# GMI Cloud vs Wafer

> GMI Cloud sells owned hardware and a broad multimodal catalog; Wafer sells agent-tuned open-model stacks and a flat-rate coding pass.

Canonical: https://www.subconscious.dev/compare/gmi-cloud-vs-wafer · By The Subconscious Team · Updated September 30, 2026

## How they compare

Both companies claim a speed edge from engineering below the model. GMI says its in-house Cluster Engine runs near bare metal and recovers the 10 to 15% overhead of standard cloud virtualization. Wafer uses AI agents to tune batching, quantization, engines and kernels per workload, and reports its tuned Qwen 3.5 397B at 2.8x stock SGLang, with GLM 5.1 and DeepSeek V4 Pro each 2x a vLLM baseline. Both sets of numbers are self-reported and neither company has much third-party benchmarking, so test before committing.

Beyond speed they diverge. GMI owns NVIDIA hardware across the US and APAC and serves 100+ models, including video, image and audio, with a path to reserved GPUs. Wafer is very young, with a small hosted catalog of big open models, and it runs on NVIDIA or AMD. Its Wafer Pass starts at $10 a week for Claude Code, Cline and OpenHands users. Choose GMI for multimodal breadth and APAC residency. Choose Wafer for coding agents on large open models or a dedicated endpoint re-tuned against a strict latency SLO.

## What each one does

### 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 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.

### Wafer

Wafer builds AI agents that act as GPU performance engineers, then sells inference on the stacks those agents tune. The company came out of Y Combinator's Summer 2025 batch as a "Cursor for CUDA" that turned slow PyTorch into custom kernels. Founders Emilio Andere and Steven Arellano are based in San Francisco. Its agents profile a workload, generate candidate configs across batching, decoding, quantization, engines, kernels and hardware, measure each one and deploy the winner.

## Which is best, and when

### Choose GMI Cloud for

- Multimodal apps across text, image, video and audio
- In-country hosting in Taiwan, Thailand or Malaysia
- Owned hardware with reserved H100 or H200 options

### Choose Wafer for

- Flat-rate weekly access for agentic coding tools
- Large open models tuned for interactive speed
- Hedging GPU supply across NVIDIA and AMD

## At a glance

| Attribute | GMI Cloud | Wafer |
|---|---|---|
| Model access | Open and third-party models | Open weights |
| Flagship models | GLM-4.7-Flash, Google Veo | Qwen 3.5 397B Turbo, GLM 5.1 Turbo |
| Speed | Near bare-metal performance | 2–2.8x vs stock vLLM or SGLang |
| Price | $0.07 in, $0.40 out (GLM-4.7-Flash) | Wafer Pass from $10 a week |
| Customization | - | Agent-tuned dedicated deployments |
| Deployment | Shared, autoscaling, reserved GPUs | Serverless pass, dedicated |
| Long context | Varies by model | Varies by model |

## FAQ

### What is the difference between GMI Cloud and Wafer?

GMI Cloud sells owned hardware and a broad multimodal catalog; Wafer sells agent-tuned open-model stacks and a flat-rate coding pass.

### When should I choose GMI Cloud over Wafer?

Multimodal apps across text, image, video and audio; In-country hosting in Taiwan, Thailand or Malaysia; Owned hardware with reserved H100 or H200 options.

### When should I choose Wafer over GMI Cloud?

Flat-rate weekly access for agentic coding tools; Large open models tuned for interactive speed; Hedging GPU supply across NVIDIA and AMD.

### Is GMI Cloud or Wafer cheaper?

GMI Cloud: $0.07 in, $0.40 out (GLM-4.7-Flash). Wafer: Wafer Pass from $10 a week. The cheaper choice depends on the model and workload.

### Which has more context, GMI Cloud or Wafer?

GMI Cloud: Varies by model. Wafer: Varies by model.

## Running long-horizon agents?

If your agents run past 200K tokens, compare both against Subconscious: [Subconscious vs GMI Cloud](https://www.subconscious.dev/compare/subconscious-vs-gmi-cloud.md), [Subconscious vs Wafer](https://www.subconscious.dev/compare/subconscious-vs-wafer.md).

Full profiles: [GMI Cloud](https://www.subconscious.dev/providers/gmi-cloud.md), [Wafer](https://www.subconscious.dev/providers/wafer.md).