⚡Stack Radar

Inference APIs · Reviewed 19 Oct 2026

Together AI

Full-stack AI cloud for building, fine-tuning, and deploying open-source models.

free tier · together.ai ↗

Paid against free › Inference APIs › Together AI

Together AI at a glance

SEO analysis

Collected Oct 19, 2026

together.ai: an estimated 998,181 total monthly visits and about 33,409 monthly organic visits across 6,240 ranking keywords. Scout crawled 15 pages and measured a technical health score of 97/100.

998.2KEstimated total trafficModeled monthly visits6.2KRanking keywordsPublic search sample97/100Technical health15 pages checked14.7KReferring domainsLive backlink summary

Overview

01

Summary

The useful answer before the supporting detail.

Together AI is a full-stack AI cloud platform for building, fine-tuning, and deploying open-source AI models, from inference to GPU clusters S5. It serves developers and enterprises that need production-ready AI infrastructure without managing underlying hardware S5 S18. The platform provides serverless and dedicated inference, fine-tuning, and GPU clusters, with APIs compatible with OpenAI for easy migration S18 S81.

02

Product identity and positioning

Name, category, positioning, audience, and first-party claims.

  • Identity: Together AI, an AI Native Cloud platform S1 S18.
  • Core purpose: Provides full-stack infrastructure for building, fine-tuning, and deploying open-source AI models S5.
  • Intended users: Developers and enterprises running production AI workloads S5 S81.
  • Product scope: A platform offering inference, fine-tuning, GPU clusters, and sandboxes S5.
  • Positioning: Full-stack AI platform powered by cutting-edge systems research S1.
  • Claimed distinction: Research-optimized platform with superior unit economics S1 S5.
03

Use cases and audiences

Who the product serves and the jobs it is designed to handle.

AudiencePractical use case
DevelopersBuild and deploy AI applications using open-source models via API S5 S87.
EnterprisesRun GenAI securely in production with dedicated infrastructure S81.
Voice teamsDeploy real-time voice agents with low latency S51.
Research teamsAccelerate model training and inference with optimized kernels S5 S103.
Customer supportAutomate support with AI chatbots and virtual assistants S81.

Features

09

Features and capabilities

Core functions and evidence-backed product capabilities.

CapabilityWhat it does
Serverless inferenceRun open-source models on demand with per-token pricing S5 S43.
Dedicated endpointsDeploy models on dedicated GPU infrastructure with guaranteed performance S5 S43.
Fine-tuningFine-tune open-source models for production using LoRA or full training S5 S78.
GPU clustersProvision GPU clusters for training and serving, from self-serve to thousands of GPUs S5.
Code sandboxesCreate secure VM sandboxes for AI app development and testing S5 S43.
Batch inferenceProcess large volumes of requests asynchronously at lower cost S5 S151.
Voice APIDeploy real-time voice agents with low-latency models from multiple providers S51.
10

Integrations and ecosystem

Connected products, exports, APIs, and workflow compatibility.

Integration or interfaceTypeWhat it enables
OpenAI-compatible APIAPIDrop-in compatibility for production workloads S81.
Python SDKSDKProgrammatic access to platform features S78.
Voice model providersIntegrationAccess MiniMax, Rime, Deepgram, OpenAI, Cartesia through a single API S51.
AWS MarketplaceIntegrationPurchase Together AI via AWS Marketplace S81.
Hugging FaceIntegrationEnhanced integrations for fine-tuning S78.
KubernetesIntegrationPreemptible compute nodes with Kubernetes events S74.

Pricing

11

Pricing and plans

Published plans, free access, trials, credits, and pricing limitations.

Plan or offerVerified price and billingIncludedLimits
Serverless inferencePer model, per 1M tokens S43Access to open-source models S18Batch API price listed per model S43
Provisioned throughputPer model, reserved S43Dedicated capacity S43Not established
GPU clustersPer GPU hour, reserved or on demand S43Training and serving S43Not established
Fine-tuningPer training token, per 1M tokens S43Training and validation data S78Serve the result S43
Free credits$25 free credits for new users S60Not establishedNot established
Preemptible computeHalf the price of on-demand S74Same compute S74Ephemeral, no minimum lifetime S74

Competition

12

Competitive landscape

Domains competing for the same organic search demand.

