IBM watsonx.ai Lite Plan (Free Tier)
Source: https://www.ibm.com/products/watsonx-ai/pricing
Description
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+ 1 Always-free tier for IBM's enterprise AI platform providing 20 Capacity Unit Hours (CUH) per month for ML workloads and 300,000 tokens per month for foundation model inference. No credit card charge -- identity verification only. Includes access to IBM Granite models, Meta Llama, Mistral, and other third-party foundation models. Best suited for experimentation, prototyping, and learning.
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+ 7 1. Go to dataplatform.cloud.ibm.com/registration/stepone?context=wx
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+ 8 2. Select an IBM Cloud region (Dallas or Frankfurt recommended for full foundation model access)
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+ 9 3. Log in with your IBMid or create a new IBM Cloud account (email, personal info, and credit card for identity verification)
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+ 10 4. If prompted, select your account and resource group
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+ 11 5. Click Continue and wait for activation to complete
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+ 12 6. Bookmark your watsonx.ai home page for future logins
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+ 13
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+ 14 Notes:
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+ 15 • One Lite plan instance per IBM Cloud account
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+ 16 • If you land on the IBM Cloud Dashboard instead, return to the signup page and click "Log in with existing account"
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+ 17 • No charges unless you manually upgrade to a paid plan
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+ 23 CUH is IBM's billing unit for all watsonx.ai Runtime activity except foundation model inference. CUH is consumed when you:
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+ 24
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+ 25 • Train AutoAI models
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+ 26 • Run or score deployed ML models
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+ 27 • Execute Decision Optimization jobs
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+ 28 • Tune models in the Tuning Studio (not available on Lite)
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+ 29
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+ 30 CUH consumption depends on the training tool, hardware spec, and runtime environment. Compute time is measured to the millisecond with a one-minute minimum per operation. A deployment that receives no scoring requests for a set duration goes idle and stops consuming CUH.
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+ 32 Example: A Decision Optimization batch job running 15 minutes on 2 nodes (2 vCPU, 8 GB RAM, CUH rate 30) consumes 0.25 x 2 x 30 = 15 CUH.
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+ 34 Foundation model inference uses a separate metric: Resource Units (RU), where 1 RU = 1,000 tokens.
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+ 40 ResourceLite Plan Limit
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+ 41 CUH20 per month
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+ 42 Foundation model tokens300,000 per month
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+ 43 Inference request rate2 requests/second
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+ 44 Deployment idle timeout1 day
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+ 45 Parallel batch jobs (Decision Opt.)2 per deployment
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+ 46 Deployment job retention100 jobs per space
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+ 47 Document text classification100 pages/month
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+ 48 Cloud Object Storage25 GB/month
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+ 49 Studio instances1 per account
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+ 55 The Lite plan provides access to the same foundation models as paid plans, with capacity limits. Model availability varies by data center.
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+ 58
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+ 59 ModelParametersUse Cases
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+ 60 granite-4-h-smallSmallGeneral purpose
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+ 61 granite-3-3-8b-instruct8BInstruction-following, Q&A, summarization
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+ 62 granite-3-8b-base8BBase model for fine-tuning
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+ 63 granite-8b-code-instruct8BCode generation and explanation
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+ 64 granite-guardian-3-8b8BSafety filtering, HAP/PII detection
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+ 65 granite-ttm variantsVariousTime-series forecasting
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+ 68
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+ 69 ModelParametersUse Cases
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+ 70 llama-4-maverick-17b-128e-instruct-fp817B (128 experts)Multimodal, latest generation
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+ 71 llama-3-3-70b-instruct70BLarge-scale instruction-following
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+ 72 llama-3-2-11b-vision-instruct11BMultimodal vision + text
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+ 73 llama-guard-3-11b-vision11BSafety classification
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+ 74
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+ 76
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+ 77 ModelNotes
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+ 78 mistral-large-2512256K context window
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+ 79 mistral-medium-2505Medium capability tier
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+ 80 mistral-small-3-1-24b-instruct24B, efficient small model
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+ 81
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+ 83
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+ 84 ModelProviderNotes
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+ 85 gpt-oss-120bOpenAIOpen-source variant, 120B parameters
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+ 86 mt0-xxl-13bBigScienceMultilingual translation
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+ 87 allam-1-13b-instructSDAIAArabic language model
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+ 93 A token is roughly 4 characters or 0.75 words. With 300,000 tokens per month (input + output combined):
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+ 94
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+ 95 Use CaseApprox. Capacity
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+ 96 Short Q&A prompts (~200 tokens each)~1,500 interactions
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+ 97 Summarizing documents (~1,000 tokens each)~300 documents
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+ 98 Code generation (~500 tokens each)~600 code snippets
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+ 99 RAG-based chatbot (~800 tokens per exchange)~375 conversations
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+ 100 Small classification pipeline (~100 tokens each)~3,000 classifications
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+ 101
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+ 102 This is enough for prototyping, academic projects, demos, and light personal use. Not suitable for production workloads.
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+ 108 The Lite plan does not support:
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+ 109
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+ 110 • Foundation model tuning (prompt tuning, fine-tuning)
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+ 111 • Custom foundation model deployments
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+ 112 • GPU runtime environments for notebooks
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+ 113 • Large runtime environments (8+ vCPU)
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+ 114 • Project export
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+ 115 • Encryption with your own key (BYOK)
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+ 116 • Quota increases beyond Lite limits
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+ 117
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+ 118 Collaborators in your projects must each have their own Lite plan.
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+ 119
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+ 123
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+ 124 • Use smaller models (granite-4-h-small, mistral-small) to consume fewer tokens per interaction
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+ 125 • Monitor usage in the IBM Cloud dashboard -- track CUH and RU consumption to avoid hitting limits mid-month
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+ 126 • Use the Prompt Lab for interactive testing before building pipelines
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+ 127 • Select Dallas or Frankfurt as your region for the widest model availability
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+ 128 • Idle deployments time out after 1 day -- redeploy as needed rather than keeping deployments running
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+ 129 • Combine with the free demo at ibm.com/products/watsonx/get-started for an additional 20,000 tokens over 30 days (requires only IBM/Google/LinkedIn login)
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• Use the Python SDK (ibm-watsonx-ai) for programmatic access and automation
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+ 131 • Set up billing alerts if you ever upgrade, as there are no spending caps by default
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+ 137 PlanPriceNotes
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+ 138 LiteFree20 CUH + 300K tokens/month
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+ 139 EssentialsPay-as-you-go (from $0/month)No standing charge, pay only for usage
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+ 140 Standard~$1,050/month baseEnterprise support, higher limits
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+ 141 ProfessionalCustom pricingFlat-rate, full capacity
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+ 142
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+ 144
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+ 145 Sources:
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+ 146 • IBM watsonx.ai Pricing
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+ 147 • watsonx.ai Runtime Service Plans
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+ 148 • Supported Foundation Models
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+ 149 • Signing Up for IBM watsonx
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+ 150 • Billing Details for ML Assets
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+ 151 • Billing Details for GenAI Assets
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+ 152 • IBM watsonx.ai Foundation Models
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+ 153 • Try IBM watsonx.ai for Free
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