# Venice vs GMI Cloud > Both run multimodal catalogs behind OpenAI-compatible APIs. GMI Cloud owns its GPUs and offers APAC residency and reserved capacity; Venice offers zero retention and uncensored models. Canonical: https://www.subconscious.dev/compare/venice-vs-gmi-cloud · By The Subconscious Team · Updated September 30, 2026 ## How they compare GMI Cloud is infrastructure first. It owns NVIDIA hardware in Tier-4 data centers in Silicon Valley, Colorado, Taiwan, Thailand and Malaysia, and says its Cluster Engine recovers the 10 to 15% overhead of standard virtualization. Its Inference Engine exposes 100+ models, including 45+ LLMs and 50+ video models from providers like Google Veo, Kling and MiniMax, with GLM-4.7-Flash at $0.07 in and $0.40 out. Venice owns no published hardware story. Its pitch is data handling: zero retention on open models, TEE or end-to-end encryption on some, and an anonymized tier for closed models from Anthropic, OpenAI and Google. It lists 370+ models, with GLM 4.7 Flash at $0.06 in and $0.40 out. Growth path and geography favor GMI. Customers can start on shared endpoints, move to autoscaling, then reserve H100 or H200 capacity on the same API, and APAC companies can keep inference in-country. Venice is serverless only. Venice leads on openness: uncensored fine-tunes, 1M context on most current models, and payment in USD, crypto, x402 USDC or DIEM credits. GMI's LLM catalog is smaller and less current than larger US hosts, and its claims have little third-party benchmarking. Venice's closed-model access carries a markup and leaves prompts visible upstream. Pick GMI for regional compliance and reserved GPUs, Venice for privacy on shared inference. ## What each one does ### Venice Venice is a privacy-focused AI platform founded in 2024 by Erik Voorhees, the crypto entrepreneur behind ShapeShift. It pairs a consumer chat app with a developer API that works as a drop-in replacement for OpenAI's chat endpoint and covers text, image, audio and video across 370+ models. Open models such as GLM 5.3, Kimi K3, DeepSeek V4 and Venice's own uncensored fine-tunes run under a private tier with contract-enforced zero data retention, and some add TEE inference or end-to-end encryption, where only an attested enclave can decrypt the prompt. Closed models from Anthropic, OpenAI and Google are proxied under an anonymized tier that hides user identity but leaves prompt content visible to the upstream provider. ### 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. ## Which is best, and when ### Choose Venice for - Zero-retention inference without reserved hardware - Proxied closed models under an anonymized tier - Token-staked daily API credits ### Choose GMI Cloud for - APAC data residency in Taiwan, Thailand or Malaysia - Moving from shared endpoints to reserved GPUs - Video generation and LLMs on owned hardware ## At a glance | Attribute | Venice | GMI Cloud | |---|---|---| | Model access | Open weights, plus proxied closed models | Open and third-party models | | Flagship models | GLM 5.3, Kimi K3, DeepSeek V4 Pro | GLM-4.7-Flash, Google Veo | | Speed | - | Near bare-metal performance | | Price | $0.06–$12 in, $0.28–$60 out per 1M; DIEM staking | $0.07 in, $0.40 out (GLM-4.7-Flash) | | Customization | - | - | | Deployment | Serverless API, consumer app | Shared, autoscaling, reserved GPUs | | Long context | 1M on most current models | Varies by model | ## FAQ ### What is the difference between Venice and GMI Cloud? Both run multimodal catalogs behind OpenAI-compatible APIs. GMI Cloud owns its GPUs and offers APAC residency and reserved capacity; Venice offers zero retention and uncensored models. ### When should I choose Venice over GMI Cloud? Zero-retention inference without reserved hardware; Proxied closed models under an anonymized tier; Token-staked daily API credits. ### When should I choose GMI Cloud over Venice? APAC data residency in Taiwan, Thailand or Malaysia; Moving from shared endpoints to reserved GPUs; Video generation and LLMs on owned hardware. ### Is Venice or GMI Cloud cheaper? Venice: $0.06–$12 in, $0.28–$60 out per 1M; DIEM staking. 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, Venice or GMI Cloud? Venice: 1M on most current models. GMI Cloud: Varies by model. ## Running long-horizon agents? If your agents run past 200K tokens, compare both against Subconscious: [Subconscious vs Venice](https://www.subconscious.dev/compare/subconscious-vs-venice.md), [Subconscious vs GMI Cloud](https://www.subconscious.dev/compare/subconscious-vs-gmi-cloud.md). Full profiles: [Venice](https://www.subconscious.dev/providers/venice.md), [GMI Cloud](https://www.subconscious.dev/providers/gmi-cloud.md).