Moonshot AI vs GMI Cloud
Moonshot's flagship open model against a GPU cloud that owns hardware across Asia and the US. GMI brings residency and media models; Moonshot brings the stronger LLM.
By The Subconscious Team · Updated
Moonshot AI vs GMI Cloud: key differences
GMI Cloud and Moonshot meet different needs. GMI owns its NVIDIA hardware and runs Tier-4 data centers in Silicon Valley, Colorado, Taiwan, Thailand and Malaysia, which gives Asia-Pacific companies in-country inference. Its Inference Engine exposes 100+ models, including 45+ LLMs and 50+ video models, through an OpenAI-compatible API, with entry pricing like GLM-4.7-Flash at $0.07 in and $0.40 out. Moonshot offers one standout LLM, Kimi K3, at $3 in and $15 out, with 1M context, native vision and near-frontier coding scores. GMI's listing does not name Kimi.
The deciding axes are capability, residency and modality. K3 wins on hard coding and document-heavy research. GMI wins when data must stay in Taiwan, Thailand or Malaysia, or when an app wants LLMs, image, video and audio on one bill. GMI's LLM catalog is smaller and less current than larger hosts, and its performance claims need your own testing. Moonshot's issues are K3's speed and the capacity crunch that paused new subscriptions after launch. Teams that need K3 in APAC could weigh self-hosting it, a 64+ accelerator job, on GMI's reserved H100 or H200 capacity.
What Moonshot AI and GMI Cloud do
Moonshot AI
Moonshot AI is the Beijing lab behind the Kimi models. Its flagship Kimi K3 launched July 16, 2026 as a 2.8 trillion parameter mixture-of-experts model that activates 16 of 896 experts per token, with native vision and a 1M token context. It is the first open model in the 3T class, and full weights landed on Hugging Face on July 27. The hosted API costs $3 in and $15 out per million tokens, with cached input at $0.30, and it runs through an OpenAI-compatible endpoint, Kimi Code in the terminal, OpenRouter and Cloudflare Workers AI.
Example models: Kimi K3, Kimi K2.6
Full Moonshot AI 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 and B200 supply. The company pivoted from crypto mining into AI, which gave it experience standing up high-density power and cooling fast. An $82M Series A came from Headline, Wistron and Thai energy group Banpu.
Example models: GLM-4.7-Flash, Google Veo
Full GMI Cloud profileShould you choose Moonshot AI or GMI Cloud?
Moonshot AI
Choose Moonshot AI for
- Hard coding and research tasks on open weights
- 1M context with native vision
- Teams without data residency constraints
GMI Cloud
Choose GMI Cloud for
- Asia-Pacific teams with in-region data rules
- Multimodal apps mixing LLMs and video generation
- Reserved H100 or H200 capacity on one API
Moonshot AI vs GMI Cloud at a glance
| Attribute | ||
|---|---|---|
| Model access | Open weights, custom license | Open and third-party models |
| Flagship models | Kimi K3, Kimi K2.6 | GLM-4.7-Flash, Google Veo |
| Speed | ~33 tok/s on Kimi K3 | Near bare-metal performance |
| Price | $3 in, $15 out (Kimi K3) | $0.07 in, $0.40 out (GLM-4.7-Flash) |
| Customization | Open weights to fine-tune | Unknown |
| Deployment | API, Kimi Code, OpenRouter | Shared, autoscaling, reserved GPUs |
| Long context | 1M | Varies by model |
Frequently asked questions
What is the difference between Moonshot AI and GMI Cloud?
Moonshot's flagship open model against a GPU cloud that owns hardware across Asia and the US. GMI brings residency and media models; Moonshot brings the stronger LLM.
When should I choose Moonshot AI over GMI Cloud?
Hard coding and research tasks on open weights; 1M context with native vision; Teams without data residency constraints.
When should I choose GMI Cloud over Moonshot AI?
Asia-Pacific teams with in-region data rules; Multimodal apps mixing LLMs and video generation; Reserved H100 or H200 capacity on one API.
Is Moonshot AI or GMI Cloud cheaper?
Moonshot AI: $3 in, $15 out (Kimi K3). GMI Cloud: $0.07 in, $0.40 out (GLM-4.7-Flash). The cheaper choice depends on the model and workload.
Which has more context, Moonshot AI or GMI Cloud?
Moonshot AI: 1M. GMI Cloud: Varies by model.
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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.