AI Tool Comparison
Comparing as AI Code Generation & AutocompleteJetBrains AI Assistant vs Google Gemini API
Compare features, pricing, pros & cons, and user ratings to decide which AI tool is best for your needs.
JetBrains AI Assistant
VS
Google Gemini API
Verdict by Category
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Detailed Comparison
Feature
JetBrains AI Assistant
Google Gemini API
Pricing
FreemiumJetBrains AI offers four tiers. AI Free is $0/month with 3 AI credits every 30 days, unlimited code completion via JetBrains' Mellum model, and local model support via Ollama or LM Studio, but excludes frontier models and Junie for sustained agentic work. AI Pro is $10/month (Individual) or $20/month (Business), with 10 AI credits per month. AI Ultimate is $30/month (Individual) or $60/month (Business), with 35 AI credits per month, including a $5 bonus over the plan price. AI Enterprise is custom-priced at roughly $60/user/month billed annually, adding organization-wide credit pooling and enterprise controls. Each AI Credit equals $1 USD, and unused top-up credits (purchased separately at $1 each) remain valid for 12 months, while unused monthly plan credits do not roll over. A 30-day AI Pro trial is available for new users. AI Pro is also bundled into JetBrains' All Products Pack and dotUltimate subscriptions.
FreemiumThe Gemini API uses a three-tier structure. Free is for developers and small projects, offering limited access to select models with free input and output tokens, Google AI Studio access, and no billing account required, though content is used to improve Google's products. Paid unlocks higher rate limits for production, context caching, the Batch API (roughly 50% cost reduction), access to Google's most advanced models, and a guarantee that content is not used to improve Google's products. Pricing is billed per million tokens and varies by model: for example, Gemini 3.1 Pro Preview costs $2.00 input and $12.00 output per million tokens for prompts under 200K tokens, while cost-efficient options like Gemini 3.5 Flash-Lite start as low as $0.30 input and $2.50 output per million tokens, with additional Flex and Priority billing modes available for different latency and cost tradeoffs. Enterprise is for large-scale deployments through the Gemini Enterprise Agent Platform, adding dedicated support channels, advanced security and compliance certifications (HIPAA, SOC 2, FedRAMP), provisioned throughput, volume-based discounts, and MLOps tooling, available by contacting Google's sales team.
Categories
AI Coding Assistants
AI Developer APIs & PlatformsAI Coding Assistants
Summary
AI coding assistance built natively into every JetBrains IDE
Build with Google's multimodal Gemini models via API and AI Studio
JetBrains AI Assistant Pros & Cons
Pros
- Deep semantic project understanding via IntelliJ's existing static-analysis engine, not just open-file context
- Junie autonomous agent handles multi-file planning, implementation, and self-correction, including a dedicated Debug mode
- Works across a single subscription spanning 20+ JetBrains IDEs
- Supports local models via Ollama and LM Studio at zero credit cost
- Strong enterprise trust features including zero-data-retention policies and .aiignore support
Cons
- Locked into the JetBrains IDE ecosystem, so it offers no value for developers using VS Code or other editors
- Credit-based quota system can be confusing, and heavy Junie or Claude Agent use can exhaust monthly credits well before the billing period ends
- AI Pro's 10 monthly credits are reportedly consumed within about a week under heavy agentic use, pushing users toward costly top-ups ($1 per credit)
- Best suited to JVM languages (Java, Kotlin); completion quality is reportedly less consistent for other languages
- AI Free tier excludes frontier models and the Junie agent, limiting it mostly to a demo of completion features
Google Gemini API Pros & Cons
Pros
- Genuinely native multimodal models covering text, image, video, and audio in one API
- Google AI Studio offers a real, usable free prototyping environment with no billing account required
- Google Search and Google Maps grounding help reduce hallucinations with live information
- Batch API and Flex pricing modes offer substantial cost savings for non-latency-sensitive workloads
- Clear upgrade path from free prototyping to enterprise-grade deployment via the Gemini Enterprise Agent Platform
Cons
- Pricing structure is complex, with per-model, per-mode (Standard/Batch/Flex/Priority) rates that require careful reading to estimate real costs
- Free tier usage is used to improve Google's products, so privacy-sensitive projects need to upgrade to the Paid tier for that guarantee to apply
- Frequent model churn (previews, deprecations, shutdown dates) means integrations need occasional migration work to stay current
- Full enterprise-grade features like fine-tuning, VPC Service Controls, and CMEK live on the separate Gemini Enterprise Agent Platform, not the Developer API itself
- Advanced capabilities like Computer Use and some agent tooling remain in preview with more restrictive rate limits