Knowledge catalogue
fyi @FireworksAI_HQ launched inference AND training for K3 on day 0. having 'specialized intelligence' isn't just inference, it's inference + training, together. That's why K3 on Fireworks offers both
Kimi K3 is now available on @digitalocean 's Serverless Inference! Developers can start building with our most capable model in minutes. .@Kimi_Moonshot K3 from Moonshot AI is now live on DigitalOcean
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
Next YC Paper Club: Inference Inference is no longer just: y = model.forward(x) It has now become as complex and important as training. The difference between naive inference and well tuned could be 1
Inference is becoming the largest compute market and energy consumer in AI. Pearl turns inference CapEx of hyperscalers into a profit center: every LLM token produced by GPUs can simultaneously genera
A milestone for Pearl Research Labs: our first major enterprise partnership is live with Together AI. @togethercompute’s inference platform is an ideal demonstration of @prlnet's value proposition — O
Minimax M3 is a remarkable model in many ways, but esp for inference efficiency. Minimax model designers and @togethercompute inference team will discuss it tomorrow live. MiniMax M3 is live and Toget
Many research labs only consider inference efficiency after the fact. Step 3.7 Flash is a 196B MoE model, and built for inference from the start by @StepFun_ai. Multi-Matrix Factorization Attention (M
Together AI has long been a proud supporter of open-source innovation in inference. We're excited for the new TokenSpeed inference engine, available in preview today with MIT licence, and can't wait t
We’ve developed our own inference engine Runtime-Optimized Serving Engine (ROSE) to serve models ranging from embeddings to trillion-parameter LLMs. With CuTeDSL integrated into our inference engine,
Sam Altman praises the inference team's work on efficiently serving a model, suggesting that becoming proficient in AI inference is crucial to the field's progress. The post appears to highlight the t
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
2/ New deep dive: Autoscaling endpoints for LLM inference. Dedicated Inference can scale on eight metrics. inflight_requests is the default because it sees queue pressure before latency degrades. We t
Together Serverless Inference gives developers a high-throughput, managed production path for running Muse Glimmer across agentic and multimodal workloads. Start building: https://www.together.ai/mode
***Lights, inference, action…*** I’m so happy to share that @sequoia has led the Seed in @previewio. Developers are flying in magical AI-native editors. But creative tooling is still stuck in the pre-
Together Serverless Inference gives developers a managed, high-throughput path for running Qwen3.8-2.4T-A95B across coding and agentic workloads. Start building: https://www.together.ai/models/qwen3-8
Behind the MiMo API Price Reduction: The deepest price cut, up to 99%, is for Input (Cache Hit). The core reason is our inference framework now supports hierarchical KV cache optimization for SWA. Pro
@AIatMeta Together Serverless Inference gives developers a high-throughput, managed production path for running Muse Spark Open across agentic coding and multimodal workloads. Start building: https://
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
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
Inference scaling part 1. Starting with a modded text generation function (temperature scaling, top-p filtering, multinomial sampling) to generate diverse outputs for self-consistency and best-of-N (i
Live now: our Inference Engineering Track from AI Engineer World's Fair 2026. A benchmark tool told to run 200 queries a second that ran 38 and reported 200. A model that answered one prompt in a thou
Since announcing Jalapeño, our first custom inference chip, we’ve been testing it and the system around it. The results show a major advance: more intelligence from every watt and faster responses, de
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
Leveraging the frontier ecosystem We work with neolabs like @trajectorylabs and @EngramLab and inference + post-training infra providers like @baseten, @FireworksAI_HQ, and @appliedcompute to post-tra
Together AI is teaming up with @IBM and @nvidia to bring enterprise-grade AI inference to IBM Cloud. A dedicated NVIDIA B300 cluster. Spectrum-X networking. First of its kind on IBM Cloud, powered by
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
Today’s LLMs still write like typewriters: one token at a time. This sequential process creates a hard inference bottleneck. We're introducing Uno, a diffusion-augmented LLM that delivers autoregressi
ai is the ultimate grow the pie event cheaper inference = better gross margins for application companies, AND beautiful cohort expansion for model and inference companies Sequoia Capital GP @sonyatwee
This is what strong inference economics unlock. @rox_ai built its own search agent, ran it in production for 6+ months, and reached 91.3% accuracy at 1.03¢ per query. Together AI is proud to help powe
Big unlock for open-source AI inference: Hugging Face Transformers models can now run in vLLM at native speed, often matching or beating hand-written implementations. Until now, every new architecture