Sampled competitors

CompetitorFirst-page appearancesSampled queriesAverage positionQueries observed
reddit.com222.5together ai, llama coder
lablab.ai111together ai
llamacoder.together.ai111llama coder
newcomer.co112together ai
about.fb.com113llama coder
together.fund114together ai
youtube.com114llama coder
instagram.com115together ai
linkedin.com115llama coder
sacra.com116together ai

Website intelligence — Collected evidence

Customers, testimonials, and first-party review claims

No supporting public-page evidence was collected for this category.

Independent review sources discovered

No links to supported independent review platforms were discovered on the collected pages.

14

AI visibility

Measured ChatGPT and Google AI mentions with cited sources.

AI-assistant referral traffic

  • Estimated current generative-AI referral share: 2.7%
MonthSource
—All AI assistants
—All AI assistants
—All AI assistants

Website intelligence — Collected evidence

Site-stated AI capabilities

Page typeEvidenceSource
otherBuild what's next on the AI Native Cloud. Full-stack AI platform for inference, fine-tuning, and GPU clusters — powered by cutting-edge research.https://www.together.ai/
otherFull-stack AI platform, powered by cutting-edge research.https://www.together.ai/
otherThe Together AI Platformhttps://www.together.ai/
otherGPU infrastructure purpose-built for generative media workloads. Deploy video, audio, and image models with performance acceleration powered by Together Research.https://www.together.ai/
otherUse fast, secure code sandboxes at scale to set up full-scale development environments for AI apps and agents.https://www.together.ai/
otherHigh-performance managed storage for AI-native workloads. Object storage and parallel filesystems optimized for AI, with zero egress fees.https://www.together.ai/
otherFoundational systems research for production AI.https://www.together.ai/
featuresCursorhttps://www.together.ai/blog/ai-native-conf-research-and-product-announcements
featuresDecagonhttps://www.together.ai/blog/ai-native-conf-research-and-product-announcements
featuresHedra‍https://www.together.ai/blog/ai-native-conf-research-and-product-announcements
featuresThe AI Native Cloud is more than a positioning statement. It is a full-stack AI cloud that is purpose-built for AI-natives by researchers and engineers who have delivered foundational AI work such as FlashAttention and ThunderKittens. The same people who published that research are the ones running the production systems our customers, such as Cursor and Decagon, depend on. That proximity is hard to replicate. When a technique comes out of our research program, we can quickly move from research to production and ship these techniques for our customers' immediate benefit.https://www.together.ai/blog/ai-native-conf-research-and-product-announcements
featuresToday at the first AI Native Conf, we are announcing seven research and product releases across three areas: Kernels, reinforcement learning, and algorithmic inference optimization. Each one represents a massive advancement from our research-to-production pipeline for customers to use.https://www.together.ai/blog/ai-native-conf-research-and-product-announcements
featuresAn extension of ThunderKittens, together.compile generates an optimized kernel stack at startup with a single function call — no changes to model code required. When applied to Hedra's Omnia video model, together.compile accelerated generation of 200 frames by 25%.https://www.together.ai/blog/ai-native-conf-research-and-product-announcements
featuresThe production platform for open-weight AI inferencehttps://www.together.ai/blog/the-production-platform-for-open-weight-ai-inference
featuresTalk to our teamhttps://www.together.ai/blog/the-production-platform-for-open-weight-ai-inference
featuresWe're also announcing a closed beta for custom training, including full-weight and LoRA reinforcement learning and supervised fine-tuning, with checkpoints you can deploy straight to production. Request access to the custom training beta.https://www.together.ai/blog/the-production-platform-for-open-weight-ai-inference
featuresOpen-weight models now match closed models on quality, run at a fraction of the cost, and are fully customizable for your task. That combination has made them the foundation for teams building serious AI products and agents. But the strategic motivation for adopting open-weight models is still the ability to exercise control. Unlike their closed alternatives, open-weight models give teams control over performance, quality, and functionality. Many commercial AI applications have adopted a majority open-weight endpoint strategy so they can maintain complete control over their user experience. Many enterprises use this control to incorporate their valuable proprietary IP into models without risking exposure to third parties.https://www.together.ai/blog/the-production-platform-for-open-weight-ai-inference
featuresWhile open-weight model users want maximum control over performance, functionality, and quality, few teams want to test their ability to correctly align a matrix of decisions across quantization levels, parallelism schemes, engine parameters, and draft model architectures—to name just a few—on a weekly basis. Meanwhile, frontier techniques for achieving the best quality and performance are advancing just as quickly. In a rapidly evolving AI landscape, no one has the time or desire to stop and read an almanac’s worth of trivia about inference internals or a mountain of research papers—not even the teams running the world’s most successful models and agents.https://www.together.ai/blog/the-production-platform-for-open-weight-ai-inference
featuresBuild voice agents that sound natural. Combine the best STT, LLM, and TTS models on co-located infrastructure for ultra-low latency and production-scale reliability.https://www.together.ai/solutions/voice
featuresWhy Together AI for Voice Agentshttps://www.together.ai/solutions/voice

