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GMI Cloud vs OpenScale
GMI Cloud owns its GPUs and serves 100+ multimodal models with APAC data residency. OpenScale sells one open model cheaply from Singapore.
By The Subconscious Team · Updated
GMI Cloud vs OpenScale: key differences
GMI Cloud owns its NVIDIA hardware in Tier-4 data centers across the US, Taiwan, Thailand and Malaysia, serves 100+ text, image, video and audio models, and offers shared, autoscaling and reserved tiers on one OpenAI-compatible API. OpenScale serves DeepSeek V4.1 Flash at $0.06 in, $0.003 cached and $0.24 out per million tokens under a 50% promotion, at 200+ tokens per second, with a fast tier at about twice the speed. It lists a single Singapore datacenter for that model.
GMI Cloud is the choice for predictable capacity, multimodal apps and reserved GPUs. OpenScale is the cheaper choice for DeepSeek V4.1 Flash behind coding agents, with Anthropic and OpenAI Responses formats and no commitments.
What GMI Cloud and OpenScale do
GMI 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 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 GMI Cloud or OpenScale?
GMI Cloud vs OpenScale at a glance
| Attribute | GMI Cloud | OpenScale |
|---|---|---|
| Model access | Open and third-party models | Open weights |
| Flagship models | DeepSeek V4 Flash, GLM-5.2, Google Veo | DeepSeek V4.1 Flash |
| Speed | Near bare-metal performance | 200+ tok/s; fast tier ~2x |
| Price | H100 from $2.60/GPU-hr | $0.06 in, $0.24 out (promo, DeepSeek V4.1 Flash) |
| Customization | Unknown | N/A |
| Deployment | Shared, autoscaling, reserved GPUs | Serverless API |
| Long context | Varies by model | 1M context |
Frequently asked questions
What is the difference between GMI Cloud and OpenScale?
GMI Cloud owns its GPUs and serves 100+ multimodal models with APAC data residency. OpenScale sells one open model cheaply from Singapore.
When should I choose GMI Cloud over OpenScale?
Predictable capacity on owned hardware; APAC data residency in several countries; Multimodal apps on one bill.
When should I choose OpenScale over GMI Cloud?
Very cheap DeepSeek V4.1 Flash calls; Cache-heavy coding agent traffic; Prepaid credits with no minimums.
Is GMI Cloud or OpenScale cheaper?
GMI Cloud: H100 from $2.60/GPU-hr. 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, GMI Cloud or OpenScale?
GMI Cloud: Varies by model. 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.