Watch: Benchmark Groq on your own prompts for latency, context...
ToolChatbotsfreemiumactive8-8.9
Groq
Groq is the LPU inference provider, not xAI's Grok...
8.8/10Strong
Active
Free 30 req/min / paid usage-based
Best plan
Free 30 req/min / paid usage-based
Risk: Benchmark Groq on your own prompts for latency, context...
Editorial · no paid placements
Should you use it?
Groq is the LPU inference provider, not xAI's Grok chatbot. The June 25, 2026 buyer case is still speed and predictable API economics for supported open models: free-tier prototyping, paid usage-based pricing, prompt caching, built-in tools, and Batch API discounts. Pick it for latency-critical open-model workloads; skip it when you need a closed frontier model from OpenAI, Anthropic, or Google.
- Buy ifLatency-sensitive LLM workloads
- PickFree 30 req/min / paid usage-based
- Skip ifUsers who need frontier-proprietary models from OpenAI, Anthropic, or Google
Plan guidance
What to buy
Usage-based by model
Benchmark Groq on your own prompts for latency, context...
Current pricing source: Groq pricing
Fit
Use it for this, skip it for that
Best for
- Latency-sensitive LLM workloads
- Real-time voice or streaming applications
- Production apps needing consistent low-latency
- Open-weight model inference at scale
Avoid if
- Users who need frontier-proprietary models from OpenAI, Anthropic, or Google
- Long-context or reasoning workloads (open-weight on Groq is capped)
- Users without API integration (consumer-facing UI is minimal)
- Watch out
- Benchmark Groq on your own prompts for latency, context length, model quality, rate limits, deprecations, and fallback strategy rather than buying only on speed positioning.
Recent changes
Only what affects the decision
- Model pricing and prompt caching
Reverified pricing table: GPT OSS 20B/120B, Llama 4 Scout, Qwen3 32B, Llama 3.3 70B, Llama 3.1 8B, and Qwen 3.6 27B are public pricing rows; Kimi K2 0905 appears in prompt-caching pricing
Groq pricing - Model pricing
Reverified current public pricing table and discount surfaces; use the live pricing page because model IDs and throughput labels can move
Groq pricing - Llama 4 Scout
Verified unchanged; 594 TPS measured
Groq pricing
Alternatives
Best swaps
ChatGPT
Build comparisonOpenAI's flagship AI assistant, with GPT-5 models, image generation, Codex coding agent, voice, and agent mode across web, mobil
$0-$200/month · 9.5/10ClaudeAnthropic's AI assistant. Strongest on long-context reasoning, agentic coding, and long-form writing.
$0-$200/month · 9.3/10OllamaLocal open-model runtime plus optional Ollama Cloud inference. Free local runtime; Cloud Pro $20/mo or $200/yr; Max $100/mo; Tea
$0 local / $20-$100/mo cloud · 9/10Proof and score mathVerified Jun 25
Proof
Why this recommendation is trusted
EvidenceGroq official site
- Source
- Registered source
- Freshness
- Review due
- Confidence
- Low confidence
- Verified
- Review
- Volatility
- Volatile
Stale source groq-pricing.
Editorial score
Unweighted average of 4 axes · confidence high
- Utility9/10
How much real work it can do for a competent operator, end to end.
- Value9/10
What you get for the dollar relative to the closest alternative.
- Moat9/10
How hard it would be for a competitor to replicate the underlying advantage.
- Longevity8/10
How likely the product is to still be best-in-class 24 months out.
Verified facts
- Best ForBest for developers who need very low-latency hosted inference for supported open models through an API, with current catalog checks across Llama, Qwen, Whisper, DeepSeek, and OpenAI-compatible GPT OSS routes.
- Pricing AnchorAs of June 25, 2026, Llama 4 Scout runs $0.11/$0.34, Llama 3.1 8B Instant $0.05/$0.08, Llama 3.3 70B Versatile $0.59/$0.79, Qwen3 32B $0.29/$0.59, Qwen 3.6 27B $0.60/$3.00, and GPT OSS 20B $0.075/$0.30 per million tokens. Qwen3 32B and Llama 4 Scout are scheduled to shut down for free and developer-tier users on July 17, 2026, so new production builds should prefer the recommended replacements.
- Watch Out ForBenchmark Groq on your own prompts for latency, context length, model quality, rate limits, deprecations, and fallback strategy rather than buying only on speed positioning.
- Api AvailableGroq is API-first; the docs define authentication, chat/completions behavior, streaming, tool use, and production integration assumptions.
