 5 preview launch night with stepfun we’ll dig into the model, building + serving agent workloads, and what’s worth building as models keep improving, with dan fu, hongyu zhou, mar hershenson, saoud rizwan, joey wang rsvp:
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