--- title: "codex-auto-review - Model Details & Comparison" description: "codex-auto-review from OpenAI: capabilities, context limits, pricing, and side-by-side comparisons with alternative models." url: "https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/openai/codex-auto-review" markdown: "https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/openai/codex-auto-review.md" --- # codex-auto-review - Model Details & Comparison > codex-auto-review from OpenAI: capabilities, context limits, pricing, and side-by-side comparisons with alternative models. ## Important Links - [View MCP Gateway](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/resources/mcp-gateway.md) - [Features](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/#features) - [Enterprise](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/enterprise) - [Pricing](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/pricing.md) - [Docs](https://docs.getbifrost.ai) - [GitHub](https://github.com/maximhq/bifrost) - [Book a Demo](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/book-a-demo) ## About codex-auto-review codex-auto-review is a chat model from OpenAI, one of 91 chat models they offer. It is priced at $2.50 per 1M input tokens and $15.00 per 1M output tokens, ranking 2225 out of 2669 chat models by cost and cheaper than 17% of models in this category. codex-auto-review supports vision, function calling, reasoning, prompt caching, structured output. Its 1,050K-token context window is in the top 3% among chat models. ## Specifications - **OpenAI Provider.** - **Chat Mode.** - **1,050,000 Max Input Tokens.** - **128,000 Max Output Tokens.** - **128,000 Max Tokens.** - **$2.50 / 1M tokens Input Price.** - **$15.00 / 1M tokens Output Price.** ## Capabilities codex-auto-review supports: Function Calling, Vision, Reasoning, Prompt Caching, Parallel Function Calling, System Messages, Response Schema, Tool Choice, PDF Input. ## codex-auto-review Pricing Overview At $2.50 per 1M input tokens and $15.00 per 1M output tokens, codex-auto-review ranks 2225 out of 2669 chat models by input cost. It is more expensive compared to the median of $0.50 for chat models, and is cheaper than 17% of models in this category. codex-auto-review is one of 91 OpenAI chat models, with support for vision, function calling, reasoning, prompt caching, structured output. its 1,050K-token context window places it in the top 3% of chat models. ## Models to Compare Alternatives to codex-auto-review with comparable capabilities. | Model | Provider | Input $/1M | Output $/1M | | --- | --- | --- | --- | | amazon.nova-2-pro-preview-20251202-v1:0 | AWS Bedrock | $2.19 | $17.50 | | apac.amazon.nova-2-pro-preview-20251202-v1:0 | AWS Bedrock | $2.19 | $17.50 | | eu.amazon.nova-2-pro-preview-20251202-v1:0 | AWS Bedrock | $2.19 | $17.50 | | us.amazon.nova-2-pro-preview-20251202-v1:0 | AWS Bedrock | $2.19 | $17.50 | | anthropic.claude-3-7-sonnet-20250219-v1:0 | AWS Bedrock | $3.00 | $15.00 | - [Compare amazon.nova-2-pro-preview-20251202-v1:0](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/bedrock/amazon.nova-2-pro-preview-20251202-v1-0.md) - [Compare apac.amazon.nova-2-pro-preview-20251202-v1:0](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/bedrock/apac.amazon.nova-2-pro-preview-20251202-v1-0.md) - [Compare eu.amazon.nova-2-pro-preview-20251202-v1:0](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/bedrock/eu.amazon.nova-2-pro-preview-20251202-v1-0.md) - [Compare us.amazon.nova-2-pro-preview-20251202-v1:0](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/bedrock/us.amazon.nova-2-pro-preview-20251202-v1-0.md) - [Compare anthropic.claude-3-7-sonnet-20250219-v1:0](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/bedrock/anthropic.claude-3-7-sonnet-20250219-v1-0.md) ## Related Resources - [Calculate codex-auto-review costs](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/openai/model/codex-auto-review.md) - [Check OpenAI status](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/provider-status/openai.md) - [All OpenAI pricing](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/openai.md) ## FAQ ### Is codex-auto-review cheaper than amazon.nova-2-pro-preview-20251202-v1:0? No. codex-auto-review costs $2.50 per 1M input tokens while amazon.nova-2-pro-preview-20251202-v1:0 costs $2.19 per 1M input tokens, making amazon.nova-2-pro-preview-20251202-v1:0 12% more affordable for input. However, codex-auto-review may offer different capabilities or performance characteristics that justify the price difference. ### How does codex-auto-review pricing compare to the average chat model? codex-auto-review input pricing is $2.50 per 1M tokens, which is 400% above the median of $0.50 for chat models. It ranks 2225 out of 2669 chat models by input cost, making it cheaper than 17% of models in this category. For output, it costs $15.00 per 1M tokens compared to the median of $1.44. ### What makes codex-auto-review different from other OpenAI models? Among OpenAI's 91 chat models, codex-auto-review ranks 64 by input cost. ### What are the best alternatives to codex-auto-review? The most comparable chat models to codex-auto-review are: amazon.nova-2-pro-preview-20251202-v1:0 from AWS Bedrock ($2.19/1M input tokens); apac.amazon.nova-2-pro-preview-20251202-v1:0 from AWS Bedrock ($2.19/1M input tokens); eu.amazon.nova-2-pro-preview-20251202-v1:0 from AWS Bedrock ($2.19/1M input tokens); us.amazon.nova-2-pro-preview-20251202-v1:0 from AWS Bedrock ($2.19/1M input tokens). These alternatives were selected based on similar capabilities, pricing, and provider diversity. You can compare any of these models in detail using the Bifrost Model Library. ### How large is codex-auto-review's context window? codex-auto-review supports up to 1,050,000 input tokens, placing it in the top 3% of chat models by context window size (rank 75 of 2653). This makes it suitable for processing long documents, extensive code repositories, or maintaining detailed conversation histories. ### How do I check if OpenAI is down? You can monitor OpenAI service health in real time on the Bifrost OpenAI Status page. It tracks current component status, active incidents, and historical reliability data pulled from the official status page every 60 seconds. ### How do I calculate codex-auto-review costs? codex-auto-review is priced based on input and output tokens. Use the interactive calculator at the top of this page to estimate costs for your specific workload. Enter your expected input and output tokens volume and the calculator will show the total cost breakdown. For reference, processing 1M input tokens costs $2.50 and generating 1M output tokens costs $15.00. ## Related Resources - [OpenAI models](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/provider/openai.md) - [Model library](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library.md) - [LLM cost calculator](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator.md) - [Docs: Bifrost docs](https://docs.getbifrost.ai) - [GitHub: maximhq/bifrost](https://github.com/maximhq/bifrost) - [Pricing: Bifrost pricing](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/pricing.md) - [Enterprise: Bifrost enterprise](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/enterprise) - [Book a Demo: Bifrost demo](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/book-a-demo) - [Resources: Bifrost resources](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/resources.md) --- *This is a markdown version of [https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/openai/codex-auto-review](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/model-library/compare/openai/codex-auto-review) for AI/LLM consumption.*