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Cerebras vs GMI Cloud
GMI Cloud owns NVIDIA GPUs across APAC and serves 200+ text and media models. Cerebras owns wafer-scale chips and serves two models very fast.
By The Subconscious Team · Updated
Cerebras vs GMI Cloud: key differences
Both own their hardware, and the hardware says a lot. GMI Cloud is an NVIDIA Cloud Partner running H100, H200 and B200 in Tier-4 data centers in the US, Taiwan, Thailand and Malaysia. Its Inference Engine serves 200+ models, including 45+ LLMs and 50+ video models like Google Veo and Kling. Cerebras runs its own wafer-scale chip and serves GPT-OSS 120B near 3,000 tokens per second at $0.35 in and $0.75 out, with Qwen 3.8 27B the only other shared model.
GMI wins on multimodal breadth, APAC data residency and a path from shared endpoints to reserved H100 or H200 capacity on one API. It has less developer mindshare and third-party benchmarking than US peers, so its claims need testing. Cerebras wins on raw generation speed and has a wafer-scale route to OpenAI's Ultrafast GPT-5.6 Sol preview. Pick GMI for in-region Asian workloads or apps mixing LLMs and video. Pick Cerebras for voice and streaming, where every token's arrival counts.
What Cerebras and GMI Cloud 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 profileGMI Cloud
GMI Cloud is a vertically integrated GPU cloud and inference platform that owns its NVIDIA hardware. It runs Tier-4 data centers in Silicon Valley, Colorado, Taiwan, Thailand and Malaysia, and as an NVIDIA Cloud Partner it gets priority access to H100, H200, B200 and GB200 supply, with GB300 on pre-order. In March 2026 it announced a 1GW sovereign AI factory in Kagoshima, Japan. The company pivoted from crypto mining into AI, which gave it experience standing up high-density power and cooling fast. In September 2026 it raised $668M: a $223M Series B led by ARCHIV with NVIDIA participating, plus a $445M credit facility led by CTBC. It reports over $600M in contracted ARR and about 4T tokens a week on its inference platform.
Example models: DeepSeek V4 Flash, GLM-5.2, Google Veo
Full GMI Cloud profileShould you choose Cerebras or GMI Cloud?
Cerebras
Choose Cerebras for
- The fastest published tokens per second on GPT-OSS 120B
- Voice and live autocomplete
- Long streamed outputs
GMI Cloud
Choose GMI Cloud for
- APAC data residency in Taiwan, Thailand or Malaysia
- LLMs plus video, image and audio models on one API
- Reserved H100 or H200 capacity on owned hardware
Cerebras vs GMI Cloud at a glance
| Attribute | Cerebras | GMI Cloud |
|---|---|---|
| Model access | Open weights | Open and third-party models |
| Flagship models | GPT-OSS 120B, Qwen 3.8 27B | DeepSeek V4 Flash, GLM-5.2, Google Veo |
| Speed | ~3,000 tok/s on GPT-OSS 120B | Near bare-metal performance |
| Price | $0.35 in, $0.75 out (GPT-OSS 120B) | H100 from $2.60/GPU-hr |
| Customization | Unknown | Unknown |
| Deployment | Shared API, dedicated, partners | Shared, autoscaling, reserved GPUs |
| Long context | 131K on GPT-OSS 120B, 128K on Qwen 3.8 27B | Varies by model |
Frequently asked questions
What is the difference between Cerebras and GMI Cloud?
GMI Cloud owns NVIDIA GPUs across APAC and serves 200+ text and media models. Cerebras owns wafer-scale chips and serves two models very fast.
When should I choose Cerebras over GMI Cloud?
The fastest published tokens per second on GPT-OSS 120B; Voice and live autocomplete; Long streamed outputs.
When should I choose GMI Cloud over Cerebras?
APAC data residency in Taiwan, Thailand or Malaysia; LLMs plus video, image and audio models on one API; Reserved H100 or H200 capacity on owned hardware.
Is Cerebras or GMI Cloud cheaper?
Cerebras: $0.35 in, $0.75 out (GPT-OSS 120B). GMI Cloud: H100 from $2.60/GPU-hr. The cheaper choice depends on the model and workload.
Which has more context, Cerebras or GMI Cloud?
Cerebras: 131K on GPT-OSS 120B, 128K on Qwen 3.8 27B. GMI Cloud: Varies by model.
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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.