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Groq vs Meta
Meta's Model API sells closed Muse models with 1M context, images and transcription. Groq sells fast open models. A preview API against a speed specialist.
By The Subconscious Team · Updated
Groq vs Meta: key differences
Meta now runs its own closed API. Muse Spark 1.3 has a 1M context and costs $1.25 in and $4.25 out, aimed at agentic coding, tool use and computer use. The same key reaches Muse Image at $0.01 per image and Muse Voice Transcribe at $0.18 per hour. Groq serves open GPT-OSS and Qwen 3.6 on its LPU, with Whisper for transcription. Groq is the clear pick for raw speed and steady tail latency. Meta is the pick for long context, since Groq caps around 131K, and for a broader modality mix.
Maturity cuts both ways. Meta's API is still a public preview with a short track record. Groq has run for years but now operates independently after NVIDIA hired about 90% of its staff, and a Senate antitrust inquiry into that deal opened in March 2026. Meta's Contributor tier drops prices to $0.10 in and $0.20 out if Meta can train on your data, useful for experiments but not business traffic. Groq's small-model prices are already near the floor without that condition.
What Groq and Meta 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 profileMeta
Meta has moved from open Llama releases toward its own closed API. Meta Superintelligence Labs builds the Muse family, and in July 2026 Meta opened a public preview of the Meta Model API with Muse Spark 1.1, a multimodal reasoning model aimed at agentic coding, tool use and computer use. The current lineup runs through Muse Spark 1.3 with a 1M token context. Standard pricing is $1.25 in and $4.25 out per million tokens, with cached input at $0.15, and the endpoint speaks OpenAI Chat Completions, Anthropic Messages and a stateful agentic format.
Example models: Muse Spark 1.3, Muse Glimmer
Full Meta profileShould you choose Groq or Meta?
Groq vs Meta at a glance
| Attribute | Groq | Meta |
|---|---|---|
| Model access | Open weights | Closed API; open Muse Glimmer |
| Flagship models | GPT-OSS 120B, Qwen 3.6 27B | Muse Spark 1.3, Muse Glimmer |
| Speed | 500–1,000 tok/s | ~145–233 tok/s on Muse Spark 1.3 |
| Price | Near the floor on small models | $1.25 in, $4.25 out; Contributor tier cheaper |
| Customization | No fine-tuned model hosting | Open Muse Glimmer weights to fine-tune |
| Deployment | GroqCloud API | Meta Model API (preview) |
| Long context | Around 131K max | 1M |
Frequently asked questions
What is the difference between Groq and Meta?
Meta's Model API sells closed Muse models with 1M context, images and transcription. Groq sells fast open models. A preview API against a speed specialist.
When should I choose Groq over Meta?
Fastest replies on open GPT-OSS and Qwen; Voice agents with Whisper and a fast LLM; Cheap small-model calls without sharing data.
When should I choose Meta over Groq?
Agentic coding and computer use at 1M context; Cheap image generation on the same key; Near-free prototyping where data sharing is fine.
Is Groq or Meta cheaper?
Groq: Near the floor on small models. Meta: $1.25 in, $4.25 out; Contributor tier cheaper. The cheaper choice depends on the model and workload.
Which has more context, Groq or Meta?
Groq: Around 131K max. Meta: 1M.
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