Generative AI & Automation★ EDITOR'S PICK · BUY· read full review ↓

Together AI

Inference platform for open-source LLMs — fast, cheap hosting for Llama, Mixtral, Qwen, DeepSeek, and 200+ others.

Professional
Pricing Tier
Easy
Learning Curve
hours
Implementation
small, medium, large, enterprise
Best For
Visit website ↗🔖 Save to StackAsk AI about Together AIDocs ↗
Use when

Teams running production LLM workloads who want open-model pricing, anyone fine-tuning, multi-provider router setups.

Avoid when

If you need the absolute frontier (GPT-5, Claude Opus 4.7) — those are first-party only. Stick with Anthropic/OpenAI direct.

What is Together AI?

Together AI runs the largest fleet of open-source LLM inference in the industry. They host 200+ models with OpenAI-compatible APIs, fine-tuning workflows, and dedicated GPU clusters. Series B raised $305M in early 2025 at a $3.3B valuation. Used by Salesforce, Zoom, and other production AI teams who want open-model economics without the ops burden.

Key features

200+ open-source models (Llama, Mixtral, Qwen, DeepSeek)
OpenAI-compatible API (drop-in)
Fine-tuning with LoRA + full
Dedicated GPU endpoints
JSON mode and function calling
Together Code Interpreter for agent workflows

Integrations

OpenAI SDK (compatible)LangChainLlamaIndexVercel AI SDK
💰 Real-world pricing

What people actually pay

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StackMatch EditorialVerdict: BuyUpdated Apr 30, 2026

OpenAI-class API, open-source weights, half the price

Editor's summary

Together.ai serves Llama, Mixtral, Qwen, and DeepSeek at production latency through an OpenAI-compatible API at meaningfully lower cost than the frontier providers. The right pick for inference-heavy apps that don't need GPT-5 or Opus.

Together has quietly become a default for production inference on open-source models. The OpenAI-compatible API means you can swap from GPT-4o to Llama 3.1 70B with a base_url change, and the per-token pricing on 70B-class open models is 5-10x cheaper than frontier APIs. Performance is competitive with Fireworks and Groq for most workloads, and the dedicated endpoint option keeps cost predictable for high-volume apps.

The constraints are model-quality constraints, not Together-specific. Llama 3.1 70B and Mixtral 8x22B are very good for their cost — but they're not Claude Opus or GPT-5. Apps that need top-tier reasoning, agentic tool use, or long-context coherence still belong on frontier APIs. Together also doesn't differentiate strongly versus Fireworks AI; choose between them based on benchmarks for your specific model and pricing for your specific volume.

Buy Together for production apps using open-source models — chatbots, classification, summarization, anything where 70B-class quality is sufficient and per-token cost matters. Pair with frontier APIs for the highest-stakes calls in the same product. Skip if you're only consuming GPT/Claude — there's no win here over going direct.

Best for

Production inference workloads on Llama, Mixtral, Qwen, or DeepSeek — chatbots, classification, summarization at scale.

Not for

Frontier-only workflows or teams that don't care about open-source models — direct OpenAI/Anthropic is simpler.

Written by StackMatch Editorial. StackMatch editorial reviews are independent analyst commentary, not user reviews. We have no affiliate relationship with this tool. See user reviews below for community perspective.

HONEST ALTERNATIVES

Before you buy Together AI

Vendors don't tell you about their competitors. We do — with verdicts attached when we have them.

3 of 3 have a StackMatch Editorial verdict.
See all in Generative AI & Automation
REAL COST CALCULATOR

What Together AI actually costs

Sticker price isn't the real cost. We add implementation, training, and a probability-weighted lock-in penalty.

1500
Subscription
$50/seat/mo × 50 × 36 mo
$90K
Implementation (one-time)
Minutes/hours
$0
Training (one-time)
$200/seat × 50 (easy curve)
$10K
Real total cost (3-year)
~$33K per year
$100K
1.1× sticker. Vendor will quote ~$90K (subscription only). Real cost is $100K once implementation, training, and switching risk are priced in.
Heuristic — uses median industry rates. Negotiate to beat list pricing; the implementation and training estimates assume reasonable rollout.
NEGOTIATION TIMING

When to negotiate Together AI

Vendor sales pressure is non-uniform — quarter-close, year-end, and post-funding-round are your high-leverage windows.

HIGH LEVERAGE15 days to Q2 close

Strong negotiation window. Reps will push for end-of-quarter signature. Don't move first — let them initiate the discount. Target 15-30% off list plus negotiated terms.

