Search: “together-ai--x”

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

Qwen3.8-Max is live on Together AI on day zero. Proud to have supported early testing alongside @Alibaba_Qwen, @vllm_project, and Inferact to get day-zero support live. We’re continuing to optimize pe

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

DeepSeek V4 Flash 0731 is now available to fine-tune on Together AI. Specialize it for coding, tool use, and your own domain with SFT or DPO, then deploy the fine-tuned model on Together AI for produc

In August 2026, Together AI entered into a multi‑year partnership with IBM and NVIDIA to deliver enterprise‑grade open‑source AI inference on IBM Cloud. The collaboration deploys a dedicated NVIDIA B3

Nemotron 3.5 Lightning is available on Together AI through Dedicated Model Inference, giving teams reserved capacity and predictable performance for high-volume agent workloads. Start building: https:

NVIDIA’s Nemotron 3.5 Lightning—a fast open AI model designed for always‑on agents that perform high‑volume, specialized work—has been launched on the Together AI platform as of 11 August 2026. NVIDIA

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

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

Frontier performance you can actually own. Proud to help power DeepSeek-V4-Flash on Ollama's cloud, with the fastest hosted performance available. Open weights, zero data retention, U.S. & EU hosting.

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

We compared how far the same budget goes with DeepSeek V4 Flash and GPT-5.6 Luna on DeepSWE. Two DeepSeek V4 Flash attempts solved MORE tasks than one Luna attempt at roughly one-third the cost. Media

Researchers from TogetherAI analyzed DeepSeek V4 Flash and GPT‑5.6 Luna on the DeepSWE benchmark. The study found that employing a DeepSeek‑first cascade with test‑suite verification solved more tasks

When you move a model into production, you want the quality you evaluated to carry through the serving stack. @Kimi_Moonshot benchmarked Kimi K3 across major inference providers, and Together AI ranke

A lot of the questions we get from developers are about the concepts behind the API: TTFT, context windows, sampling, fine-tuning, quantization, deployment tradeoffs. We added Learn to the Together do

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

We analyzed DeepSeek-V4 Flash-0731 vs. GPT-5.6 Luna on software engineering tasks using DeepSWE. DeepSeek-V4 Flash-0731 delivers 80% of Luna’s performance at roughly 1/6 the cost. More insights in the

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

FLUX 3 is now live on Together AI. @bfl_ai’s new multimodal model generates video and synchronized audio together, with up to 20-second clips, multiple shots, and control from text, images, or keyfram

Open models give teams more room to run agent loops, with API prices at a fraction of GPT-5.6 Sol and Claude Fable 5. That matters as planning, tool calls, retries, and long contexts compound token us

Together Serverless Inference gives developers a managed production path for bringing FLUX 3 into creative products and automated media workflows. Start building: https://www.together.ai/models/flux-3

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

DeepSeek V4 Flash is now live on Together AI. Frontier agent performance is getting dramatically cheaper. DSV4 on Together AI brings a major jump in coding, tool use, and long-running agent performanc

Together AI gives developers a high-throughput production path for running DeepSeek V4 Flash across coding, tool-use, and agentic workloads. Start building: https://www.together.ai/models/deepseek-v4-

Kimi K3 has set a new bar for OSS model intelligence! 2.8T params, 1M context, OpenAI-compatible API. Complete guide to running Kimi K3 on Together AI 👇 👏👏 @Kimi_Moonshot 👏👏 https://www.together.ai/bl

Inkling-Small is now live on Together AI. @thinkymachines’ new open-weight multimodal model delivers similar performance to Inkling at one-quarter the size, built for coding, agents, and general multi

The first thing we learned building autoscaling for dedicated inference is that CPU-style metrics don't tell the whole picture. A GPU can read 60% busy while the engine's queue is already backing up,

Together AI gives developers a high-throughput production path for running Inkling-Small on @NVIDIAAI Accelerated Infrastructure across multimodal, coding, and agentic workloads. Start building: https

Together AI gives developers a high-throughput production path for running Inkling-Small on NVIDIA Accelerated Infrastructure across multimodal, coding, and agentic workloads. Start building: https://

Osmosis_AI claims that an open‑source model can rival a foundation model by leveraging reinforcement learning techniques. To demonstrate this, they will use the Y Combinator‑dedicated GPU cluster on T

Interesting data from the OpenRouter Kimi K3 dashboard: @togethercompute offers one of the lowest prices for @Kimi_Moonshot K3 while also achieving one of the highest prompt cache hit rates. Low prici

Starting in 15 minutes Kimi K3 has everyone’s attention. On July 30, hear @Kimi_Moonshot's Feihu Tang explain the architecture and decisions behind it. He joins Jue Wang and Zain Hasan from Together A

Agentic inference wastes GPUs on KV cache thrashing. ThunderAgent fixes it at the scheduler level: 2.5x higher single-node throughput and ~10x lower P50 latency at high concurrency. ThunderAgent was a

It's a drop-in. One program_id field and it plugs into your existing engine configs such as KV offloading + speculative decoding. Format-agnostic by design, with OpenAI chat completions supported toda

Packed house today at the first edition of our @MiniMax_AI Intelligence in the Open event. Thank you to our amazing cohost @withprotegeai And our wonderful partners UpscaleX @togethercompute @Artifici

The problem: agent workflows alternate between GPU-heavy reasoning and GPU-idle waiting on tools. Run hundreds concurrently and their KV caches fight for memory. Engines evict on a dumb LRU policy, ev