Skip to main content
AI Choice Engine
← GPU inference hub

Inference comparison

Groq vs Together AI

Managed inference API against managed inference api. Editorial fit scores help shortlist; live pricing stays on the provider sites.

Groq product facts checked October 2, 2026Groq editorial scores reviewed September 3, 2026Together AI product facts checked October 2, 2026Together AI editorial scores reviewed September 3, 2026

Managed inference API

Groq

GroqCloud model-specific token, audio-hour or character pricing; eligible asynchronous Batch requests receive a 50% discount. Dedicated platform terms differ.

vs

Managed inference API

Together AI

Serverless per-token; dedicated inference per GPU-minute for ready replicas; GPU clusters and provisioned throughput have separate contracts.

Some outbound links use a first-party redirect hop for click counting. Commission is only claimed when a partner programme is active for that specific link — most vendor hops here are not paid placements. Affiliate disclosure.

Visit GroqDetails
Visit Together AIDetails
Groq vs Together AI GPU inference comparison
DimensionGroqTogether AI
CategoryManaged inference APIManaged inference API
BillingGroqCloud model-specific token, audio-hour or character pricing; eligible asynchronous Batch requests receive a 50% discount. Dedicated platform terms differ.Serverless per-token; dedicated inference per GPU-minute for ready replicas; GPU clusters and provisioned throughput have separate contracts.
GPU choiceGroqMetal dedicated LPU infrastructure; GroqCore adds an inference stack and GroqAssured enterprise controls. These are separate from the shared GroqCloud API.Managed serverless; dedicated deployment profiles with selected hardware; separate GPU clusters for infrastructure control.
Cold startGroqCloud is a shared API; no universal first-request latency is established by the captured documentation. Dedicated capacity has its own deployment terms.Dedicated replicas need provisioning/model loading after restart or zero replicas; ready warm replicas continue billing while idle. No universal startup latency is established.
Model accessGroqCloud production and preview catalogs are separate. Current docs list GPT-OSS text and Whisper audio models; some Llama and MiniMax routes require Enterprise sales. Preview models are for evaluation and may be discontinued at short notice.Serverless catalog plus supported dedicated models, fine-tunes and uploaded LoRA adapters. Custom deployment profiles must meet Together's supported-runtime requirements.
Best forLatency-sensitive chat, agents, and batch inference on Groq’s supported model setServing open-weight models without operating your own GPU fleet
Watch outConfirm the exact served model, endpoint and current quota before committing architecture. Groq’s first-party announcement describes a non-exclusive NVIDIA technology licensing agreement. Its August 17, 2026 release confirms a $350M Series A; neither announcement establishes a fixed throughput or capacity guarantee for your workload.Serverless token APIs, dedicated GPU hours and provisioned throughput have different cost models. Each PTU represents reserved capacity; tokens per minute depend on the model and token type. Together announced $800M in Series C funding on July 1, 2026; this does not guarantee endpoint availability or service levels.
GPU choice (1–10)2/10Winner: 3/10
Time-to-serving (editorial) (1–10)Winner: 10/109/10
Price clarity (1–10)6/10Winner: 7/10
Production ops (1–10)8/108/10
Open-model breadth (1–10)6/10Winner: 9/10

Chart

Fit scores on the decision axes

Editorial 1–10 ratings for this pair only — not live pricing or latency benchmarks.

GPU choice

Pick exact GPUs

Time-to-serving (editorial)

Warm-path fit

Price clarity

Easy to forecast

Production ops

Less DIY ops

Open-model breadth

Catalog depth

Scores are editorial planning ratings (1–10) for product shape — not published $/hour quotes or vendor SLAs. Verify current pricing on each provider site.

How to decide

Prefer Groq when latency-sensitive chat, agents, and batch inference on groq’s supported model set. Prefer Together AI when serving open-weight models without operating your own gpu fleet. If those statements both feel true, rent a GPU for control and keep a managed API for peak traffic — do not force one product to do both jobs.

Common questions

Groq vs Together AI

Answered from the verified figures on this page rather than general guidance.

How are Groq and Together AI billed?
Both bill as groqcloud model-specific token, audio-hour or character pricing; eligible asynchronous batch requests receive a 50% discount. dedicated platform terms differ.. Cost still depends on GPU class, region, and whether instances idle — verify live rates on each site before budgeting.
Which gives more control over the GPU, Groq or Together AI?
Groq: GroqMetal dedicated LPU infrastructure; GroqCore adds an inference stack and GroqAssured enterprise controls. These are separate from the shared GroqCloud API.. Together AI: Managed serverless; dedicated deployment profiles with selected hardware; separate GPU clusters for infrastructure control.. Together AI scores higher for GPU choice (3/10 vs 2/10). Pick a marketplace when you need a specific SKU; pick serverless or managed APIs when you want the platform to handle hardware.
Which has faster cold starts, Groq or Together AI?
Groq: GroqCloud is a shared API; no universal first-request latency is established by the captured documentation. Dedicated capacity has its own deployment terms.. Together AI: Dedicated replicas need provisioning/model loading after restart or zero replicas; ready warm replicas continue billing while idle. No universal startup latency is established.. Our editorial ratings favour Groq for warm API speed (10/10 vs 9/10), but real latency depends on model size, region, and whether endpoints are kept warm. Those 1–10 scores are editorial rankings, not measured milliseconds — record your own TTFT/p95 on a warm endpoint in the target region before you buy on latency.
Should I use Groq or Together AI?
Choose Groq when latency-sensitive chat, agents, and batch inference on groq’s supported model set. Choose Together AI when serving open-weight models without operating your own gpu fleet. Watch out: Confirm the exact served model, endpoint and current quota before committing architecture. Groq’s first-party announcement describes a non-exclusive NVIDIA technology licensing agreement. Its August 17, 2026 release confirms a $350M Series A; neither announcement establishes a fixed throughput or capacity guarantee for your workload. Serverless token APIs, dedicated GPU hours and provisioned throughput have different cost models. Each PTU represents reserved capacity; tokens per minute depend on the model and token type. Together announced $800M in Series C funding on July 1, 2026; this does not guarantee endpoint availability or service levels.
When should I use a managed API like Groq instead of renting a GPU?
Prefer a managed inference API when you want tokens quickly without CUDA ops and the model is already on the catalog. Prefer GPU rental when you need a specific SKU, custom serving stack, or sustained utilization that beats token pricing — size VRAM on /gpus first.