# FluidStack vs General Compute

FluidStack ghi nhận 154.620 lượt truy cập hàng tháng với mức tăng trưởng so với tháng trước là +7,3% và giá Trả phí, Liên hệ để biết giá. General Compute ghi nhận 13.828 lượt truy cập hàng tháng với mức tăng trưởng +7,2% và giá Dùng thử miễn phí, Liên hệ để biết giá.

| Chỉ số | [FluidStack](https://openaitools.app/vi/tool/fluidstack) | [General Compute](https://openaitools.app/vi/tool/general-compute) |
| :--- | :--- | :--- |
| URL trang web | https://fluidstack.io | https://www.generalcompute.com |
| Danh mục | Công cụ cho lập trình viên AI, Mô hình AI, Large Language Models (LLMs) | AI API, Mô hình AI, Large Language Models (LLMs), Công cụ cho lập trình viên AI |
| Mô hình giá | Trả phí, Liên hệ để biết giá | Dùng thử miễn phí, Liên hệ để biết giá |
| Lượt truy cập hàng tháng | 154.620 | 13.828 |
| Tốc độ tăng trưởng theo tháng | +7,3% | +7,2% |
| Thị trường chính | Hoa Kỳ | Hoa Kỳ |
| Truy cập trực tiếp | 47.869 | 6.732 |
| Điểm đánh giá | 4,4 | 4,2 |
| Số lượt lưu | 1 | 0 |
| Nền tảng được hỗ trợ | Trang web | Trang web |

## FluidStack

FluidStack builds and operates large-scale compute infrastructure for AI, including gigawatt-class data centers and GPU clusters used for training and inference. The company designs its own power, cooling and data center systems, onshores manufacturing and deploys solar generation to supply the power its clusters need. Rather than a self-serve cloud console, FluidStack works with AI labs and enterprises to provision large reserved clusters, with orchestration tooling for the ML frameworks and schedulers those teams already use.

**Giá & các gói:** Enterprise and contact-for-pricing. FluidStack does not publish per-GPU-hour rates or a self-serve sign-up on its website; capacity is scoped and quoted through a direct sales conversation based on cluster size, duration and hardware. Catalogue listings classify it as a paid product requiring contact for pricing.

- **Datacenter-scale compute built in-house:** FluidStack designs and builds large AI data centers, including high-density campuses with significant per-site power capacity, rather than reselling capacity from other clouds.
- **GPU clusters for training and inference:** Clusters are architected for large-scale model training and inference, with high-bandwidth interconnect and orchestration suitable for distributed workloads.
- **Power and cooling engineered together:** The company develops off-grid solar and recirculating closed-loop cooling, treating power and water efficiency as core engineering problems.
- **Managed operations and reliability:** Smart hands, cluster provisioning and operations support let research teams focus on models while FluidStack runs the physical and orchestration layers.
- **US-built and onshored supply chain:** Data centers are built in the United States with onshored manufacturing of compute and power infrastructure, a deliberate supply-chain and sovereignty choice.

**Điểm mạnh:** Purpose-built AI infrastructure rather than generic cloud resale; Power, cooling and data center design handled in-house, which matters at scale; Managed provisioning and operations for large training and inference clusters; Explicit positioning on US-built, onshored infrastructure

**Hạn chế:** No published self-serve pricing or instant sign-up; access requires a sales conversation; Enterprise-scale focus means very small individual workloads may not be a fit; Capacity is concentrated in US locations, which may matter for latency-sensitive or data-residency-bound teams

[Profile (Markdown)](https://openaitools.app/vi/tool/fluidstack.md)

## General Compute

General Compute is an inference cloud built around alternative AI silicon rather than standard GPU fleets. The company buys racks of accelerators, racks them in colocation data centres, and handles the cooling, power, and networking itself. On top of that hardware it runs a disaggregated inference stack that splits each request: prompt processing runs on NVIDIA GPUs for prefill, while token generation runs on faster decode chips such as Cerebras, SambaNova, Positron AI, and d-Matrix. Customers get bare metal access or a tokens-per-second SLA.

**Giá & các gói:** Pricing is contract-based and requires a call; it is quoted per engagement according to term, volume, and site rather than published as self-serve rates. Indications of free trial availability exist, but no public price list is shown.

- **Disaggregated prefill and decode:** Prompt processing runs on NVIDIA GPUs while token generation runs on faster ASICs from Cerebras, SambaNova, Positron AI, and d-Matrix.
- **Bare metal or SLA endpoint:** Buy racks of GPUs for prefill and ASICs for decode, with General Compute handling cooling, power, networking, and the orchestration software.
- **Per-chip specifications:** Inspect each accelerator in an interactive 3D view with its SRAM, power draw, cooling type, and the workloads it suits best.
- **Software for non-standard silicon:** The platform abstracts bespoke hardware so models run without customers having to learn a new chip toolchain.
- **Throughput SLA and failover:** Multi-provider redundancy and automatic failover for production inference, backed by contracted throughput guarantees.

