Best AI API Models in 2026: Complete Pricing Comparison Across 8 Providers

We verified pricing for 33 API models from OpenAI, Anthropic, Google, xAI, DeepSeek, Mistral, Cohere, and Meta. Here is every price, context window, and feature — in one place.

If you are building an application powered by AI in 2026, your most important decision is which model to call — and how much it will cost at scale.

The API pricing landscape has changed dramatically in the past year. DeepSeek V4 Flash now costs $0.14 per million input tokens. Claude Opus 4.7 costs $5. GPT-5.5 costs $5. The gap between the cheapest and most expensive frontier models is now 35x to 100x, which means your model choice can be the difference between a profitable product and one that loses money on every request.

We verified every price in this guide against the official provider documentation as of April 2026. No estimates, no third-party aggregators — just the actual numbers from each provider's pricing page.

The Flagship Models: Maximum Capability

These are the most powerful models each provider offers. Use them for complex reasoning, hard coding problems, research synthesis, and any task where output quality is the primary metric.

GPT-5.5 from OpenAI costs $5 per million input tokens and $30 per million output tokens. It has a 1 million token context window and 128,000 max output tokens. Batch processing cuts costs by 50 percent. OpenAI describes it as a new class of intelligence for coding and professional work. It supports vision, function calling, web search, and computer use.

Claude Opus 4.7 from Anthropic costs $5 per million input tokens and $25 per million output tokens. It also has a 1 million token context window and 128,000 max output tokens. Prompt caching can reduce input costs by 90 percent. It is the current benchmark leader for coding tasks and has the best vision capabilities of any Claude model.

DeepSeek V4 Pro costs $1.74 per million input tokens and $3.48 per million output tokens at regular pricing (currently 75 percent off until May 31, 2026, making it $0.435 and $0.87). It has a 1 million token context window and 384,000 max output tokens. At regular pricing, it is roughly one-seventh the cost of Claude Opus 4.7 for output tokens.

Gemini 3.1 Pro from Google costs $1.25 per million input tokens and $5 per million output tokens. It has the most competitive pricing among Western-lab flagship models and integrates deeply with Google Workspace.

Source: Pricing verified at developers.openai.com, platform.claude.com, api-docs.deepseek.com, and ai.google.dev, April 2026.

The Value Models: Best Price-to-Performance

These models handle most production workloads at a fraction of flagship pricing. For chatbots, content generation, summarisation, data extraction, and standard coding tasks, they are usually the right default.

Claude Sonnet 4.6 from Anthropic costs $3 per million input tokens and $15 per million output tokens. It includes the full 1 million token context window and supports all the same tools as Opus. For most production use cases, the quality difference between Sonnet and Opus is small enough that Sonnet is the better economic choice.

GPT-5.4 from OpenAI costs $2.50 per million input tokens and $15 per million output tokens. It is the previous generation flagship, now positioned as the balanced option. Context window is 1 million tokens.

DeepSeek V4 Flash costs $0.14 per million input tokens and $0.28 per million output tokens. This is currently the cheapest serious model on the market — roughly 100 times cheaper than GPT-5.5 on output tokens. Cache hits cost just $0.0028 per million tokens. It has a 1 million token context window and supports thinking mode. For cost-sensitive, high-volume workloads, V4 Flash is nearly impossible to beat on price.

Grok 4 Fast from xAI supports a 2 million token context window — the largest of any model in this comparison — and offers batch processing at 50 percent off.

The Budget Models: Maximum Efficiency

When you need to process millions of requests per day and quality requirements are moderate — classification, entity extraction, routing, content moderation — budget models keep costs negligible.

GPT-5.4 Mini from OpenAI costs $0.75 per million input tokens and $4.50 per million output tokens. It is OpenAI's strongest mini model, designed specifically for coding, computer use, and subagents.

GPT-5.4 Nano from OpenAI costs $0.20 per million input tokens and $1.25 per million output tokens. It is the cheapest OpenAI model and handles simple classification, short responses, and high-volume routing.

Claude Haiku 4.5 from Anthropic costs $1 per million input tokens and $5 per million output tokens. It is fast, handles classification and extraction well, and includes vision support.

For the absolute lowest cost, DeepSeek V4 Flash at $0.14 and $0.28 is technically cheaper than even the budget models from OpenAI and Anthropic, while offering a 1 million token context window. The trade-off is that DeepSeek's models are less consistently reliable for structured outputs and function calling compared to OpenAI and Anthropic.

Context Windows: Who Handles the Most?

Context window size determines how much text you can feed into a single request. For applications that work with large codebases, long documents, or extensive conversation histories, this is a critical specification.

Grok 4.20 from xAI leads with a 2 million token context window — roughly 1.5 million words in a single conversation. This was verified in their documentation at docs.x.ai.

Llama 4 Maverick and Scout from Meta both support 10 million token context windows. However, these are open-weight models without an official Meta-hosted API, so the actual context window depends on your serving provider. The 10 million figure comes from Meta's official documentation at llama.com.

GPT-5.5, Claude Opus 4.7, DeepSeek V4 Flash, and DeepSeek V4 Pro all support 1 million token context windows. This is enough for most production use cases, including loading entire codebases or processing book-length documents.

Gemini models from Google also support 1 million tokens. GPT-5.4 Mini supports 400,000 tokens. Most other models support 128,000 to 256,000 tokens.

How to Choose the Right Model

The decision framework is simpler than the pricing table makes it look. Start with three questions.

First: does output quality on hard tasks matter more than cost? If yes, use a flagship model. GPT-5.5 and Claude Opus 4.7 are the two strongest options. If you need the best coding model specifically, Claude Opus 4.7 has the edge based on CursorBench scores. If you need the broadest set of built-in tools (web search, computer use, code interpreter), GPT-5.5 is the most complete package.

Second: is your workload high-volume and cost-sensitive? If yes, DeepSeek V4 Flash is the default starting point. At $0.14 and $0.28, you can process enormous volumes for negligible cost. Test whether the quality is sufficient for your use case — if it is, the savings are transformational.

Third: do you need something in between? Claude Sonnet 4.6 at $3 and $15 and GPT-5.4 at $2.50 and $15 are both excellent balanced options. They handle production inference reliably at one-third to one-half the flagship price.

The best teams do not pick one model. They route dynamically: flagships for hard tasks, balanced models for standard work, budget models for simple operations. This hybrid approach can reduce blended API costs by 50 to 70 percent compared to using a single model for everything.

All prices in this guide are verified and tracked at aitoolsmentor.com/models, where you can sort by price, provider, context window, and features across all 33 models.