o3 Pro OpenAI
💰 Total Cost Calculation (from Plugin)
Output: $0.120000
Output: $0.120000
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Multimodal Input Details
Resolution: Medium
Tokens: 12,900
Cost: $0.000000
Detailed Cost Analysis (from Plugin)
For 50,000 input tokens and 1,500 output tokens:
- Input Cost: $1.258000 (rounded ~ $1.26)
- Output Cost: $0.120000
- Total Cost: $1.038340 (rounded ~ $1.04)
- Cost per 1K tokens: $0.016123 (rounded ~ $0.02)
- Tokens per dollar: 62,022 tokens
- Context Window: 200000 tokens
Speed & Performance Analysis
With a processing speed of 350 tokens per second and 300ms time to first token:
- Processing Time: 3 minutes, 9.70 seconds
- Latency: 300 milliseconds to first token
- Base Throughput: 350 tokens/second
- Effective Throughput: 340 tokens/second (temperature-adjusted)
Best Use Cases
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← Back to o3 Pro| Rank | AI Model & Provider | Total Cost | vs o3 Pro |
|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.005042 (rounded ~ $0.01) Best Value | ↓ 99.5% cheaper |
| 🥈 |
Gemini 3.1 Flash Lite
Google
|
$0.013729 (rounded ~ $0.01) | ↓ 98.7% cheaper |
| 🥉 |
Gemini 2.5 Flash
Google
|
$0.017525 (rounded ~ $0.02) | ↓ 98.3% cheaper |
| #4 |
Mistral Large 3
Mistral AI
|
$0.026209 (rounded ~ $0.03) | ↓ 97.5% cheaper |
| #5 |
Gemini 3.1 Flash
Google
|
$0.027459 (rounded ~ $0.03) | ↓ 97.4% cheaper |
| #6 |
Kimi K2.5
Moonshot AI
|
$0.032843 (rounded ~ $0.03) | ↓ 96.8% cheaper |
| #7 |
GPT-5.4 mini
OpenAI
|
$0.041188 (rounded ~ $0.04) | ↓ 96% cheaper |
| #8 |
Kimi K2.6
Moonshot AI
|
$0.050876 | ↓ 95.1% cheaper |
| #9 |
o4-mini Deep Research
OpenAI
|
$0.051917 (rounded ~ $0.05) | ↓ 95% cheaper |
| #10 |
Claude Haiku 4.5
Anthropic
|
$0.053417 (rounded ~ $0.05) | ↓ 94.9% cheaper |
| #11 |
o4-mini
OpenAI
|
$0.057109 (rounded ~ $0.06) | ↓ 94.5% cheaper |
| #12 |
Grok 4.3
xAI
|
$0.061146 (rounded ~ $0.06) | ↓ 94.1% cheaper |
| #13 |
Gemini 2.5 Pro
Google
|
$0.072396 (rounded ~ $0.07) | ↓ 93% cheaper |
| #14 |
Gemini 3.5 Flash
Google
|
$0.082376 (rounded ~ $0.08) | ↓ 92.1% cheaper |
| #15 |
GPT-5.3 Codex Spark
OpenAI
|
$0.101355 (rounded ~ $0.10) | ↓ 90.2% cheaper |
| #16 |
GPT-5.3 Instant
OpenAI
|
$0.101355 (rounded ~ $0.10) | ↓ 90.2% cheaper |
| #17 |
Gemini 3.1 Pro
Google
|
$0.109834 | ↓ 89.4% cheaper |
| #18 |
GPT-5.4
OpenAI
|
$0.137293 (rounded ~ $0.14) | ↓ 86.8% cheaper |
| #19 |
GPT-5.4 Thinking
OpenAI
|
$0.137293 (rounded ~ $0.14) | ↓ 86.8% cheaper |
| #20 |
Claude Sonnet 4.6
Anthropic
|
$0.160251 | ↓ 84.6% cheaper |
| #21 |
Claude Opus 4.7
Anthropic
|
$0.267085 (rounded ~ $0.27) | ↓ 74.3% cheaper |
| #22 |
Claude Opus 4.8
Anthropic
|
$0.267085 (rounded ~ $0.27) | ↓ 74.3% cheaper |
| #23 |
Claude Opus 4.6
Anthropic
|
$0.267085 (rounded ~ $0.27) | ↓ 74.3% cheaper |
| #24 |
GPT-5.5
OpenAI
|
$0.274585 (rounded ~ $0.27) | ↓ 73.6% cheaper |
| #25 |
GPT-5.5 Instant
OpenAI
|
$0.274585 (rounded ~ $0.27) | ↓ 73.6% cheaper |
| #26 |
o3 Deep Research
OpenAI
|
$0.519170 | ↓ 50% cheaper |
| #27 |
GPT-5.2 Pro
OpenAI
|
$1.216257 (rounded ~ $1.22) | ↑ 17.1% more |
| #28 |
GPT-5.2 Pro
OpenAI
|
$1.216257 (rounded ~ $1.22) | ↑ 17.1% more |
Mistral Small 3 Mistral AI
Gemini 3.1 Flash Lite Google
Gemini 2.5 Flash Google
Mistral Large 3 Mistral AI
Gemini 3.1 Flash Google
Kimi K2.5 Moonshot AI
GPT-5.4 mini OpenAI
Kimi K2.6 Moonshot AI
o4-mini Deep Research OpenAI
Claude Haiku 4.5 Anthropic
o4-mini OpenAI
Grok 4.3 xAI
Gemini 2.5 Pro Google
Gemini 3.5 Flash Google
GPT-5.3 Codex Spark OpenAI
GPT-5.3 Instant OpenAI
Gemini 3.1 Pro Google
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
Claude Sonnet 4.6 Anthropic
Claude Opus 4.7 Anthropic
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
GPT-5.5 OpenAI
GPT-5.5 Instant OpenAI
o3 Deep Research OpenAI
GPT-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
Leveraging Deep Reasoning for Complex Web Automation
Game studio AI leads are increasingly moving away from simple reactive agents toward systems that can ‘think’ before they click. When building agentic browser automation that involves 50K-token inputs, the challenge is rarely about throughput—it is about the quality of the decision-making process in response to web-based stimuli.
o3 Pro is engineered specifically for this use case. Unlike standard LLMs that might attempt immediate execution upon identifying a UI element, o3 Pro utilizes its deep reasoning capabilities to analyze the broader context of the browser session. This is critical for tasks like automated gameplay testing or complex account management workflows where a single incorrect tool call can break the entire sequence.
By investing in a model that prioritizes reasoning, your engineering team can reduce the overhead of implementing complex error-handling logic in the application layer. The model’s ability to self-correct during the reasoning phase allows for more graceful recovery from page load errors or unexpected UI changes. For studios managing large-scale autonomous pipelines, this leads to higher success rates per session, effectively offsetting the higher computational intensity required for deep thinking.
Consider this model when your browser automation cannot afford the risk of shallow execution. If your agents are performing high-value, multi-step actions that interact with sensitive or complex web services, the reasoning depth provided by o3 Pro offers a level of assurance that standard, fast-turnaround models struggle to match.