# Groq vs Hugging Face Inference Providers

> Groq runs a small catalog on its own LPU for speed. Hugging Face routes to Groq and 16 other hosts, trading a network hop for a far wider model list.

Canonical: https://www.subconscious.dev/compare/groq-vs-hugging-face · By The Subconscious Team · Updated September 30, 2026

## How they compare

Groq is a Hugging Face partner, and a :groq suffix pins traffic to it through the router. Direct, Groq publishes 1,000 tokens per second on GPT-OSS 20B and 500 on GPT-OSS 120B, with tail latency that stays close to the median. Its catalog is small and shrinking, centered on GPT-OSS and Qwen 3.6 after Llama 3.3 70B and Llama 3.1 8B shut down on August 16, 2026, and context caps around 131K. Hugging Face lists 132 chat models, with gpt-oss-120b alone on eleven providers, and context up to 1M on some hosts. The router bills Groq's rate with no markup, but its extra hop and rate limits blunt the tail-latency consistency that makes Groq worth choosing.

Groq also hosts Whisper for speech to text and Groq Compound, an agentic system with built-in search and code execution, which suits voice agents. Neither side hosts fine-tuned models. Hugging Face's strengths are choice and resilience: default routing picks the highest-throughput provider, automatic failover covers outages, and /v1/models exposes live price and latency per host. That resilience carries extra weight here, since GroqCloud's long-term investment is an open question after NVIDIA licensed the LPU and hired most of its engineers. For a voice agent with a strict SLA, call Groq directly. For breadth, longer context or a hedge against depending on one host, route through Hugging Face.

## What each one does

### 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.

### Hugging Face Inference Providers

Inference Providers is a router run by Hugging Face that sits in front of partner inference clouds. The current partner list covers Baseten, Cerebras, Cohere, DeepInfra, fal, Featherless AI, Fireworks, Groq, Novita, Nscale, OVHcloud, Public AI, Replicate, Scaleway, Together, WaveSpeedAI and Z.ai, plus Hugging Face's own HF Inference, which now mostly serves CPU workloads like embeddings and classification. Chat traffic goes through an OpenAI-compatible endpoint at router.huggingface.co/v1, and the Python and JavaScript clients add text-to-image, video, speech and embeddings. The router lists 132 chat models today, from GLM 5.3 and Kimi K3 to gpt-oss-120b on eleven providers.

## Which is best, and when

### Choose Groq for

- Voice agents pairing Whisper with fast replies
- Strict SLAs judged on tail latency
- Fast multi-step loops on GPT-OSS

### Choose Hugging Face Inference Providers for

- Models and context lengths beyond Groq's catalog
- Hedging against a single host with failover
- Routing gpt-oss-120b across eleven providers

## At a glance

| Attribute | Groq | Hugging Face Inference Providers |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | GPT-OSS 120B, Qwen 3.6 27B | GLM 5.3, Kimi K3, DeepSeek V4.1 Flash |
| Speed | 500–1,000 tok/s | Routes to fastest provider by default |
| Price | Near the floor on small models | Provider rates, no markup |
| Customization | No fine-tuned model hosting | N/A |
| Deployment | GroqCloud API | Serverless router; dedicated Endpoints |
| Long context | Around 131K max | Up to 1M, provider-dependent |

## FAQ

### What is the difference between Groq and Hugging Face Inference Providers?

Groq runs a small catalog on its own LPU for speed. Hugging Face routes to Groq and 16 other hosts, trading a network hop for a far wider model list.

### When should I choose Groq over Hugging Face Inference Providers?

Voice agents pairing Whisper with fast replies; Strict SLAs judged on tail latency; Fast multi-step loops on GPT-OSS.

### When should I choose Hugging Face Inference Providers over Groq?

Models and context lengths beyond Groq's catalog; Hedging against a single host with failover; Routing gpt-oss-120b across eleven providers.

### Is Groq or Hugging Face Inference Providers cheaper?

Groq: Near the floor on small models. Hugging Face Inference Providers: Provider rates, no markup. The cheaper choice depends on the model and workload.

### Which has more context, Groq or Hugging Face Inference Providers?

Groq: Around 131K max. Hugging Face Inference Providers: Up to 1M, provider-dependent.

## Running long-horizon agents?

If your agents run past 200K tokens, compare both against Subconscious: [Subconscious vs Groq](https://www.subconscious.dev/compare/subconscious-vs-groq.md), [Subconscious vs Hugging Face Inference Providers](https://www.subconscious.dev/compare/subconscious-vs-hugging-face.md).

Full profiles: [Groq](https://www.subconscious.dev/providers/groq.md), [Hugging Face Inference Providers](https://www.subconscious.dev/providers/hugging-face.md).