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Gemini 2.0 Flash vs o1

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Gemini 2.0 Flash and o1.

Google

Gemini 2.0 Flash

Gemini 2.0 Flash is Google's previous-generation fast, cost-efficient multimodal model, offering a compelling balance of speed, capability, and price. It supports text, image, and audio inputs with native multimodal understanding, making it well-suited for high-volume classification, real-time content moderation, and data extraction pipelines. Gemini 2.0 Flash introduced Google's context caching feature, significantly reducing costs for repeated document processing. While the 3.x series has since succeeded it, Gemini 2.0 Flash remains a popular cost-optimized choice for teams with established Vertex AI workflows.

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OpenAI

o1

The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason...

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Technical Specifications

SpecificationGemini 2.0 Flasho1
ProviderGoogleOpenAI
Context Window1,048,576 tokens200,000 tokens
Agent Suitability80/10088/100
Time to First Token (TTFT)180 ms2500 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-02-052024-12-17

API Pricing Comparison

Input Price per Million Tokens

Gemini 2.0 Flash

$0.10

o1

$15.00

Output Price per Million Tokens

Gemini 2.0 Flash

$0.40

o1

$60.00

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

MMLUGeneral knowledge & multi-task understanding
N/Avs9180.0%
Gemini 2.0 Flash
o1
HumanEvalPython coding & logic synthesis
N/Avs9450.0%
Gemini 2.0 Flash
o1
MATHComplex mathematical problem solving
N/Avs9480.0%
Gemini 2.0 Flash
o1
GPQAGraduate-level expert reasoning
N/Avs7830.0%
Gemini 2.0 Flash
o1
HellaSwagCommonsense reasoning and inference
N/Avs9200.0%
Gemini 2.0 Flash
o1
MT-BenchMulti-turn conversation flow quality
N/Avs940.0%
Gemini 2.0 Flash
o1

Gemini 2.0 Flash Quirks & Gotchas

  • โ–ธContext caching via Vertex AI โ€” up to 75% cost reduction for repeated prompts
  • โ–ธLegacy model โ€” migrate to Gemini 3.1 Flash for improved accuracy

o1 Quirks & Gotchas

  • โ–ธReasoning model โ€” high latency by design, not for real-time use
  • โ–ธBest for complex math/code reasoning where accuracy > speed
  • โ–ธUse o3-mini when you need reasoning with lower latency