Codesphere Free GPU Workspace

Free GPU & Compute | Amount: 1 free GPU workspace with 20 GB storage (shared GPU, unlimited hours but auto-shutdown after 60 min idle) | AI-generated | 1/5 InstantSignup and get credits instantly — no credit card, no approval active
2026-02-26
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Source: https://codesphere.com/

Description

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+ 1 Codesphere offers one free GPU workspace per user with 20 GB of storage and a shared GPU — no credit card required. Unlike notebook-only platforms (Colab, Kaggle), Codesphere gives you a full cloud development environment where you can run any workload, not just Jupyter notebooks. The free tier includes 3 workspaces (with GPU on one) and 3 team seats. The catch: free workspaces auto-shutdown after ~60 minutes of inactivity, and GPU availability is limited by demand.

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+ 2  

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+ 3

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+ 4  

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+ 5 Registration (Step-by-Step)

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+ 6  

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+ 7 1. Go to codesphere.com or the early access signup at signup.codesphere.com

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+ 8 2. Create an account — no credit card required

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+ 9 3. You receive 3 free workspaces and 1 free shared GPU automatically

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+ 10 4. Create a new workspace and select the GPU option

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+ 11 5. Choose from available templates (Stable Diffusion, LLM inference, etc.) or start with a blank environment

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+ 12 6. Start coding — your workspace includes a full IDE, terminal, and deployment pipeline

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+ 13  

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+ 14 Caveats:

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+ 15 • Free workspaces turn off after ~60 minutes of inactivity (no IDE activity). They boot back up in seconds when you return

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+ 16 • GPU availability is constrained — Codesphere has stated they sometimes have more demand than capacity. If you can't get a GPU workspace, try again later or upgrade to paid

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+ 17 • The GPU is shared, not dedicated — expect variable performance

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+ 18 • Only your initial team gets the 3 free workspace allocation. Additional teams require paid plans

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+ 19  

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+ 20

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+ 21  

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+ 22 GPU Hardware & Specs

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+ 23  

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+ 24 FeatureDetail

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+ 25 Free GPU typeShared GPU (specific model not publicly disclosed)

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+ 26 Paid GPU optionsNVIDIA T4, A100 (available on-demand)

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+ 27 Free storage20 GB

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+ 28 Paid GPU add-on~$10/month per GPU with "off when unused" feature

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+ 29  

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+ 30 The free shared GPU is suitable for:

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+ 31 • Running smaller AI models and inference

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+ 32 • Stable Diffusion image generation

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+ 33 • Fine-tuning small models

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+ 34 • General GPU-accelerated development

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+ 35  

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+ 36 For heavy training workloads, you would need to upgrade to paid T4 or A100 instances.

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+ 37  

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+ 38

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+ 39  

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+ 40 Free Tier Limits

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+ 41  

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+ 42 FeatureFree TierPaid (Micro $5/mo)Paid (Boost $20/mo)

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+ 43 Workspaces3MoreMore

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+ 44 Storage20 GB1 GB (base)More

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+ 45 GPU1 shared GPUAdd-on availableAdd-on available

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+ 46 Team seats3 free+$10/seat/mo+$10/seat/mo

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+ 47 Auto-shutdown~60 min idleConfigurableConfigurable

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+ 48 Credit cardNot requiredRequiredRequired

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+ 49  

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+ 50

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+ 51  

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+ 52 Platform Features

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+ 53  

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+ 54 Full cloud IDE — not just notebooks. You get a VS Code-like editor, terminal, file explorer, and Git integration

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+ 55 One-click deployment — deploy your workspace as a live web service with a URL

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+ 56 Docker support — run any containerized workload

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+ 57 Collaboration — share workspaces with your team in real time

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+ 58 Managed PostgreSQL — available as an add-on service

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+ 59 Templates — pre-built templates for common AI workloads (Stable Diffusion, LLMs, etc.)

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+ 60  

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+ 61

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+ 62  

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+ 63 Additional Tips

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+ 64  

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+ 65 Not just for notebooks — the biggest differentiator vs. Google Colab or Kaggle is that Codesphere gives you a full dev environment. You can build and deploy full applications, not just run experiments

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+ 66 Auto-shutdown workaround — the 60-minute idle timeout applies to IDE activity specifically. A planned "Dev Deployment mode" was announced that would keep workspaces alive when users visit their dev domain, but check if this has shipped

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+ 67 GPU availability is hit-or-miss — if the free GPU slots are full, you'll need to wait or pay. Try signing up during off-peak hours (nights, weekends) for better luck

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+ 68 Good for hobbyists and prototyping — the free tier is best suited for hobbyist projects, learning ML, and quick prototyping. For serious training, use a dedicated GPU cloud (RunPod, Vast.ai, Lambda)

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+ 69 Combine with other free tiers — use Codesphere for development and deployment, and a free GPU provider (Colab, Kaggle, Lightning AI) for heavy compute tasks

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+ 70 $10/month GPU add-on is competitive — if you like the platform, the paid GPU option with "off when unused" billing is very affordable for intermittent workloads

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+ 71  

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+ 72

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+ 73  

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+ 74 Sources:

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+ 75 Codesphere Homepage

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+ 77 Codesphere Pricing

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