Cerebras vs General Compute

Cerebras sells its wafer-scale inference directly. General Compute runs decode on Cerebras and other ASICs inside its own cloud.

By The Subconscious Team · Updated October 27, 2026

Cerebras vs General Compute: key differences

Cerebras lists GPT-OSS 120B near 3,000 tokens per second at $0.35 in and $0.75 out per million tokens, with 131K context. Its shared catalog is GPT-OSS 120B and Qwen 3.8 27B, with more on dedicated endpoints and partners. General Compute uses Cerebras as one of its decode chips, next to SambaNova, Positron AI and d-Matrix, with NVIDIA GPUs on prefill. It serves GPT-OSS 120B at $0.21 in and $0.79 out and reports over 1,000 tokens per second on it in its own benchmark.

Cerebras is the pick for the highest published speed on GPT-OSS 120B and for OpenAI's Ultrafast GPT-5.6 Sol preview. General Compute is cheaper on GPT-OSS 120B input, adds MiniMax M2.7 and two DeepSeek models, and serves custom LoRA or fine-tuned checkpoints. Its dedicated racks spread capacity across several chip vendors, though most of that capacity lands in Q1 2027.

What Cerebras and General Compute 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 profile

General Compute

General Compute is a San Francisco inference cloud built on alternative chips. It splits each request across hardware, with NVIDIA GPUs handling prefill and ASICs from Cerebras, SambaNova, Positron AI and d-Matrix handling decode. In its own open benchmark on GPT-OSS 120B it measured 1,025 to 1,234 output tokens per second against 100 to 121 on an unnamed GPU cloud, and up to 16.2x faster end to end. Founders Finn Puklowski and Jason Goodison raised a $15M seed led by FUSE, an up to $400M debt facility from Upper90 and, on October 27, 2026, a $100M Series A co-led by Blackbird and Abstract.

Example models: MiniMax M2.7, DeepSeek V3.2, GPT-OSS 120B

Full General Compute profile

Should you choose Cerebras or General Compute?

Cerebras

Choose Cerebras for

Top published speed on GPT-OSS 120B
Long streamed outputs
OpenAI's Ultrafast GPT-5.6 Sol preview

General Compute

Choose General Compute for

Cheaper GPT-OSS 120B input
Custom checkpoints on ASIC decode
Capacity across several chip vendors

Cerebras vs General Compute at a glance

Attribute	Cerebras	General Compute
Model access	Open weights	Open weights
Flagship models	GPT-OSS 120B, Qwen 3.8 27B	MiniMax M2.7, DeepSeek V3.2, GPT-OSS 120B
Speed	~3,000 tok/s on GPT-OSS 120B	1,000+ tok/s on GPT-OSS 120B (vendor)
Price	$0.35 in, $0.75 out (GPT-OSS 120B)	$0.21–$0.28 in, $0.38–$1.20 out per 1M
Customization	Unknown	Custom LoRA and fine-tuned checkpoints
Deployment	Shared API, dedicated, partners	Serverless API, dedicated racks, bare metal
Long context	131K on GPT-OSS 120B, 128K on Qwen 3.8 27B	192K (MiniMax M2.7)

Frequently asked questions

What is the difference between Cerebras and General Compute?

Cerebras sells its wafer-scale inference directly. General Compute runs decode on Cerebras and other ASICs inside its own cloud.

When should I choose Cerebras over General Compute?

Top published speed on GPT-OSS 120B; Long streamed outputs; OpenAI's Ultrafast GPT-5.6 Sol preview.

When should I choose General Compute over Cerebras?

Cheaper GPT-OSS 120B input; Custom checkpoints on ASIC decode; Capacity across several chip vendors.

Is Cerebras or General Compute cheaper?

Cerebras: $0.35 in, $0.75 out (GPT-OSS 120B). General Compute: $0.21–$0.28 in, $0.38–$1.20 out per 1M. The cheaper choice depends on the model and workload.

Which has more context, Cerebras or General Compute?

Cerebras: 131K on GPT-OSS 120B, 128K on Qwen 3.8 27B. General Compute: 192K (MiniMax M2.7).

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.

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