vs
Groq vs OpenScale
Groq sells raw speed on its own LPU chips across a small catalog. OpenScale sells low prices and a 1M window on DeepSeek V4.1 Flash.
By The Subconscious Team · Updated
Groq vs OpenScale: key differences
Groq runs GPT-OSS 120B, Qwen 3.8 27B and a few other open models at 500 to 1,000 tokens per second with tight tail latency, capped around 131K context. OpenScale serves DeepSeek V4.1 Flash at 200+ tokens per second with a 1M token window, at $0.06 in and $0.24 out under a 50% promotion, plus a faster tier at about twice the speed.
Groq is the pick when every call has to return fast, as in voice agents. OpenScale is the pick for coding agents that need long context and cheap cached input more than peak speed.
What Groq and OpenScale 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 3.8 27B
Full Groq profileOpenScale
OpenScale is a Y Combinator-backed inference API built by LatentSpace and run out of Singapore. It sells open models behind one endpoint that speaks Chat Completions, the OpenAI Responses API and Anthropic Messages, so Claude Code, Codex, OpenCode, Cline, GitHub Copilot, Zed and other coding agents can point at it with a base URL and key. Its public catalog today is DeepSeek V4.1 Flash in two versions, standard and fast, both with a 1M token context window and up to 384K output tokens.
Example models: DeepSeek V4.1 Flash
Full OpenScale profileShould you choose Groq or OpenScale?
Groq vs OpenScale at a glance
| Attribute | Groq | OpenScale |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | GPT-OSS 120B, Qwen 3.8 27B | DeepSeek V4.1 Flash |
| Speed | 500–1,000 tok/s | 200+ tok/s; fast tier ~2x |
| Price | Near the floor on small models | $0.06 in, $0.24 out (promo, DeepSeek V4.1 Flash) |
| Customization | No fine-tuned model hosting | N/A |
| Deployment | GroqCloud API | Serverless API |
| Long context | Around 131K max | 1M context |
Frequently asked questions
What is the difference between Groq and OpenScale?
Groq sells raw speed on its own LPU chips across a small catalog. OpenScale sells low prices and a 1M window on DeepSeek V4.1 Flash.
When should I choose Groq over OpenScale?
Voice agents and fast agent loops; Predictable tail latency; Small open models at very high speed.
When should I choose OpenScale over Groq?
1M token context on DeepSeek V4.1 Flash; Cheap cached input for coding agents; Anthropic and OpenAI-compatible endpoints.
Is Groq or OpenScale cheaper?
Groq: Near the floor on small models. OpenScale: $0.06 in, $0.24 out (promo, DeepSeek V4.1 Flash). The cheaper choice depends on the model and workload.
Which has more context, Groq or OpenScale?
Groq: Around 131K max. OpenScale: 1M context.
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.