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Groq vs Infron
Groq serves a few models very fast on its own LPU chips. Infron routes across 400+ models from many providers on one key.
By The Subconscious Team · Updated
Groq vs Infron: key differences
Groq runs a small catalog, like GPT-OSS 120B and Qwen 3.6 27B, at 500 to 1,000 tokens per second with tight tail latency, capped around 131K context. Infron is a gateway: one OpenAI-compatible API in front of 400+ models from 100+ providers, at provider rates plus a 3% to 5% fee on credit top-ups, with fallbacks, region pinning and a 99.9% uptime SLA on dedicated throughput.
Groq is the pick when speed on a supported model matters most. Infron is the pick for breadth and resilience across vendors. A product can use both: Groq for latency-critical calls and Infron for everything else.
What Groq and Infron do
Groq
Groq serves open models on its own chip, the LPU, which keeps model weights in on-chip SRAM and runs a deterministic schedule instead of waiting on GPU memory. Groq publishes 1,000 tokens per second on GPT-OSS 20B and 500 on GPT-OSS 120B. Latency stays tight between median and tail, which matters for strict SLAs. The API is OpenAI-compatible and also hosts Whisper for speech to text plus an agentic system called Groq Compound with built-in search and code execution.
Example models: GPT-OSS 120B, Qwen 3.6 27B
Full Groq profile
Infron
Infron is a US-based AI gateway and inference platform. One OpenAI-compatible API reaches 400+ models from 100+ providers, including DeepSeek, Qwen, Claude, Gemini and GPT through what Infron calls official partner routes, plus media and search models. Teams set provider preferences and fallbacks, see usage and billing in one place, and can bring their own provider keys at no fee. Lawrence Xu is CEO and co-founder Andrew Zheng is CTO.
Example models: DeepSeek, Qwen, Claude, Gemini, GPT
Full Infron profileShould you choose Groq or Infron?
Groq vs Infron at a glance
| Attribute | Groq |  Infron |
|---|---|---|
| Model access | Open weights | Closed and open, 400+ models |
| Flagship models | GPT-OSS 120B, Qwen 3.6 27B | DeepSeek, Qwen, Claude, Gemini, GPT |
| Speed | 500–1,000 tok/s | Unknown |
| Price | Near the floor on small models | Provider rates; 3–5% top-up fee |
| Customization | No fine-tuned model hosting | Custom deployments |
| Deployment | GroqCloud API | Gateway API, dedicated, BYOK |
| Long context | Around 131K max | Varies by model |
Frequently asked questions
What is the difference between Groq and Infron?
Groq serves a few models very fast on its own LPU chips. Infron routes across 400+ models from many providers on one key.
When should I choose Groq over Infron?
Very fast output on small open models; Tight tail latency; Low prices on a short list.
When should I choose Infron over Groq?
Closed and open models on one key and one bill; Automatic failover across providers; Multi-model products that switch models often.
Is Groq or Infron cheaper?
Groq: Near the floor on small models. Infron: Provider rates; 3–5% top-up fee. The cheaper choice depends on the model and workload.
Which has more context, Groq or Infron?
Groq: Around 131K max. Infron: Varies by model.
Related comparisons
Running long-horizon agents?
If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.