The 2025 AI Pricing War: Gemini vs. ChatGPT API Cost Comparison
For developers and CTOs, the AI landscape has shifted from a "capability war" to a "price war." With OpenAI’s release of the GPT-5 series and o3 reasoning models, and Google’s aggressive pricing on Gemini 2.5 and 3, the choice of which API to use is no longer just about benchmarks—it’s about unit economics.
We have analyzed the entire catalog of models from both providers. Below is the definitive guide to API pricing for every model available in late 2025.
1. The "Deep Reasoning" Tier
Best for: Complex coding, scientific research, legal analysis, and multi-step logic.
This is the most expensive tier. These models use "thinking tokens" (hidden chain-of-thought) to self-correct before answering.
| Model | Provider | Input Cost (per 1M) | Output Cost (per 1M) | The Verdict |
| o1-pro | OpenAI | $150.00 | $600.00 | The most expensive model on earth. Use only for "unsolvable" problems. |
| o1 | OpenAI | $15.00 | $60.00 | The standard for heavy reasoning. |
| o3-deep-research | OpenAI | $10.00 | $40.00 | Specialized for autonomous research agents. |
| Gemini 3 Pro | $2.00 | $12.00 | Best Value. Google is aggressively undercutting OpenAI here, offering reasoning capabilities for ~85% less than o1. | |
| o3-mini | OpenAI | $1.10 | $4.40 | A "lite" reasoning model. Good for coding, but expensive compared to standard minis. |
Key Insight: Google’s Gemini 3 Pro is the disruptor here. At $2.00 input, it brings "reasoning model" capabilities closer to standard flagship prices.
2. The "Flagship" Tier (General Purpose)
Best for: Production applications, chatbots, RAG, and general intelligence tasks.
This year, the prices for flagship models have converged. Both providers have settled on similar price points, making the differentiator speed and context window.
| Model | Provider | Input Cost (per 1M) | Output Cost (per 1M) | Context Window |
| GPT-5.2 | OpenAI | $1.75 | $14.00 | 400k |
| GPT-5.1 | OpenAI | $1.25 | $10.00 | 400k |
| Gemini 2.5 Pro | $1.25 | $10.00 | 2 Million | |
| GPT-4o (Legacy) | OpenAI | $2.50 | $10.00 | 128k |
Which one wins?
Tie: GPT-5.1 and Gemini 2.5 Pro cost exactly the same ($1.25/$10.00).
Winner: Gemini 2.5 Pro wins on utility because of its 2 Million token context window, allowing you to process video and massive codebases for the same price.
3. The "Efficiency" Tier (Budget Models)
Best for: High-volume tasks, summarization, simple classification, and data extraction.
If you are processing billions of tokens, this is where you live. Google is currently winning the "race to the bottom" on price.
| Model | Provider | Input Cost (per 1M) | Output Cost (per 1M) | Notes |
| Gemini 2.5 Flash-Lite | $0.10 | $0.40 | Cheapest Model. The new king of bulk processing. | |
| GPT-4o-mini | OpenAI | $0.15 | $0.60 | Still a solid, reliable choice for OpenAI users. |
| GPT-5-mini | OpenAI | $0.25 | $2.00 | Smarter than 4o-mini, but nearly double the price. |
| Gemini 2.5 Flash | $0.30 | $2.50 | A "hybrid" model: smarter than a mini, faster than a pro. |
4. Multimodal Pricing (Audio, Video, Images)
The days of "text-only" pricing are over. Here is how the costs break down for rich media.
Image Generation
Imagen 3 (Google): ~$0.03 per image.
DALL·E 3 (OpenAI): $0.040 (Standard) to $0.120 (HD) per image.
Gemini 2.5 Flash Image Input: ~$0.0011 per image (billed as tokens).
GPT-4o Image Input: ~$0.002 per image (billed as tokens).
Video Generation
Veo 3 Fast (Google): $0.15 per second.
Veo 3 Standard (Google): $0.40 per second.
Sora 2 (OpenAI): $0.10 - $0.50 per second (depending on resolution).
Audio Intelligence
Gemini 2.5 Flash Audio Input: $1.00 / 1M tokens (approx. 10 hours of audio).
GPT-4o Audio Input: $10.00 / 1M tokens.
Verdict: Gemini is 10x cheaper for audio processing. If you are building voice bots or transcribing meetings, OpenAI's audio rates are significantly higher.
5. The "Hidden" Feature: Context Caching
Both providers now offer Context Caching—a way to "save" large prompts (like a 50-page manual) so you don't pay to re-upload them for every user query.
| Feature | Google Gemini | OpenAI |
| Discount | ~75% off Input costs | ~90% off Input costs |
| Storage Fee | ~$4.50 / 1M tokens per hour | None (Ephemeral / Short-term) |
| Best For | Static Data: Long-term storage of documents accessed frequently over days. | Chat History: Immediate re-use of context in a conversation loop. |
6. The 2025 Strategy Guide: What Should You Buy?
Scenario A: The "Super-Smart" Chatbot
Use: Gemini 2.5 Pro or GPT-5.1.
Why: They are priced identically ($1.25/$10). Choose Gemini if you need long context (documents >100 pages), choose GPT-5.1 if you prefer OpenAI's tool-calling ecosystem.
Scenario B: The "Data Cruncher" (ETL / Summarization)
Use: Gemini 2.5 Flash-Lite.
Why: At $0.10 per million tokens, it is 33% cheaper than GPT-4o-mini. For a startup processing 1 billion tokens a month, this is a savings of $50 vs $150.
Scenario C: The "Complex Problem Solver"
Use: Gemini 3 Pro.
Why: It offers "reasoning" capabilities for $2.00, whereas OpenAI's o1 costs $15.00. Unless you are solving Ph.D. level physics, Gemini 3 Pro is the far more economical choice.
Scenario D: The Voice Assistant
Use: Gemini 2.5 Flash.
Why: OpenAI's audio input is $10/1M tokens. Gemini's is $1/1M tokens. The math is simple.