Accelerate inference, model shaping, and pre-training on a research-optimized platform.
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Together AI retweeted
Our serverless APIs for open weights models have become exquisite machinery (that we plan to write more about soon!)
One effect is that @togethercompute now one of the largest originators of open tokens in the US, with a wild week over week growth curve that reflects the pace of OSS adoption. Will serve 1.8T tokens today on @OpenRouter alone.
You can get started with $5 — api.together.ai
openrouter.ai/provider/toget…
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Reliable, fast inference is essential. As Ted shared at Apsara Conference 2026, Together makes it easy for teams to get access to frontier open models without needing to manage any of the infrastructure complexity.
See for yourself api.together.ai
Making AI simpler for businesses.
At #ApsaraConference2026, Ted Cui, VP of Engineering and Inference Platform at Together AI, spoke about AI becoming more accessible, with model selection becoming less of a concern for businesses.
Find out more: click.alibabacloud.com/m/200…
#AgenticEra #AgentNative #AIAgentsAtApsara #BringYourAgent #AlibabaCloud
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Just trained Tev1 0.8B, a tiny Jev-like classifier.
Here it is running completely locally on my mac with @ollama & classifying some tasks.
It's extremely fast: only ~50ms E2E latency. Video is not sped up!
Releasing weights & benchmarks very soon so you can try it yourself :)
Announcing tev1-4B-experimental, a Jev-like classifier finetuned on top of Qwen3.5 4B for only $17.
I'm releasing everything: the weights, data recipe, & a full tutorial on how to train your own.
You can try it today on Together serverless at $0.042/1M input & $0/M output.
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"We discovered early on that it's really hard to reliably deploy AI in the real world. Frontier models are really strong, but they're really slow for real-time use cases."
See how @DecagonAI partners with Together to power its voice AI concierge.
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Note that this is an experimental model meant to show how you can train your own specialized decision models fairly easily!
You can also check out the model weights here, along with the full tutorial on finetuning your own classifiers above:
huggingface.co/togethercompu…
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Qwen3.7-Max and Qwen3.8-Flash from @Alibaba_Qwen are now 40% off on serverless through September 30.
Use Max for long-horizon agent work and Flash for high-volume, cost-sensitive workloads.
Get started today! api.together.ai
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New on Dedicated Model Inference: canary rollouts.
Upgrade the model behind a live endpoint without downtime. Traffic moves from your current deployment to the new checkpoint in gated steps (default 5% → 25% → 50% → 100%).
Health checks run before any traffic shifts. After every step, metric gates compare the new model's p95 latency and error rate against the old one. If a gate trips, the rollout pauses at the canary share and waits for you: resume, promote to 100%, or roll back.
Three strategies: canary, blue-green, and rolling. Available now via the tg CLI, REST API, and Python SDK.
Learn how to start a rollout: together.ai/blog/canary-roll…
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Introducing theopenfrontier.com!
Figure out which open model is best for your use case.
Compare models across coding, agents, long context, vision, finance, and more.
Then see how they compare on cost + quality, including what you could save by moving to open models.
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coding agents are moving fast from prototype to production. the infrastructure question is what's left.
join @parthsareen from @ollama and @zainhas Hasan from Together AI at @AIconference for a breakout on what it actually takes to build coding agents on open models, and run them at scale.
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This week in London, we got into the real economics of running AI in production.
Cost, model selection, routing, reliability. Straight talk from teams doing this at scale.
Thanks to @MiniMax_AI, @deel, and everyone who joined us. Until next time.
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deepseek v4.1 flash on together ai is leading on ttft for pre-warmed queries
for agent workflows, that startup time shows up again on every model turn, so shaving it down matters more as the loop gets longer
we’ve been pushing hard on the serving path to keep that overhead as low as possible
omg @togethercompute I love you. this is time to first token for every provider for Deepseek v4.1 flash. you guys CRUSH on pre-warmed queries. there's no other game in town
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Together AI retweeted
Together AI just raised $800M at an $8.3B valuation.
I got their product team to open up the actual repo they run on:
0:00 - Slop is the new party foul
1:44 - Why individual output backfired
3:26 - Inside the shared product repo
8:57 - Who owns the context files
10:41 - Team skills vs personal skills
11:57 - Picking a harness and a model
15:17 - Feature research running live
16:57 - What stays human in the loop
19:56 - The PRD skill that interviews you
23:09 - Half a day of research in 5 min
24:25 - Their customer insights MCP
27:31 - What a good PRD looks like now
32:02 - Reading the finished PRD
35:07 - Every repo in one place
40:24 - Context is a hierarchy, not a pool
41:20 - Build your own orchestrator
44:19 - Agent evals on shipped features
49:41 - Design validated every few hours
52:26 - Where PM ends, engineer begins
55:10 - What it actually cost them
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minimax h3 is now live on together ai
the 33b omni-modal video model generates 4–15s clips at up to 2k with native stereo audio, using text, images, video + audio as context
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try it now: together.ai/models/minimax-h…
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How do you actually shortlist an open model for production?
Rochelle Mattern, our Head of Field Engineering, is tackling that at @AIconference. Real evaluation criteria, not leaderboard vibes.
Worth clearing your calendar for.
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