This post likely discusses FireworksAI's fast inference capabilities and their implications or surprising effectiveness in the AI inference space. The post is from Sonya Huang, associated with SemiAna
ThunderAgent is an agentic inference system designed for fast and efficient execution of AI agent programs, developed by Together AI. The system appears to optimize program-aware inference by leveragi
PSA: Just added a few thousand chips, including B200s and B300s to our Dedicated Model Inference (http://api.together.ai/endpoints). With Dedicated Model Inference, you can now on-click deploy our Bla
We are excited to have @baseten as a day 0 launch partner for Kimi K2.6! Their inference stack brings KV-aware routing, NVFP4 on Blackwell, multi-modal hierarchical caching, and prefill-decode disaggr
New course: Efficient Inference with SGLang: Text and Image Generation, built in partnership with LMSys @lmsysorg and RadixArk @radixark, and taught by Richard Chen @richardczl, a Member of Technical
Impressive by @river_ai_inc to beat @deepseek_ai rates - cache in particular is tough! Talented team there, full RL + inference stack should be real competition River Inference is live! We're serving
the inference platforms are doing hardcore work, post-training open weight models to solve customer problems: @FireworksAI_HQ ember-1 @fal H3 max more to come;) makes total sense considering their pos
Today we’re open-sourcing Lily, the local inference engine we built for hybrid compute in Perplexity Computer. Lily is specialized for Qwen3.6-35B-A3B on Apple silicon, built so on-device compute does
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
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
Zain (@zainhas) published a detailed article on August 7, 2026 explaining that autoscaling for highly peaky large‑language‑model (LLM) inference is fundamentally different from autoscaling conventiona
Using optimization at inference time is a foundational concept of Energy-Based Models (EBM) and Objective-Driven AI architectures (ODAI). When the variables to be inferred are continuous, it makes sen
who wants to help eyal poke holes in this approach to run LLM inference... in browser? Looking for peer reviewers 🧪 Built an LLM inference engine in pure WebGPU/WGSL. Runs in browser and Node, on-devi
Agentic coding changes what inference engines need to handle. At AI Engineer World’s Fair, Together AI engineers will lead a hands-on workshop on how inference engines work and what it takes to serve
Many research labs only consider inference efficiency after the fact. Step 3.7 Flash is a 198B sparse MoE VLM designed by @StepFun_ai for inference from the start. 196B language backbone with a 1.8B v
Excited to speak at PyCon US @pycon about production LLM inference systems, runtime optimization, and next-gen engine design — including some of the new ideas behind the recently open-sourced project
Instead of the gold standard, we can imagine an inference standard of exchange, the FLOP. (As opposed to tokens, this accounts for AI ability) With some AI help, I figure 1 buys roughly 10^17 managed-
ICYMI from yesterday's @dealbook: inference startups are ripping as enterprises continue to adopt AI - @togethercompute's annual bookings hit 1.2 billion as of July - @FireworksAI_HQ crossed 1 billion
if you’re building an ai app, you might want to host inference to improve your margins, and if you do that you should support a few models, and if you’re doing that you might as well build a router, a
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
Counterpoint: “If alignment issues are becoming big enough that OpenAI is willing to commit 20% of research inference compute to chain-of-thought monitoring [suggesting] that suggests that alignment i
Qwen3.8-Max is live on DigitalOcean Serverless Inference. Launching side by side with DigitalOcean as our Day 0 launch partner. Big model. Smooth sailing. Now on DigitalOcean.🌊🏄♀️ @digitalocean Now a
Congrats to @mattrubens and the Roomote team on the launch. Builders can use Together AI as an inference provider in Roomote and assign different open models to coding, planning, vision, and review ac
99.9% uptime changes what your inference architecture has to survive. At Together AI, it means multi-data-center deployment, live traffic across both facilities, and enough capacity to absorb a full d
.@Kimi_Moonshot benchmarked K3 endpoints across major inference providers. Together AI leads or ties for #1 on 3 of 4 benchmarks: OCRBench, MMMU Pro Vision, and DeepSWE. Open models like Kimi K3 have
An interesting way to take Noam at his word in regards to always keeping a constant inference budget for any eval reporting - is that open models have a lot more dollar per token mileage than closed m
The next generation of inference needs purpose-built infrastructure. Together AI and 5C are deploying NVIDIA GB300 NVL72 systems with high-density compute, advanced cooling, and AI-optimized storage f
DeepSeek Inference Analysis Day 0 GB200 NVL72, Blackwell, AMD MI355X Huawei performance analysis Performance every day over time for the past 44 days DeepSeekV4 1.6T Day 0 to Day 43 Performance Over T
For browser-use AI agents, every task is dozens of model calls in a tight loop. The inference layer isn’t background infrastructure. It’s what the product runs on. @yutori_ai runs Scouts, Delegate, an