Gemini 3.8 Live vs o1 Pro
Pricing verdict: Gemini 3.8 Live vs o1 Pro: Gemini 3.8 Live is cheaper for input-heavy usage ($0.75/M vs $150.00/M input tokens), while o1 Pro is better for long-context tasks (200,000 tokens).
Direct answer: choose Gemini 3.8 Live for lower token spend and choose o1 Pro when your workload needs longer context.
Compare API pricing, input and output token costs, context windows, and monthly estimates on one page so you can pick the right model fast.
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Gemini 3.8 Live
o1 Pro
Cost Differences
o1 Pro costs more than Gemini 3.8 Live
Quick Recommendation
Winner for direct API pricing: Gemini 3.8 Live. At the default workload, Gemini 3.8 Live saves about $1,341.00/month ($16,315.50/year) versus o1 Pro.
Feature Comparison
| Feature | Gemini 3.8 Live | o1 Pro |
|---|---|---|
| Provider | OpenAI | |
| Input Price | $0.75/1M tokens | $150.00/1M tokens |
| Output Price | $4.50/1M tokens | $600.00/1M tokens |
| Context Window | 131,072 tokens | 200,000 tokens |
| Max Output | 65,536 tokens | 100,000 tokens |
| Category | balanced | flagship |
| Capabilities | textvisionaudiovideoreasoningstreaming | textvisioncodereasoning |
| Release Date | 9/15/2026 | 12/17/2024 |
Gemini 3.8 Live vs o1 Pro: Which Should You Choose?
Choosing between Gemini 3.8 Live and o1 Pro depends on your priorities: cost efficiency, context length, or raw capability. Gemini 3.8 Live is the more affordable option at $0.75/1M input tokens — 100% cheaper than o1 Pro. Meanwhile, o1 Pro offers a significantly larger context window at 200,000 tokens vs 131,072 for Gemini 3.8 Live.
These models come from different providers — Google and OpenAI — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Google, switching to OpenAIinvolves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: Gemini 3.8 Live is a balanced model while o1 Pro is flagship. This means they're optimized for different workloads. o1 Pro targets more demanding workloads, while Gemini 3.8 Live provides a cost-effective option for everyday tasks.
Output costs matter too. Gemini 3.8 Live charges $4.50/1M output tokens vs $600.00 for o1 Pro. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Gemini 3.8 Live has the edge here at $4.50/1M output tokens.
Multimodal capabilities: Both models support vision (image understanding), so you can send images alongside text prompts with either option.
Best Use Cases
Choose Gemini 3.8 Live when:
- • Budget is a primary concern
- • You need more capabilities (audio, video, streaming)
- • You're already using Google's API ecosystem
Choose o1 Pro when:
- • You need a larger context window (200,000 tokens)
- • You need longer outputs (up to 100,000 tokens)
- • You're already using OpenAI's API ecosystem
Pros and Caveats at a Glance
Gemini 3.8 Live
- • Input pricing: $0.75/M tokens
- • Output pricing: $4.50/M tokens
- • Context window: 131,072 tokens
- • Max output: 65,536 tokens
Watch out for
- • Smaller context window than o1 Pro
o1 Pro
- • Input pricing: $150.00/M tokens
- • Output pricing: $600.00/M tokens
- • Context window: 200,000 tokens
- • Max output: 100,000 tokens
Watch out for
- • Higher input cost than Gemini 3.8 Live
- • Higher output cost than Gemini 3.8 Live
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Gemini 3.8 Live (Google)
o1 Pro (OpenAI)
Start using Gemini 3.8 Live today
Sign Up for Google →Start using o1 Pro today
Sign Up for OpenAI →Frequently Asked Questions
Which is cheaper, Gemini 3.8 Live or o1 Pro?▼
What is the context window difference between Gemini 3.8 Live and o1 Pro?▼
Which model is better for AI Chatbot?▼
Which model has better overall pricing for heavy usage?▼
Where can I compare Google and OpenAI API pricing beyond this model matchup?▼
Related Comparisons
Related Articles
Learn when to pick each model, then compare live pricing scenarios.