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DeepSeek R1 vs Gemini 3.1 Flash

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 DeepSeek R1 and Gemini 3.1 Flash.

DeepSeek

DeepSeek R1

A premier reasoning model employing large-scale reinforcement learning. Displays specialized math, coding, and logical validation capabilities comparable to OpenAI's o1.

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Google

Gemini 3.1 Flash

Gemini 3.1 Flash is Google's high-speed, cost-efficient multimodal model in the 3.1 generation, purpose-built for high-volume content synthesis, classification, and intelligent routing at scale. Featuring a 1-million-token context window, it can process large batches of documents, customer data, or multimedia content in a single inference pass, dramatically reducing pipeline complexity. At just $0.25/MTok for input, it is one of the most affordable routes to Google-caliber multimodal AI, making it an ideal backbone for production pipelines, data enrichment workflows, and high-frequency API integrations.

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Technical Specifications

SpecificationDeepSeek R1Gemini 3.1 Flash
ProviderDeepSeekGoogle
Context Window163,840 tokens1,000,000 tokens
Agent Suitability78/10086/100
Time to First Token (TTFT)1800 ms150 ms
Deployment Modelmanaged apimanaged api
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-01-202026-04-20

API Pricing Comparison

Input Price per Million Tokens

DeepSeek R1

$0.70

Gemini 3.1 Flash

$0.25

Output Price per Million Tokens

DeepSeek R1

$2.50

Gemini 3.1 Flash

$1.50

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
9080.0%vs8680.0%
DeepSeek R1
Gemini 3.1 Flash
HumanEvalPython coding & logic synthesis
9280.0%vs8850.0%
DeepSeek R1
Gemini 3.1 Flash
MATHComplex mathematical problem solving
9310.0%vs7820.0%
DeepSeek R1
Gemini 3.1 Flash
GPQAGraduate-level expert reasoning
6210.0%vs6050.0%
DeepSeek R1
Gemini 3.1 Flash
HellaSwagCommonsense reasoning and inference
9050.0%vs9520.0%
DeepSeek R1
Gemini 3.1 Flash
MT-BenchMulti-turn conversation flow quality
935.0%vs900.0%
DeepSeek R1
Gemini 3.1 Flash

DeepSeek R1 Quirks & Gotchas

  • โ–ธReasoning model โ€” not designed for high-frequency tool calling
  • โ–ธPair with a smaller model (V4 Flash) for routing and use R1 for complex reasoning only

Gemini 3.1 Flash Quirks & Gotchas

  • โ–ธMost cost-effective Google model โ€” ideal for high-volume pipelines
  • โ–ธContext caching available via Vertex AI for repeated document processing