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GMI Cloud vs Relace
Relace sells fast apply, search and compaction models for coding agents; GMI Cloud hosts general text and media models. Complementary pieces.
By The Subconscious Team · Updated
GMI Cloud vs Relace: key differences
Relace's small models do the utility work of a coding agent. relace-apply-3 merges edit snippets at about 10,000 tokens per second with 128K tokens of input and output, its agentic search answers questions about large codebases in seconds, and its compaction model runs at 50,000 tokens per second. GMI Cloud is general infrastructure: an OpenAI compatible Inference Engine with 200+ text, image, video and audio models, run on NVIDIA hardware it owns in the US and APAC. Relace sells tools that sit around a model, while GMI sells the models and the GPUs underneath them.
The two meet on deployment control. Relace can be self-hosted for enterprises that keep code in-house, and GMI offers in-country facilities in Taiwan, Thailand and Malaysia, so an APAC engineering team could keep both the main model and the tooling in-region. Relace errors past 128K tokens, so very large files need a fallback model, which could come from GMI's LLM catalog. Pick GMI to host models. Add Relace where apply and search steps slow down or cost too much.
What GMI Cloud and Relace 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 profileRelace
Relace started out training small, fast models that act as tools for coding agents, and by October 2026 its homepage led with open-model inference instead. It says it served 30 trillion tokens in the 30 days to late October and ranks among the top providers on OpenRouter. The hosted catalog covers DeepSeek V4 Pro, V4 Flash and V4.1 Flash, Kimi K3, GLM 5.3, GLM 5.3 Flash and GLM 5.2 over OpenAI and Anthropic compatible APIs, billed per token with no subscription. Prices run from $0.07 in and $0.14 out per million tokens on DeepSeek V4 Flash to $2.00 in and $14.00 out on Kimi K3, and Relace says it reprices often.
Example models: DeepSeek V4.1 Flash, Kimi K3, GLM 5.3, relace-apply-3
Full Relace profileShould you choose GMI Cloud or Relace?
GMI Cloud
Choose GMI Cloud for
- The general LLM behind a coding agent, hosted in APAC
- Multimodal features alongside code tooling
- Moving to reserved capacity as traffic grows
Relace
Choose Relace for
- Applying AI edits to user codebases in app builders
- Parallel search over large repos for PR review
- Self-hosted code utilities for in-house codebases
GMI Cloud vs Relace at a glance
| Attribute | GMI Cloud | Relace |
|---|---|---|
| Model access | Open and third-party models | Open weights, plus specialist coding models |
| Flagship models | DeepSeek V4 Flash, GLM-5.2, Google Veo | DeepSeek V4.1 Flash, Kimi K3, GLM 5.3, relace-apply-3 |
| Speed | Near bare-metal performance | ~10,000 tok/s apply |
| Price | H100 from $2.60/GPU-hr | $0.07 in, $0.50 out (DeepSeek V4.1 Flash) |
| Customization | Unknown | Unknown |
| Deployment | Shared, autoscaling, reserved GPUs | Hosted API, OpenRouter or self-hosted |
| Long context | Varies by model | 128K on apply; varies by open model |
Frequently asked questions
What is the difference between GMI Cloud and Relace?
Relace sells fast apply, search and compaction models for coding agents; GMI Cloud hosts general text and media models. Complementary pieces.
When should I choose GMI Cloud over Relace?
The general LLM behind a coding agent, hosted in APAC; Multimodal features alongside code tooling; Moving to reserved capacity as traffic grows.
When should I choose Relace over GMI Cloud?
Applying AI edits to user codebases in app builders; Parallel search over large repos for PR review; Self-hosted code utilities for in-house codebases.
Is GMI Cloud or Relace cheaper?
GMI Cloud: H100 from $2.60/GPU-hr. Relace: $0.07 in, $0.50 out (DeepSeek V4.1 Flash). The cheaper choice depends on the model and workload.
Which has more context, GMI Cloud or Relace?
GMI Cloud: Varies by model. Relace: 128K on apply; varies by open model.
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.