- Model ControlThe June 2026 supported-models and deprecations pages should be treated as the source of truth because model IDs, production/preview status, context windows, and shutdown dates move quickly; Qwen3 32B and Llama 4 Scout are scheduled to shut down for free and developer-tier users on July 17, 2026.
Full review notesLong-form details, FAQ, and source history
Not to be confused with Grok (xAI’s chatbot, different company, different product). This page is Groq, the LPU inference provider.
One of the fastest LLM providers on the market in 2026. Custom silicon called the Language Processing Unit (LPU) is optimized for low-latency model serving, and Groq’s API exposes supported open models through an OpenAI-compatible developer surface.
As of June 25, 2026, Groq’s public pricing page still frames the buyer case around predictable per-token pricing, prompt caching discounts, and built-in tools. Kimi K2 0905 appears in prompt-caching pricing, while Qwen 3.6 27B is now a visible public model-price row beside GPT OSS, Llama, and Qwen3. Do not pin new free/developer-tier production work to Qwen3 32B or Llama 4 Scout without a migration plan because Groq’s deprecations page schedules both for July 17, 2026 shutdown on those tiers.
System Verdict
Pick Groq if your workload is latency-sensitive. Real-time voice agents, streaming chat interfaces, interactive AI applications all feel qualitatively different at 500+ tokens/second. You notice the speed the first time you try it.
Skip Groq if you need frontier proprietary models. Groq serves supported open and open-compatible model routes. For the newest closed frontier ChatGPT, Claude, or Gemini models, go to the source provider.
The 2026 context: Open-weight flagships have closed the gap on many tasks, but quality still varies by job. Groq’s edge is not “best model”; it is fast serving, simple API migration, and lower-latency economics for the open models it supports.
Key Facts
| Free tier | 30 requests/min, 6,000 tokens/min, 14,400 requests/day |
| Developer tier | 10x free rate limits, 25 percent discount on tokens |
| Llama 4 Scout 17B | $0.11 input / $0.34 output per M tokens (594 TPS) |
| Llama 3.3 70B Versatile | $0.59 input / $0.79 output per M tokens (394 TPS) |
| Llama 3.1 8B Instant | $0.05 input / $0.08 output per M tokens (840 TPS) |
| Qwen3 32B | $0.29 input / $0.59 output per M tokens (662 TPS) |
| Qwen 3.6 27B | $0.60 input / $3.00 output per M tokens (500 TPS) |
| GPT OSS 20B | $0.075 input / $0.30 output per M tokens (1,000 TPS) |
| GPT OSS 120B | $0.15 input / $0.60 output per M tokens (500 TPS) |
| Speed | Up to 1,000 tokens/second on GPT OSS 20B; 394 to 840 TPS on Llama-family models |
| Hardware | Custom LPU (Language Processing Unit) silicon |
| Batch API | 50 percent discount for non-real-time workloads (24h to 7d windows) |
| Prompt caching | 50 percent off cached input tokens, no extra caching fee |
| Near-term deprecations | Qwen3 32B and Llama 4 Scout shut down for free/developer-tier users on July 17, 2026; enterprise committed-spend customers are not affected |
When to pick Groq
- Real-time voice applications. Users feel sub-200ms response times. Groq’s streaming LLM inference makes this achievable with open-weight models.
- Streaming chat interfaces. Token streaming that displays in real time. On Groq, the full response often lands before the user finishes reading the first line.
- Production apps scaling open-weight. Low per-token pricing plus low latency can create strong unit economics for Llama, Qwen, Whisper, DeepSeek, and compatible open-model deployments.
- Agent loops with tight latency budgets. Multi-step agent workflows where each LLM call must return fast to meet overall SLA.
When to pick something else
- Frontier proprietary quality: Go direct to OpenAI, Anthropic, or Google.
- Max model variety: Fal.ai (600+ models) or Fireworks AI (400+ models) for broader catalog.
- Long-context workflows: Groq supports long context on supported models but caps below frontier API offerings.
- Consumer chat UI: Groq is API-first. Use Ollama + a chat UI or ChatGPT for consumer workflows.
