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Compare GPU and LLM inference API pricing between EcoHash and Modal. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
Average Price Difference: $1.14/hour between comparable GPUs
| GPU Model ↑ | EcoHash Price | Modal Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A10 24GB VRAM • Modal | Not Available | — | ||
A10 24GB VRAM • | ||||
A100 PCIE 40GB VRAM • Modal | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • Modal | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
B200 180GB VRAM • Modal | Not Available | — | ||
B200 180GB VRAM • | ||||
H100 SXM 80GB VRAM • Modal | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • Modal | Not Available | — | ||
H200 141GB VRAM • | ||||
HGX B300 288GB VRAM • Modal | Not Available | — | ||
HGX B300 288GB VRAM • | ||||
L4 24GB VRAM • Modal | Not Available | — | ||
L4 24GB VRAM • | ||||
L40S 48GB VRAM • Modal | Not Available | — | ||
L40S 48GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • EcoHashModal | ↓$1.14(37.6%) | |||
Tesla T4 16GB VRAM • Modal | Not Available | — | ||
Tesla T4 16GB VRAM • | ||||
A10 24GB VRAM • Modal | Not Available | — | ||
A10 24GB VRAM • | ||||
A100 PCIE 40GB VRAM • Modal | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • Modal | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
B200 180GB VRAM • Modal | Not Available | — | ||
B200 180GB VRAM • | ||||
H100 SXM 80GB VRAM • Modal | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • Modal | Not Available | — | ||
H200 141GB VRAM • | ||||
HGX B300 288GB VRAM • Modal | Not Available | — | ||
HGX B300 288GB VRAM • | ||||
L4 24GB VRAM • Modal | Not Available | — | ||
L4 24GB VRAM • | ||||
L40S 48GB VRAM • Modal | Not Available | — | ||
L40S 48GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • EcoHashModal | ↓$1.14(37.6%) | |||
Tesla T4 16GB VRAM • Modal | Not Available | — | ||
Tesla T4 16GB VRAM • | ||||
| Model ↑ | EcoHash | Modal | 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 | $0.090 in $0.370 out | Not available | — |
Alibaba | $1.90 in $5.70 out | Not available | — |
Alibaba | $0.400 in $0.800 out | Not available | — |
Alibaba | $0.400 in $0.400 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.
Run Python functions on NVIDIA GPUs without provisioning instances; cold starts in seconds
Pay for actual GPU runtime at sub-minute granularity, with scale-to-zero by default
Define environments in code, with automatic image building and caching
From T4 and L4 through A100, L40S, H100, H200 and B200
Charged per second of GPU runtime, with scale-to-zero when idle
Monthly free credits for experimentation and personal projects
Volume commitments and enterprise support for production deployments
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.
Run `pip install modal` and authenticate via the CLI
Decorate a Python function with the desired GPU and image specification
Invoke locally or deploy as a long-lived endpoint or scheduled job
Available across multiple global regions, including the Americas.
Offers support via documentation and community channels.
Multi-region availability across North America and Europe
Documentation, community forum, and enterprise support for paid plans