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Compare GPU and LLM inference API pricing between EcoHash and Koyeb. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
| GPU Model ↑ | EcoHash Price | Koyeb Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A100 PCIE 40GB VRAM • Koyeb | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • Koyeb | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
H100 SXM 80GB VRAM • Koyeb | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
L40S 48GB VRAM • Koyeb | Not Available | — | ||
L40S 48GB VRAM • | ||||
RTX A6000 48GB VRAM • Koyeb | Not Available | — | ||
RTX A6000 48GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • EcoHash | Not Available | — | ||
RTX PRO 6000 96GB VRAM • | ||||
A100 PCIE 40GB VRAM • Koyeb | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • Koyeb | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
H100 SXM 80GB VRAM • Koyeb | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
L40S 48GB VRAM • Koyeb | Not Available | — | ||
L40S 48GB VRAM • | ||||
RTX A6000 48GB VRAM • Koyeb | Not Available | — | ||
RTX A6000 48GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • EcoHash | Not Available | — | ||
RTX PRO 6000 96GB VRAM • | ||||
| Model ↑ | EcoHash | Koyeb | Input Diff ↕ |
|---|---|---|---|
DeepSeek | $0.910 in $2.72 out | Not available | — |
Zhipu | $1.00 in $3.00 out | Not available | — |
Z AI | $1.25 in $4.30 out | Not available | — |
Moonshot | $2.00 in $12.00 out | Not available | — |
Meta | $0.100 in $0.100 out | Not available | — |
MiniMax | $0.200 in $0.900 out | Not available | — |
Alibaba | $0.150 in $0.500 out | Not available | — |
Alibaba | $1.90 in $5.70 out | Not available | — |
Alibaba | $0.400 in $0.800 out | Not available | — |
OpenAI | $0.100 in $0.0000 out | Not available | — |
Explore how these providers compare to other popular GPU cloud services
Compare EcoHash with another leading provider
Compare EcoHash with another leading provider
Compare EcoHash with another leading provider
Compare EcoHash with another leading provider
Compare EcoHash with another leading provider
Compare EcoHash with another leading provider
Offers configurations with 1, 2, 4, or 8 RTX Pro 6000 GPUs.
Supports automatic selection of LoRA/QLoRA fine-tuning over 1-4 GPUs.
Provides an API compatible with OpenAI for various AI models.
Users get full root access with shared filesystems on RTX Pro environments.
Inference endpoints can be deployed across multiple regions with failover.
Per-second billing with scale-to-zero across the GPU catalog
From RTX-4000-SFF-ADA and L4 through L40S, A100, H100, H200 and B200
Deploy applications close to users across multiple regions from a single push
Charged per second of GPU runtime, with scale-to-zero when idle
Pre-configured 2x, 4x and 8x GPU instances for larger workloads
Create an account on the EcoHash platform.
Select the desired GPU instances for your project.
Consult the EcoHash documentation to understand available features.
Launch your GPU environment for training or inference.
Start using the API for model inference or training tasks.
Sign up via the Koyeb console using email or GitHub
Select an instance type from the GPU catalog and configure your service
Push from a GitHub repo or Docker image and Koyeb handles the rest
Available across multiple global regions, including the Americas.
Offers support via documentation and community channels.
Global edge presence across North America, Europe and Asia
Documentation, community forum and paid support tiers