AI Tool Comparison
Comparing as AI Code Generation & AutocompleteOpenAI Codex vs Groq
OpenAI Codex
VS
Groq
Verdict by Category
Detailed Comparison
Feature
OpenAI Codex
Groq
Pricing
FreemiumCodex has no standalone subscription; access is bundled into ChatGPT plans. Free ($0/month) includes limited trial access via a lighter Codex model with restricted daily limits. Go costs $8/month for light, local use only (no cloud task delegation). Plus costs $20/month and includes Codex on the web, CLI, IDE extension, and iOS, covering typical daily use. Pro splits into two tiers since April 9, 2026: Pro 5x at $100/month and Pro 20x at $200/month, offering 5x and 20x higher usage than Plus respectively. Business costs $20/user/month billed annually ($25/month billed monthly), with standard seats including Codex within usual plan limits; OpenAI stopped offering new pay-as-you-go Codex-only Business seats as of June 24, 2026, though existing seats continue working. Enterprise, Edu, and Gov plans use custom pricing. Since April 2, 2026, usage across Plus, Pro, and Business shifted from per-message limits to token-based credits (roughly $0.04 each), metered on a rolling 5-hour window plus a weekly cap; Enterprise, Edu, Health, and Gov plans moved to the same system on April 23, 2026. API-key usage bypasses ChatGPT plan credits entirely and bills directly at standard OpenAI API token rates. Real-world usage for active developers commonly runs $100 to $200 per month depending on model choice, parallel agents, and fast-mode usage.
FreemiumGroqCloud uses pay-as-you-go pricing per million tokens with no seat license or minimum spend. Rates range from roughly $0.05 input / $0.08 output for Llama 3.1 8B Instant up to about $1.00 input / $3.00 output for Kimi K2, with the flagship Llama 3.3 70B Versatile priced at $0.59 input / $0.79 output and GPT-OSS 120B at $0.15 input / $0.60 output. Whisper v3 Turbo transcription is priced at $0.04 per hour of audio. A free tier is available to all registered users with no credit card required, offering access to every model at 30 requests per minute. The Batch API and prompt caching each cut rates by roughly 50%, and can be combined for an effective rate of about 25% of on-demand pricing on eligible workloads. Enterprise pricing, including GroqAssured governance features and dedicated GroqMetal infrastructure, is available by contacting Groq's sales team.
Categories
AI Coding Assistants
AI Developer APIs & PlatformsAI Coding Assistants
Summary
OpenAI's autonomous coding agent for pull requests, refactors, and reviews
The fastest inference cloud for open-source LLMs, powered by custom LPU chips
OpenAI Codex Pros & Cons
Pros
- Bundled into existing ChatGPT plans, so many users already have some level of access at no extra cost
- Consistent agent experience across ChatGPT, IDE, CLI, and desktop, all tied to one account
- Parallel agents and built-in cloud sandboxes let teams tackle multiple engineering tasks simultaneously
- Skills system lets teams encode their own standards so Codex needs less supervision over time
- Backed by OpenAI's frontier coding models and adopted by engineering teams at companies like Duolingo, Ramp, and Cisco Meraki
Cons
- Token-based credit pricing (since April 2026) makes monthly costs harder to predict than flat per-seat pricing
- Heavy parallel or fast-mode usage can push real spend to $100 to $200 per developer per month even on mid-tier plans
- The Codex brand has been recycled and repositioned multiple times since 2021, which can create confusion about what current Codex actually is
- No standalone subscription; access is entirely tied to a ChatGPT plan rather than a dedicated developer product
Groq Pros & Cons
Pros
- Consistently ranks among the fastest LLM inference providers thanks to purpose-built LPU hardware
- OpenAI-compatible API makes migration from existing integrations fast
- Generous free tier with no credit card required and access to every hosted model
- Batch API and prompt caching can stack to roughly 25% of on-demand pricing
- Proven at scale with 3M+ developers and demanding real-time customers like McLaren F1
Cons
- Only hosts open-source models (Llama, Mixtral, Gemma, Qwen, DeepSeek distills), so there's no access to proprietary models like GPT or Claude through the platform
- The December 2025 NVIDIA licensing deal and departure of founder Jonathan Ross as CEO introduce some uncertainty about the platform's long-term technical direction
- No self-serve fine-tuning; customization requires contacting Groq's sales team or submitting an Enterprise request
- Free tier is limited by requests-per-minute (30 RPM) rather than a generous token allowance, which can bottleneck bursty workloads
- Full pricing isn't published for every capability, and Enterprise/GroqAssured governance features require a custom conversation