Tier-specific leverage
Professional-tier has moderate negotiation room — annual commit + reference customer rights typically unlock 15-25% off list.
Q1
289d out
Q2
15d out
Q3
107d out
Q4
199d out
Calendar-quarter heuristic. Vendors on fiscal-year ≠ calendar may shift these windows; ask the rep what their fiscal year-end is.
BUYER'S QUESTION LIST

Take this to your sales call

10 questions vendor sales teams steer around — generated from Together AI's pricing tier, lock-in profile, and editorial verdict.

  1. 1
    PRICING
    Together AI is professional-tier on the public site. What's the discount path for small-sized teams committing annually vs. monthly?
  2. 2
    PRICING
    What overages or seat-overflow charges should we plan for? Show me the worst-case bill if our usage grows 2x in year 1.
  3. 3
    CONTRACT
    Auto-renewal: how many days notice is required to terminate, and what happens if we miss the window? Will you commit to a renewal-reminder email at 90 and 60 days?
  4. 4
    MIGRATION
    Data export: what's the complete spec — format, frequency, and what data does the export NOT include? After contract end, how long do we have read-only access?
  5. 5
    MIGRATION
    Implementation runs hours. Who from your team is included by default, and who do we add at additional cost? Is a CSM assigned?
  6. 6
    FIT
    Together AI is best for: Production inference workloads on Llama, Mixtral, Qwen, or DeepSeek — chatbots, classification, summarization at scale.. We're [describe your situation]. Walk me through the failure modes if our profile doesn't match.
  7. 7
    FIT
    Connect us with 2-3 reference customers at our company size in SaaS — not the case-study list, customers who've been live for 18+ months and have churned at least one tool from your stack.
  8. 8
    INTEGRATION
    Together AI lists 4 integrations including OpenAI SDK (compatible), LangChain, LlamaIndex. Which of OUR existing tools — bring our list — have you confirmed shipping integration with versus "on roadmap"? Show me the actual status.
  9. 9
    VENDOR
    Track record over the last 18 months: any pricing model changes, executive departures, layoffs, M&A activity, or material customer churn we should know about?
  10. 10
    VENDOR
    If you're acquired or shut down, what's the contractual continuity — source-code escrow, data portability, transition period? Show me the actual clause.
Auto-generated from Together AI's structured profile. Edit before sending — you know your situation better than we do.
ANTI-DEMO CHECKLIST

What to actually test in the demo

Vendor sales teams script demos to maximize close rate. Here's what they'd rather you not test — derived from Together AI's lock-in profile and editorial verdict.

  1. 1
    PERFORMANCE
    Bring YOUR data, not their demo data. Insist on running the demo workflow against a sample of your real records, files, or queries. If they refuse — that's a signal.
  2. 2
    PERFORMANCE
    Together AI demo will be built around the happy path. Ask: "Show me what happens when [the most common failure mode in our context]" — make them improvise.
  3. 3
    EDGE CASES
    Push the limits live: largest dataset, longest workflow, most users concurrent. Vendors prep demos for medium loads — your real-world usage might 10x what they show.
  4. 4
    EDGE CASES
    Mobile and offline behavior: how does Together AI degrade on slow connections, on iPad, in airplane mode? Test in the demo if your team uses these surfaces.
  5. 5
    PRICING
    Model your worst-case bill: 2x the seats, 3x the usage. Show the exact dollar figure on screen during the demo. Refuse "we'll get back to you" — get the math live.
  6. 6
    INTEGRATION
    Vendors love their integration logo wall. Test the actual depth: pick the 2-3 (OpenAI SDK (compatible), LangChain-style) integrations you depend on most, and ask the rep to demo a real two-way data sync, not a marketing screenshot.
  7. 7
    INTEGRATION
    API and webhook reality check: rate limits, payload size limits, retry behavior, auth refresh handling. Ask for actual API docs in the demo, not "we'll send those."
  8. 8
    MIGRATION
    Demo the full data export workflow. Even with low lock-in, you want to see how clean the exit looks before signing.
  9. 9
    SUPPORT
    Submit a real support ticket DURING the demo. Use the actual support channel customers use, not the rep's email. Time the response. This is your most honest data point about post-sale reality.
  10. 10
    SUPPORT
    Ask to be connected with a customer in the demo who you can email TODAY (not "we'll arrange a reference call next week"). The vendor's confidence in their references is a tell.
Print it, bring it to the demo call, and check items off as you cover them. The rep noticing you have a list changes the energy.

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