These are first-party product claims, not independent measurements of AI-search visibility.

15

Marketing opportunities

Actions calculated directly from the collected evidence.

OpportunityRecommended actionEvidence
Competitor gapReview the sampled queries where reddit.com appears.2 first-page appearances across together ai, llama coder
Technical priorityMissing page titlehttps://www.together.ai/blog/glm-5-3-vs-glm-5-3-flash-on-deepswe-cost-coding-and-routing

Website intelligence — Collected evidence

Website evidence gaps

  • customers: no usable public page was collected; verify whether the site publishes this evidence.
  • reviews: no usable public page was collected; verify whether the site publishes this evidence.
  • changes: no usable public page was collected; verify whether the site publishes this evidence.
  • identity: no usable public page was collected; verify whether the site publishes this evidence.
  • technical: no usable public page was collected; verify whether the site publishes this evidence.

Trust and proof

16

Customers, proof, and reviews

Published proof, customer signals, and review evidence.

Independent reviews

PlatformPageHow it was foundNote
RightAIChoiceTogether AI Pricing & Features (2026) / RightAIChoiceGrounded web search75 mentions across 4 sources (Hacker News, Bluesky, Stack Overflow, Lemmy) · researched Jul 6, 2026. ... 63% positive 37% critical ... - + Supports 100+ open-source models with easy API integration. - + Offers per-token pricing that is cheaper than AI modelOpus by 76%. - + Provides 31% more tokens per second than TensorRT-LLM. - + Includes free $25 credit for new users to test models. - + Managed storage with zero egress fees simplifies data handling. ... - − Pricing may be VC-subsidized and coul

Customer proof

No named customers, testimonials, or customer case studies were found.

Independent mentions

  • Personally I was testing with TogetherAI because I don't have the specs for a lo... / Hacker News — Personally I was testing with TogetherAI because I don't have the specs for a local 70b. Using quantized versions helps (Ollama's downloads 4-bit by default, you can get down to 2), but it would still require a higher-end Mac. Highly recommend Together, it runs quite quickly and is $0.9/million tokens
  • Llama 2 on togetherAI is as bad of a privacy nightmare as OpenAI / Hacker News — I was just talking to a colleague about the need for a service like this. Their pricing is much cheaper than self-hosting on AWS (ml.g5.48xlarge, needed to run 70B Lamma2, is $20.36/hr). But the TOS makes it completely unviable. If someone can figure out how to standup self-hostable, fine-tuneable models with a serverless architecture, it could be a game changer (allowing devs to use something other than AI model).
  • Together AI embeddings endpoint with higher quality, 4x lower cost than OpenAI / Hacker News — 8 leading embedding models – including models that outperform OpenAI’s ada-002 and Cohere’s Embed-v3 in MTEB and LoCo Benchmarks. Fully compatible with OpenAI API. 4x lower cost. Integrated with MongoDB, LangChain, and LlamaIndex for RAG.
  • The growth of together.ai makes a lot of sense given that 99% of current AI infr... / Hacker News — The growth of together.ai makes a lot of sense given that 99% of current AI infrastructure spend is in training (vs inference). As far as navigating the product maze, this is where you want to be in AI right now.
  • Based: Simple linear attention language models / Hacker News — Together.ai is interesting; I think it might be a relatively new business model in tech -- since they sell inference and training, you might be tempted to think of them as an engineering / infrastructure company. But, because inference is largely quality based -- e.g. customers seem to be selecting "cheapest generation at the quality I require", they have a strong incentive to optimize speed of inference at different quality points, and so this paper is coming at the market from a very different