**Điểm mạnh:** Purpose-built for very low token latency rather than generic GPU rental; Handles cooling, power, networking, and orchestration so customers don't have to; Mix of GPU prefill and ASIC decode can improve throughput per rack; Well funded ($100M Series A) with named chip and partner ecosystem

**Hạn chế:** Pricing is contract-based rather than published per-token rates, which slows down self-serve evaluation; No instant public signup for compute; access begins with a sales conversation; Newest deployments are scheduled from Q1 2027, so capacity is in ramp-up; Workloads need to fit the disaggregated prefill/decode model to get the full speed benefit

[Profile (Markdown)](https://openaitools.app/vi/tool/general-compute.md)

## Câu hỏi thường gặp

### FluidStack và General Compute so sánh thế nào về lưu lượng hàng tháng?

FluidStack có 154.620 lượt truy cập hàng tháng, trong khi General Compute có 13.828. Ước tính lưu lượng phản ánh quy mô khán giả chứ không phải chất lượng sản phẩm.

### Tốc độ tăng trưởng của họ so sánh thế nào?

FluidStack có tốc độ tăng trưởng so với tháng trước là +7,3%; General Compute là +7,2%.

### Giá cả so sánh thế nào?

FluidStack: Trả phí, Liên hệ để biết giá. Enterprise and contact-for-pricing. FluidStack does not publish per-GPU-hour rates or a self-serve sign-up on its website; capacity is scoped and quoted through a direct sales conversation based on cluster size, duration and hardware. Catalogue listings classify it as a paid product requiring contact for pricing. General Compute: Dùng thử miễn phí, Liên hệ để biết giá. Pricing is contract-based and requires a call; it is quoted per engagement according to term, volume, and site rather than published as self-serve rates. Indications of free trial availability exist, but no public price list is shown.

## Lựa chọn thay thế

| # | Tên công cụ | Lượt truy cập hàng tháng | Tốc độ tăng trưởng theo tháng | Mô hình giá | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Groq](https://openaitools.app/vi/tool/groq) | 3.987.936 | +10% | Trả phí | Suy luận AI siêu nhanh trên nền tảng LPU và LPX | [.md](https://openaitools.app/vi/tool/groq.md) |
| 2 | [fal.ai](https://openaitools.app/vi/tool/fal-ai) | 3.093.684 | -3,7% | Paid, pay-as-you-go usage-based pricing | Delivers developer-first serverless endpoints optimized for generative media models rather than general-purpose infrastructure. | [.md](https://openaitools.app/vi/tool/fal-ai.md) |
| 3 | [RunPod](https://openaitools.app/vi/tool/runpod) | 2.881.043 | +5,9% | Trả phí | RunPod is a cloud platform for AI and machine learning workloads that rents GPU compute by the second. It offers Pods for persistent GPU instances, Serverless endpoints that autoscale inference from zero, and multi-node | [.md](https://openaitools.app/vi/tool/runpod.md) |
| 4 | [Together AI](https://openaitools.app/vi/tool/together-ai) | 1.645.930 | +64,9% | Freemium, Trả phí | Together AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all b | [.md](https://openaitools.app/vi/tool/together-ai.md) |
| 5 | [Vast.ai](https://openaitools.app/vi/tool/vast-ai) | 1.257.554 | +2,8% | Trả phí | Thuê GPU đám mây theo từng giây từ chợ toàn cầu | [.md](https://openaitools.app/vi/tool/vast-ai.md) |
| 6 | [Modal](https://openaitools.app/vi/tool/modal-com) | 1.196.021 | +30,2% | Freemium, Liên hệ để biết giá | Hạ tầng đám mây serverless cho khối lượng công việc AI và dữ liệu | [.md](https://openaitools.app/vi/tool/modal-com.md) |
| 7 | [Nebius](https://openaitools.app/vi/tool/nebius) | 1.145.711 | +10,7% | Trả phí, Liên hệ để biết giá | Nebius is an AI-focused cloud platform that gives teams non-virtualized NVIDIA GPU clusters, managed MLOps tooling, and a serverless inference layer so they can move from experiment to production on one stack. | [.md](https://openaitools.app/vi/tool/nebius.md) |
| 8 | [Salad](https://openaitools.app/vi/tool/salad-gpu-cloud) | 713.519 | +10,4% | Dùng thử miễn phí, Trả phí, Liên hệ để biết giá | Đám mây GPU phân tán điều phối các GPU tiêu dùng nhàn rỗi trên toàn cầu | [.md](https://openaitools.app/vi/tool/salad-gpu-cloud.md) |
| 9 | [Cerebras](https://openaitools.app/vi/tool/cerebras) | 701.013 | -12,6% | Liên hệ để biết giá | Suy luận AI nhanh nhất thế giới, vận hành bởi con chip lớn nhất thế giới | [.md](https://openaitools.app/vi/tool/cerebras.md) |
| 10 | [DeepInfra](https://openaitools.app/vi/tool/deep-infra) | 457.810 | -8,9% | Trả phí | Specializes in cost-effective serverless API inference for open-weights models instead of raw infrastructure rentals. | [.md](https://openaitools.app/vi/tool/deep-infra.md) |

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Nguồn: https://openaitools.app/vi/compare/fluidstack-vs-general-compute

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