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Compare GPU and LLM inference API pricing between EcoHash and Jarvis Labs. Find the best rates for AI training, inference, and ML workloads.
Provider 1
Provider 2
| GPU Model ↑ | EcoHash Price | Jarvis Labs Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A100 PCIE 40GB VRAM • Jarvis Labs | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • Jarvis Labs | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
A30 24GB VRAM • Jarvis Labs | Not Available | — | ||
A30 24GB VRAM • | ||||
H100 SXM 80GB VRAM • Jarvis Labs | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • Jarvis Labs | Not Available | — | ||
H200 141GB VRAM • | ||||
L4 24GB VRAM • Jarvis Labs | Not Available | — | ||
L4 24GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • EcoHashJarvis Labs | ↓$0.00(0.0%) | |||
RTX PRO 6000 96GB VRAM • $1.89/hour Updated: 9/17/2026 $1.89/hour Updated: 9/20/2026 ★Best Price Price Difference:↓N/A(0.0%) | ||||
A100 PCIE 40GB VRAM • Jarvis Labs | Not Available | — | ||
A100 PCIE 40GB VRAM • | ||||
A100 SXM 80GB VRAM • Jarvis Labs | Not Available | — | ||
A100 SXM 80GB VRAM • | ||||
A30 24GB VRAM • Jarvis Labs | Not Available | — | ||
A30 24GB VRAM • | ||||
H100 SXM 80GB VRAM • Jarvis Labs | Not Available | — | ||
H100 SXM 80GB VRAM • | ||||
H200 141GB VRAM • Jarvis Labs | Not Available | — | ||
H200 141GB VRAM • | ||||
L4 24GB VRAM • Jarvis Labs | Not Available | — | ||
L4 24GB VRAM • | ||||
RTX PRO 6000 96GB VRAM • EcoHashJarvis Labs | ↓$0.00(0.0%) | |||
RTX PRO 6000 96GB VRAM • $1.89/hour Updated: 9/17/2026 $1.89/hour Updated: 9/20/2026 ★Best Price Price Difference:↓N/A(0.0%) | ||||
| Model ↑ | EcoHash | Jarvis Labs | 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.
Get access to powerful GPUs instantly with zero setup complexity
Boot templates in 1.8 seconds or VMs in under 90 seconds
Pay-as-you-go with per-minute billing and no upfront commitments
Comprehensive command-line and Python SDK with agent integration for Claude Code, Cursor, and other AI coding agents
Scale up to 8 GPUs per instance for demanding workloads
Easy pause, resume, and delete functionality for cost optimization
On-demand GPU instances with various configuration options
Pre-built environments for instant deployment
Full root access VMs for custom configurations
Per-minute billing with no minimum commitments and instant provisioning
Use spare capacity with significant discounts up to 56% off on-demand pricing
Save up to 21% with 1-month commitments or up to 32% with 6-month commitments
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 for a new account on the Jarvis Labs platform
Add funds to your account in the Recharge section
Explore the wide range of templates, configure your desired setup, and click Launch
Easily pause ⏸️, resume ▶️, and delete 🗑️ your instances with just a few clicks
Available across multiple global regions, including the Americas.
Offers support via documentation and community channels.
GPU clusters deployed in India (Noida) and Europe with flexible regional instance management
Documentation, tutorials, and getting started guides available