External links were grounded in one live web search. Search snippets are leads, not independently scraped page content; rejected links remain available in Review evidence.

17

Company, security, and trust

Ownership, policies, security signals, and public trust evidence.

SignalFindingSource
Company and ownershipFounder & Chief Scientistsource
Contact and supportContact us to discuss your enterprise deployment needs. Together APIs are fully compatible with OpenAI, making testing and migration easier.source
Legal and privacyCompliance with major industry standards such as SOC 2, GDPR, and HIPAAsource
Security and complianceEnd-to-end encryption for all data, both in transit and at restsource
Uptime and status pageCommitted inference capacity with token-based pricing, reserved throughput, and a 99% uptime SLA. Drop-in API compatibility for production workloads with no infrastructure to manage.source
Domain registered2017-12-16—
Domain expires2028-02-13—

Every trust signal above is backed by a collected page or a registration record.

18

Documentation and product updates

Help resources, product guidance, and visible changes over time.

Resource or updateTypeWhat is availableDate or freshness
Contact and supportSupportPublic contact and support channel. (source)Not dated
Contact and supportSupportPublic contact and support channel. (source)Not dated
Key research and product announcements at the AI Native ConfProduct updateProduct update is publicly available. (source)Not dated
Together Fine-Tuning Platform, Now With Preference Optimization and Continued TrainingProduct updateProduct update is publicly available. (source)Not dated

Not found in the collected public sources: public roadmap, changelog or release notes, status page, separate help center or knowledge base.

Technical

19

Technical and delivery signals

Delivery model, platforms, API, data ownership, reliability claims and release activity.

SignalFindingSource
Delivery model (cloud, self-hosted, desktop, browser extension)Cloud platform with serverless and dedicated options S81.S81
Platforms and appsWeb-based platform S18.S18
API and extensibility (API, SDK, webhooks, MCP, plugins)OpenAI-compatible API and Python SDK S81 S78.S81 S78
Data ownership and exportNot published on the collected pages.—
Performance and reliability claimsClaims 2x faster inference and 99% uptime SLA S81 S18.S81 S18
Release activityMultiple product and research announcements S103.S103
20

Measured infrastructure

Domain, certificate, and hosting signals, measured directly.

SignalFinding
Domain registered2017-12-16 — NameCheap, Inc.
Domain expires2028-02-13
First archived2022-04-14 — web archive
TLS certificateGoogle Trust Services, valid, expires 2026-11-28
Security headersCSP
Headers not servedHSTS, X-Content-Type-Options, X-Frame-Options, Referrer-Policy
Server headercloudflare
Mail handled byaspmx.l.google.com, alt1.aspmx.l.google.com
Nameserversgail.ns.cloudflare.com, edward.ns.cloudflare.com

Not measurable: rdap: exceeded the overall budget; wayback: exceeded the overall budget; tls: exceeded the overall budget; dns: exceeded the overall budget; headers: exceeded the overall budget. A gap here means the lookup was unavailable, not that the finding is negative.

21

Technical site audit

A bounded multi-page crawl with page-level issues and URLs.

