Knowledge catalogue
yesterday we took SF @Techweek_ to the water ✈️ The Science of Speed brought together founders, researchers, and builders front row for Fleet Week with @nvidia and @dtcp_capital. not to mention a gues
come hear about building with open frontier models Open Haus Berlin lineup: → @RiqwanMThamir from @n8n_io → Harry Kim from @nvidia → @zainhas from Together AI good food, drinks, and better arguments a
Together AI announced that it is expanding its enterprise‑grade inference capabilities by partnering with IBM Cloud and NVIDIA. The move leverages IBM’s cloud platform for scalable compute resources w
'It's well worth spending the money on tokens if the business is getting the benefit.' — IBM Cloud GM Alan Peacock We're scaling open-source inference with @IBM + @nvidia on a dedicated B300 cluster o
Introducing GeoGuess Bench! A benchmark to measure how good AI models are at playing GeoGuessr. We gave each model 210 photos from around the world, asked it to predict where each photo was taken, and
Congrats to the Reflection team on Beam 🎉 Be sure to join us next week at our NYC meet-up with the Reflection team and NVIDIA https://luma.com/TAIxNvidiaxReflection Introducing Beam: a highly efficien
AI researchers Zainhas and Parthsareen from Ollama delivered a breakout presentation on October 2, 2026, focusing on evaluating open-source models under real‑world production traffic rather than just
Great talk from Yogish Baliga 'From Vim (:wq) to 'You're absolutely right!'' tracing 20+ years of software engineering evolution. Highlights: 1/ open-weight models have closed the gap with closed mode
Qwen3.8-Flash is 40% off through the rest of the month, making now a perfect time to run your evals. Designed for high-volume applications like coding and coworking assistants, @Alibaba_Qwen's model o
Together is #1 on @OpenRouter token share across top open coding models, today: 🥇 @Zai_org GLM 5.3 Flash: 29.2% 🥇 @deepseek_ai V4.1 Flash: 25.6% 🥇 @Kimi_Moonshot Kimi K3: 18.9% Running coding agents o
We are proud to be launch partners for NVIDIA Open Agent Safety Platform. We believe safe and responsible AI development is critical as the use of agents scale and they get more prevalent. Together AI
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 infrastructu
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 spe
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
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 starte
We're releasing tev1-4B-experimental, a Jev-like classifier finetuned on top of Qwen3.5 4B. We're making it available on Together serverless at 0.042/M input & 0/M output. Also releasing the data reci
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
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 breako
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
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 - Insi
Deel handles compliance, payroll, and HR questions across 150+ countries. Instead of searching for the answer through an external LLM each time, they fine-tuned small models built on Deel's own compli
deepseek v4.1 flash has arrived on together ai it beats gpt-5.6 sol on agentic benchmarks at one third the cost per task the model supports a 1m context window and native multimodal input, with 552b t
DeepSeek V4.1 Flash is now available on Together AI’s model hub (https://www.together.ai/models/deepseek-v4-1-flash). The release includes the DeepSeek V4.1 Flash API with updated pricing, performance
how inference engines actually work - releasing full talk slides! i cover everything in the lifetime of a request e2e: > the inference engine > kv + prefix caching > continuous batching > paged attent
Nice stats from @OpenRouter that illustrate how @togethercompute delivers solid and scaled performance for agentic workloads. We are serving GLM 5.3 and GLM 5.3 Flash @ top decile of TPS, latency, cac
together fine-tuning now supports glm-5.3, kimi k2.7-code + more we also added live run metrics, experiment comparisons, early stopping, dataset previews + finer training controls prices are down 30–7
Together AI announced the launch of “ThunderKittens” running on the NVIDIA Vera Rubin NVL72 platform, highlighting new performance gains and future directions. The announcement was shared via their Tw
introducing preemptible compute for together gpu clusters same nvidia gpu infrastructure, 50% of the on-demand price built for evals, fine-tuning, batch inference + short experiments, with up to 5 min
This model is insane at landing pages. I asked DeepSeek V4.1 Flash & Claude Fable 5 to build me a landing page for a movie theater. Fable cost $1.21 while V4.1 Flash cost 2.6 cents, making it more tha
On September 9, 2026 Together AI announced that its new **glm‑5.3 flash** model outperforms OpenAI’s **Claude Fable 5.1** on agentic automation tasks. The benchmark also shows glm‑5.3 flash achieves a
we broke down the full open model stack for agentic coding and how to swap each layer independently model → inference → gateway/router → harness → tools the stack stays flexible as better models, prov
SF Tech Week meets Fleet Week ✈️ Oct 9: Together AI, @dtcp_capital, and @nvidia are taking over a private waterfront chalet for a front row seat to the Blue Angels. Custom aviators. Great food and dri
6 months ago, I started building an internal customer insights tool at Together AI. It pulls in our sales calls, slack channels, & support tickets and turns them into searchable customer insights. Tod
