Together AI
High-performance inference for open-weights LLMs
Overview
Together AI provides high-performance inference infrastructure for open-weights LLMs — Llama, Mixtral, Qwen, DeepSeek and 200+ others — via OpenAI-compatible API. Strong on price-performance for production inference workloads; also offers fine-tuning and dedicated endpoints for enterprises that need predictable latency.
Use cases
What you can produce with Together AI
- Call 200+ open-weights models such as Llama 4, DeepSeek R1 and Qwen3 through an OpenAI-compatible API, often by changing only the base URL and model name in existing code.
- Fine-tune an open-source LLM on your own dataset via the fine-tuning API, then deploy the resulting custom model to a serving endpoint.
- Spin up dedicated GPU endpoints for a specific model so production traffic gets predictable latency instead of shared serverless capacity.
- Rent H100 and newer GPU clusters on-demand or reserved for large-scale training and batch inference workloads.
- Generate images with hosted FLUX models and transcribe audio with Whisper through the same unified API and billing account.
- Benchmark and swap between models for price and quality without rewriting application code, using the shared API surface across the whole catalogue.
ASEAN Perspective
Together AI in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
Together AI is a developer-focused cloud for running, fine-tuning, and training open-source models (Llama, DeepSeek, Qwen, Flux, and many more) with an OpenAI-compatible API, competitive pricing, and strong inference performance. For teams building on open models, it's one of the most capable and cost-effective platforms, with good docs, broad model coverage, and dedicated GPU options for scale.
It's squarely a builder's tool, not an end-user app, so non-developers get little from it directly, and as a fast-moving infrastructure player, model availability and pricing shift over time. Hosting is US/Western-centric with no SEA data residency, which regulated regional buyers should weigh. Excellent for developers and startups wanting flexible, affordable open-model inference and training behind a clean API.
What people say
Together AI has grown from a well-regarded open-source inference shop into one of the biggest independent AI clouds. In July 2026 it closed an $800 million Series C led by Aramco Ventures at an $8.3 billion valuation, with analysts estimating it crossed roughly $1 billion in annualised revenue earlier in the year. The platform now hosts 200-plus open-weights models — DeepSeek V3 and R1, Llama 3.3 and 4, Qwen3, FLUX image models, Whisper and more — behind an OpenAI-compatible API.
What developers consistently praise is exactly what the company markets: speed and price-performance. Reviewers describe inference as noticeably snappier than rival serverless platforms, and serverless token pricing ($0.03 to $4.50 per million tokens depending on model) routinely undercuts both proprietary APIs and running equivalent models on the big hyperscalers. The OpenAI-compatible endpoint makes switching from GPT-based stacks close to trivial, and the fine-tuning pipeline gets credit for letting teams adapt open models on their own data at reasonable cost.
The complaints cluster around accessibility and billing. This is unambiguously a developer product: users who are not comfortable with APIs report being lost, and documentation is described as thin in places. Usage-based billing draws the familiar gripe that careless testing or fluctuating traffic produces month-end bills far above expectations, and some reviewers note the true cost of ownership includes non-trivial integration engineering. A few also wish more models were available on the free tier.
Together AI genuinely fits engineering teams putting open-weights models into production — startups chasing lower inference bills, researchers who need GPU clusters, and enterprises wanting dedicated endpoints with predictable latency. It is a poor match for non-technical users or anyone expecting a polished no-code experience; those buyers are better served by app-layer products built on top of platforms like this one.
Summary of public user & expert reviews, compiled by RECATOOLS.
About this listing
This entry was compiled from publicly available data including Together AI's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Together AI unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
For the latest details, please refer to Together AI directly →
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