Scout — Bounded technical crawl

  • Pages crawled: 15 of 15 maximum
  • Technical health: 97/100
  • Critical issues: 1
  • Warnings: 5
  • Notices: 5

Issues

SeverityIssueValueAffected URL
warningTitle length should be reviewed88https://www.together.ai/blog/together-link-frontier-quality-open-models-in-the-harness-you-already-use
noticeImages are missing alt text2https://www.together.ai/blog/together-link-frontier-quality-open-models-in-the-harness-you-already-use
noticeMeta description length should be reviewed224https://www.together.ai/blog/the-open-source-ai-stack
noticeImages are missing alt text2https://www.together.ai/blog/the-open-source-ai-stack
criticalMissing page title—https://www.together.ai/blog/glm-5-3-vs-glm-5-3-flash-on-deepswe-cost-coding-and-routing
noticeImages are missing alt text2https://www.together.ai/blog/glm-5-3-vs-glm-5-3-flash-on-deepswe-cost-coding-and-routing
noticeMeta description length should be reviewed248https://www.together.ai/provisioned-throughput
warningDuplicate title in audit sample2https://www.together.ai/
warningDuplicate title in audit sample2https://www.together.ai/
warningDuplicate meta description in audit sample2https://www.together.ai/
warningDuplicate meta description in audit sample2https://www.together.ai/

Crawled pages

StatusTitleH1sWordsResponseURL
200Together AI \The AI Native Cloud1333766 ms
200Together Link: open models in the harness you already use. Start with one command today.1197573 mshttps://www.together.ai/blog/together-link-frontier-quality-open-models-in-the-harness-you-already-use
200The Open Source AI Stack1460647 mshttps://www.together.ai/blog/the-open-source-ai-stack
200Missing title1411361 mshttps://www.together.ai/blog/glm-5-3-vs-glm-5-3-flash-on-deepswe-cost-coding-and-routing
200Together AI \The AI Native Cloud1333781 ms
200Serverless Inference \Together AI1167841 ms
200Batch Inference \Together AI1145236 ms
200Provisioned Throughput \Together AI1216918 ms
200Dedicated Model Inference \Together AI1198649 ms
200Dedicated Container Inference \Together AI1140020 ms
200Together Link \Open models in your harness \Together AI11584
200Build with leading AI models \Together AI1165747 ms
200NVIDIA GPU Clusters: H100, H200, B200, GB200 \Together AI1178140 ms
200Frontier AI Factory \Together AI1133220 ms
200Sandbox \Together AI1124635 ms

This is a bounded Scout crawl. Core Web Vitals and Lighthouse scores are not claimed unless a dedicated performance audit is connected.

22

Search Console and Analytics

First-party search and behavioral data connection state.

Modeled acquisition channels

ChannelEstimated share
direct51.9%
search37.0%
search organic24.6%
search paid12.4%
social2.9%
social organic2.9%
social paid0.0%
referrals4.7%
paid referrals0.3%
mail0.6%
gen ai2.7%
affiliate0.0%
other0.0%

First-party connections

IntegrationStatusData available after connection
Google Search ConsoleNot connectedClicks, impressions, CTR, average position, queries, pages, countries, and devices
Google AnalyticsNot connectedOrganic sessions, engagement, landing pages, conversions, geography, and devices

No first-party Search Console or Analytics numbers are shown until the site owner authorizes the corresponding Google account. Scout traffic model values above are modeled estimates, not private analytics totals.

Limits and method

23

Limitations and open questions

Known constraints and missing evidence from the collected pages.

The collected pages do not mention specific competitors. Evidence gaps include lack of detailed security and compliance certifications, customer counts, and independent review ratings. Pricing details for some plans are not fully established. The platform's performance claims are vendor-reported and not independently verified.

24

Sources, method, and limitations

Evidence inventory, collection method, provider use, and constraints.

This report is based on 15 collected pages from together.ai, including product, pricing, blog, and about pages. Static and rendered captures were used. External proof search was performed but no external review profiles were scraped. Pricing information is current as of 2026-10-18. Limitations: some claims are from blog posts and may be dated; customer evidence is limited to named mentions in vendor materials.

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