Open source is becoming the default way enterprises build with AI. Not just which model runs, but where it runs. Today we're partnering with @Equinix and @nvidia on Equinix Inference Exchange: our ope
for september, we’re cutting the price of Dedicated Inference on H100s from 5.49/hr to 3.99/hr new + existing deployments get the lower price automatically deploy gemma 4, qwen3/3.5, gpt-oss, llama, n
Excited to welcome @greptile, the AI code reviewer trusted by 11,000+ teams, as a Together AI customer. Greptile's agents review and test pull requests with full context of your codebase, and running
glm-5.3 now beats gpt-5.6 sol and claude fable 5 on agentic benchmarks 5.3 flash is right behind it glm-5.3 didn’t even need a new base model to get there @zai_org kept the glm-5.2 base and scaled pos
Together AI, in partnership with greptile, announces its AI‑powered code‑review platform that is trusted by more than 11,000 teams for reviewing pull requests within the full context of their codebase
GLM‑5.3 demonstrates a notably lower hallucination rate compared with other contemporary large language models. According to a report by Together AI at TogetherCompute (published August 30 2026), Clau
PSA: For everyone using GLM-5.3 you probably want to use this model in reasoning_effort='high' mode. > 'max' - 34% for 77k tokens (not bad!) > 'high' - 32% for 50k tokens But 'max' is not as unusable
GLM-5.3 has arrived on Together AI on Day 0 @Zai_org pushed the GLM-5.2 base further with scaled post-training, delivering stronger coding and long-horizon agent performance. Across benchmarks, it nea
Mahadev Konar co‑hosted a 2‑hour live broadcast titled “Amazing deep dive on K3!!” with Together Compute. The session explored scaling the Kimi K3 language model for inference, detailing deployment st
Research from August 2026 indicates that GLM‑5.3‑Flash (also called Ox Alpha) delivers a 63 % performance score at 0.24 per task, which is more cost-effective than DeepSeek‑V4 Flash 0731 (53 % at 0.46
Together AI announced a broadcast titled “Serving Kimi K3 at scale: An inference deep dive” scheduled for 7 pm on August 26, 2026 (UTC‑adjusted time shown via X’s timestamp formatting). The streamed s
Compute has always been core to the @VerneRobotics story. Getting there meant negotiating long, expensive contracts with big neoclouds, and projecting compute needs years into the future. Verne wasn't
Qwen3.8 27B is now available for both fine-tuning and Dedicated Model Inference Fine-tune it on your own data, then deploy that model on dedicated infrastructure for production, without stitching toge
Top open models by use case 👇 chat - Kimi K3, Qwen3.8 2.4T A95B reasoning - Kimi K3, DeepSeek V4 Pro coding agents - Kimi K3, DeepSeek V4 Flash, GLM 5.2 small + fast - Qwen3.8 27B, gpt-oss 20B mid-siz
Be sure to tune in this Wednesday! Inference Hours is back with another Kimi K3 webinar! On Wednesday, August 26, Zain Hasan sits down with Kevin Cui and Austin Silveria from Together AI's inference t
Inference Hours is back with another Kimi K3 webinar! On Wednesday, August 26, Zain Hasan sits down with Kevin Cui and Austin Silveria from Together AI's inference team on how we actually serve K3 in
Web agent economics are set by inference volume and each step is one inference call. A simple task (extract a field, fill a form, navigate a site) is 10 to 20 calls. A multi-site workflow runs into th
Brex’s summer benchmark shows how quickly the infrastructure behind the agent economy is growing. 14 of the 25 fastest-growing software vendors serve teams building AI products, and Together AI ranks
Relace.ai develops purpose‑built small models optimized for code generation. These models run on Y Combinator‑backed GPU clusters hosted by Together AI, achieving substantial cost savings compared to
This model is insane at 3D website design. I asked GLM 5.3 (left) & Fable 5 (right) to make me a 3d biking website. GLM nailed it while Fable failed. GLM cost 0.14 while Fable cost 2.21. More than 15x
DeepSeek V4 Pro (Aug 2026) has been released on the Together AI platform. The model employs a 1.6‑terabyte Mixture‑of‑Experts architecture with a 1‑million‑token context window and supports three dist
Fantastic initiative by @nvidia. “Circular financing” is thrown around as a pseudo intellectual gotcha, while everyone in the AI infrastructure business is witnessing demand curves that are so rapidly
Yutori's browser-use agents run in tight loops: screenshot, action, repeat, dozens of times per task. On Together AI, their Navigator model beats frontier performance at 2x faster inference and 4-5x l
We analyzed DeepSeek-V4 Pro 0813 against GPT-5.6 Sol and Fable 5 on software engineering tasks using DeepSWE. DeepSeek-V4 Pro 0813 reaches 88.5% pass@4 while costing 0.24 per task, 35x less than Sol a
Qwen3.8-2.4T-A95B is live on Together AI. The Qwen team’s new open-weight MoE packs 2.4T total parameters with 95B active, a 1M context window, and strong coding & agent capabilities. Start building:
10,000 @nvidia B300 GPUs. India's largest AI Factory. Together AI and @larsentoubro are building the country's biggest GPU cluster, backing open-source inference, fine-tuning, and training at scale fo
The Qwen Team has released its flagship model, Qwen3.8‑2.4T‑A95B, on the Together AI platform (togethercompute) as of August 12 2026. This 2.4‑trillion‑parameter model is engineered for coding tasks a