โ† Back to Model Hub/SIDE-BY-SIDE REVIEW
SHARE THIS:

Gemini 2.0 Flash vs R1

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 R1.

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.

View Full Specs
DeepSeek

R1

DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass....

View Full Specs

Technical Specifications

SpecificationGemini 2.0 FlashR1
ProviderGoogleDeepSeek
Context Window1,048,576 tokens163,840 tokens
Agent Suitability80/100N/A
Time to First Token (TTFT)180 msN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-02-052025-01-20

API Pricing Comparison

Input Price per Million Tokens

Gemini 2.0 Flash

$0.10

R1

$0.70

Output Price per Million Tokens

Gemini 2.0 Flash

$0.40

R1

$2.50

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/Avs9080.0%
Gemini 2.0 Flash
R1
HumanEvalPython coding & logic synthesis
N/Avs9280.0%
Gemini 2.0 Flash
R1
MATHComplex mathematical problem solving
N/Avs9310.0%
Gemini 2.0 Flash
R1
GPQAGraduate-level expert reasoning
N/Avs6210.0%
Gemini 2.0 Flash
R1
HellaSwagCommonsense reasoning and inference
N/Avs9050.0%
Gemini 2.0 Flash
R1
MT-BenchMulti-turn conversation flow quality
N/Avs935.0%
Gemini 2.0 Flash
R1

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

R1 Quirks & Gotchas

No developer gotchas reported.