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Cerebras vs OpenScale
Cerebras is the fastest public host on a thin catalog. OpenScale is among the cheapest on DeepSeek V4.1 Flash with a 1M token window.
By The Subconscious Team · Updated
Cerebras vs OpenScale: key differences
Cerebras serves GPT-OSS 120B near 3,000 tokens per second on its wafer-scale chip, at $0.35 in and $0.75 out per million tokens, with context around 131K. Its shared catalog is two models, with more on dedicated endpoints. OpenScale serves DeepSeek V4.1 Flash at 200+ tokens per second, with a 1M window, at $0.06 in and $0.24 out under a 50% promotion.
Cerebras is the pick when generation speed is the wait, as in voice, live autocomplete or long streamed outputs. OpenScale is the pick for long, input-heavy coding agents, where context size and cached input price matter more than tokens per second.
What Cerebras and OpenScale do
Cerebras
Cerebras builds a single chip the size of a silicon wafer, and its inference cloud is the fastest public host on the models it serves. Its developer table lists GPT-OSS 120B near 3,000 tokens per second, about six times Groq on the same weights, at $0.35 in and $0.75 out per million. The public shared catalog is thin, just GPT-OSS 120B and Qwen 3.8 27B since Gemma 4 31B moved to dedicated-only in September 2026. More model families live on dedicated endpoints and through partners like OpenRouter, Hugging Face, Vercel and AWS Marketplace.
Example models: GPT-OSS 120B, Qwen 3.8 27B
Full Cerebras 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 Cerebras or OpenScale?
Cerebras vs OpenScale at a glance
| Attribute | Cerebras | OpenScale |
|---|---|---|
| Model access | Open weights | Open weights |
| Flagship models | GPT-OSS 120B, Qwen 3.8 27B | DeepSeek V4.1 Flash |
| Speed | ~3,000 tok/s on GPT-OSS 120B | 200+ tok/s; fast tier ~2x |
| Price | $0.35 in, $0.75 out (GPT-OSS 120B) | $0.06 in, $0.24 out (promo, DeepSeek V4.1 Flash) |
| Customization | Unknown | N/A |
| Deployment | Shared API, dedicated, partners | Serverless API |
| Long context | 131K on GPT-OSS 120B, 128K on Qwen 3.8 27B | 1M context |
Frequently asked questions
What is the difference between Cerebras and OpenScale?
Cerebras is the fastest public host on a thin catalog. OpenScale is among the cheapest on DeepSeek V4.1 Flash with a 1M token window.
When should I choose Cerebras over OpenScale?
The highest published tokens per second; Voice and live autocomplete; Long streamed outputs.
When should I choose OpenScale over Cerebras?
Long-context coding agents; Cheap cached input; Self-serve signup with prepaid credits.
Is Cerebras or OpenScale cheaper?
Cerebras: $0.35 in, $0.75 out (GPT-OSS 120B). 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, Cerebras or OpenScale?
Cerebras: 131K on GPT-OSS 120B, 128K on Qwen 3.8 27B. 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.