o1
OpenAI • text+image+file->text
Context Window200K
Knowledge CutoffDec 17, 2024
o1 vs Gemini 2.5 Pro
o1 for deliberate chain-of-thought on code and math, Gemini 2.5 Pro for long-document multimodal reasoning.
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Gemini 2.5 Pro
Google • text+image+file+audio+video->text
Context Window1.0M
Knowledge CutoffJun 17, 2025
Editorial Verdict
o1 is a reasoning specialist; Gemini 2.5 Pro is a versatile multimodal flagship.
o1 and Gemini 2.5 Pro are both flagship-capable models, but o1 is a reasoning specialist and Gemini 2.5 Pro is a general-purpose multimodal model. For hard math and science reasoning, o1 leads. For general-purpose tasks, long-context processing, and multimodal applications, Gemini 2.5 Pro wins. The choice depends on whether your hardest problems are reasoning-focused or general.
o1
- State-of-the-art on hard math, competitive programming, and science benchmarks
- Extended internal reasoning chain for multi-step problem solving
- Lower cost than Gemini 2.5 Pro for reasoning-heavy workloads
Best for: Hard math, science, and competitive programming reasoning tasks
Gemini 2.5 Pro
- 1M token context for processing massive documents and codebases
- Strong multimodal reasoning with native video and audio understanding
- Versatile general-purpose model — better at non-reasoning tasks than o1
Best for: Long-context multimodal applications and versatile general-purpose production use
Pricing sourced from OpenRouter — updates as their catalog changes.
Pricing Comparison
All values pull from OpenRouter and update as their catalog changes.
| Metric | o1 | Gemini 2.5 Pro | Winner |
|---|---|---|---|
| Input (per 1M tokens) | $15.00 | $1.25 | 🏆 Gemini 2.5 Pro |
| Output (per 1M tokens) | $60.00 | $10.00 | 🏆 Gemini 2.5 Pro |
| Request fee | N/A | N/A | N/A |
| Image fee | N/A | $0.000001 | 🏆 Gemini 2.5 Pro |
Cost Estimator
Estimate monthly billing using real OpenRouter prices.
o1 Total
$1,425Gemini 2.5 Pro Total
$193.75Estimated Monthly Savings: $1,231.25 with Gemini 2.5 Pro
Capability Signals
Scores are directional estimates from model metadata — not official benchmark results.
o1MMLU Signal (Reasoning)Gemini 2.5 Pro
87%
92%
o1HumanEval Signal (Coding)Gemini 2.5 Pro
76%
81%
o1Agentic Tooling SignalGemini 2.5 Pro
84%
89%
o1Multimodal SignalGemini 2.5 Pro
78%
89%
Capabilities Matrix
Feature highlights for architecture and production fit.
o1 Strengths
- Supports image inputs for multimodal analysis workflows.
- Strong tool-calling and structured response support.
- Large context window for long documents and codebases.
Gemini 2.5 Pro Strengths
- Supports image inputs for multimodal analysis workflows.
- Supports audio and speech scenarios with native modality support.
- Strong tool-calling and structured response support.
API Implementation
Quick start snippets for each provider style.
OpenAI (Python)
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="openai/o1",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Google (Python)
from google import genai client = genai.Client(api_key="YOUR_API_KEY") response = client.models.generate_content( model="google/gemini-2.5-pro", contents="Hello" ) print(response.text)
Choose o1 when...
- Your application includes visual reasoning and image understanding tasks.
- You process large documents or code repositories in a single prompt.
- You rely on function calling, tool chaining, and structured output contracts.
Choose Gemini 2.5 Pro when...
- You need low-latency voice and speech workflows with Gemini 2.5 Pro.
- Your application includes visual reasoning and image understanding tasks.
- You process large documents or code repositories in a single prompt.
Frequently Asked Questions
Practical checks before selecting a production model.
Which model is better for coding?
Coding preference depends on your stack and tool-calling needs. Compare the coding signal row, test with your repository tasks, and validate latency in your target region.
Which model is cheaper at scale?
Input and output token pricing can diverge by workload profile. Use the estimator with your monthly request count and token mix to get a realistic cost difference.
Are these official benchmark numbers?
Pricing is live from OpenRouter. Benchmark rows are ModelsAtlas metadata-based signals and should be treated as directional guidance, not official leaderboard scores.
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