Pricing
Pricing is per-token and predictable.
| Model | Input $/M tokens | Output $/M tokens | Speed (TPS) |
|---|---|---|---|
| Llama 3.1 8B Instant | $0.05 | $0.08 | 840 |
| GPT OSS 20B | $0.075 | $0.30 | 1,000 |
| Llama 4 Scout 17B | $0.11 | $0.34 | 594 |
| GPT OSS 120B | $0.15 | $0.60 | 500 |
| Qwen3 32B | $0.29 | $0.59 | 662 |
| Qwen 3.6 27B | $0.60 | $3.00 | 500 |
| Llama 3.3 70B Versatile | $0.59 | $0.79 | 394 |
Rate tiers: Free (30 req/min, 14,400/day). Developer (10x free + 25 percent off). Enterprise (custom). Batch API: 50 percent off for 24-hour to 7-day windows. Prompt caching has no extra feature fee; the current table also lists Kimi K2 0905 at $1.00/M uncached input, $0.50/M cached input, and $3.00/M output.
Verified 2026-06-25 via groq.com/pricing, Groq supported models, and Groq model deprecations.
Failure modes
- Open-weight only. Groq hosts open-weight models including OpenAI’s GPT OSS 20B and 120B, but no frontier ChatGPT, no Claude, no Gemini. If your product needs a closed frontier model, Groq is complementary, not a replacement.
- Free tier rate limits bite. 30 req/min is enough for prototyping, not production. Plan upgrade.
- Model catalog is narrower than FLUX marketplaces. Curated selection of flagship open-weight models, not every model on Hugging Face.
- Model catalog changes. Groq’s supported-model table includes production and preview routes; check model IDs, deprecations, context limits, and rate limits before pinning a production workload.
- Two visible pricing rows are near shutdown on lower tiers. Qwen3 32B and Llama 4 Scout still appear as useful price anchors, but Groq says they shut down for free and developer-tier users on July 17, 2026. New builds should test GPT OSS 120B or Qwen 3.6 27B replacements.
- LPU geography is limited. Not globally distributed in 2026 at the level of AWS or GCP. Latency is great near a Groq region, less great far from one.
Against the alternatives
| Groq | Fireworks AI | Together AI | OpenAI | |
|---|---|---|---|---|
| Speed (tok/sec) | 394 to 1,000 | 50-200 | 50-200 | 50-100 |
| Hardware | Custom LPU | Blackwell GPUs | H100/H200 | OpenAI infra |
| Llama 4 Scout input | $0.11/M | ~$0.15/M | ~$0.20/M | N/A |
| Proprietary models | No (open-weight + GPT OSS) | No | No | Yes |
| Best for | Latency-critical open-weight | General open-weight inference | Fine-tuning + hosting | Frontier quality |
Methodology
Produced by the aipedia.wiki editorial pipeline. Last verified 2026-06-25 against Groq pricing, Groq docs, Groq supported models, and Groq model deprecations.
FAQ
Is Groq the same as Grok? No. Groq (this page) is a hardware-accelerated LLM inference provider founded in 2016. Grok is xAI’s chatbot and API platform launched in 2023. Different companies, different products, easy to confuse because of the single-letter spelling.
Is Groq really 10× faster than other providers? On open-weight models, the LPU hardware delivers 3-10× higher tokens/second than GPU-based providers. Real-world advantage depends on model, context length, and region.
What’s an LPU and how is it different from a GPU?. Unlike GPUs (which are general-purpose matrix-math chips), LPUs are optimized for the specific compute, and lower cost per token on supported models.
Was Groq acquired by Nvidia? AiPedia is not treating acquisition rumors as current buyer facts. Use Groq’s official site, pricing page, and docs for purchase decisions unless Groq or Nvidia publish a primary-source announcement.
Can I run Llama 4 Scout’s 10M context on Groq? Groq supports long context on some models but not always the full 10M. Check current model specs on Groq’s docs; the effective context window varies.
Related
- Category: AI Chatbots
- See also: Fireworks AI · Together AI · Fal.ai · Llama
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According to aipedia.wiki Editorial at aipedia.wiki (https://aipedia.wiki/tools/groq/)aipedia.wiki Editorial. (2026). Groq: Editorial Review. aipedia.wiki. Retrieved August 3, 2026, from https://aipedia.wiki/tools/groq/aipedia.wiki Editorial. "Groq: Editorial Review." aipedia.wiki, 2026, https://aipedia.wiki/tools/groq/. Accessed August 3, 2026.aipedia.wiki Editorial. 2026. "Groq: Editorial Review." aipedia.wiki. https://aipedia.wiki/tools/groq/.@misc{groq-editorial-review-2026,
author = {{aipedia.wiki Editorial}},
title = {Groq: Editorial Review},
year = {2026},
publisher = {aipedia.wiki},
url = {https://aipedia.wiki/tools/groq/},
note = {Accessed: 2026-08-02}
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