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Gemini 3.1 Pro vs DeepSeek V3.1

Detailed technical comparison between Gemini 3.1 Pro (Google) and DeepSeek V3.1 (DeepSeek). Review live API token pricing, context window capabilities, time-to-first-token latency, and verified benchmark scores side-by-side.

โšก Executive Summary & Verdict

Comparison Snapshot

Gemini 3.1 Pro: 6 WinsvsDeepSeek V3.1: 0 Wins
Context Leader

Gemini 3.1 Pro

2,000,000 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

DeepSeek V3.1

$0.25 / MTok
Googleactive

Gemini 3.1 Pro

Google's premiere multi-modal model featuring a massive 2 million token context window. Engineered for deep code analysis, video indexing, and long-context reasoning.

View Gemini 3.1 Pro Full Specs โ†’
DeepSeekactive

DeepSeek V3.1

DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...

View DeepSeek V3.1 Full Specs โ†’

Technical Specifications

๐Ÿ† = Superior Spec
SpecificationGemini 3.1 ProDeepSeek V3.1
ProviderGoogleDeepSeek
Context Window2,000,000 tokens๐Ÿ†163,840 tokens
Agent Suitability93/100 (est.)Not yet benchmarked
Time to First Token (TTFT)420 ms (est.)No public TTFT data
Deployment Modelmanaged apiself hostable
Production StabilityStable GA (est.)Stable GA (est.)
API AvailableYesYes
Released Date2026-04-202025-08-21

API Pricing Comparison

Input Price per Million Tokens

Gemini 3.1 Pro

$2.00

DeepSeek V3.1

$0.25

Output Price per Million Tokens

Gemini 3.1 Pro

$12.00

DeepSeek V3.1

$0.95

๐Ÿ’ก Cost Ratio: DeepSeek V3.1 is 8.0x cheaper per input token than Gemini 3.1 Pro.

Want to test both models live?

Run side-by-side prompt benchmarks in our dynamic multi-model Sandbox. Compare execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Standardized Scores (0โ€“100%)

Scores show verified raw accuracy percentages across standardized AI evaluation suites. Higher bars indicate superior performance in that domain.

MMLUGeneral knowledge & multi-task understanding
92.8%vs80.0%+12.8% Gemini 3.1 Pro
Gemini 3.1 Pro ๐Ÿ†
DeepSeek V3.1
HumanEvalPython coding & logic synthesis
94.6%vs78.2%+16.4% Gemini 3.1 Pro
Gemini 3.1 Pro ๐Ÿ†
DeepSeek V3.1
MATHComplex mathematical problem solving
88.0%vs55.4%+32.6% Gemini 3.1 Pro
Gemini 3.1 Pro ๐Ÿ†
DeepSeek V3.1
GPQAGraduate-level expert reasoning
81.3%vs40.8%+40.5% Gemini 3.1 Pro
Gemini 3.1 Pro ๐Ÿ†
DeepSeek V3.1
HellaSwagCommonsense reasoning and inference
98.4%vs83.0%+15.4% Gemini 3.1 Pro
Gemini 3.1 Pro ๐Ÿ†
DeepSeek V3.1
MT-BenchMulti-turn conversation flow quality
9.5%vs8.6%+0.9% Gemini 3.1 Pro
Gemini 3.1 Pro ๐Ÿ†
DeepSeek V3.1

Gemini 3.1 Pro Quirks & Gotchas

  • โ–ธBest model for massive context โ€” 2M token window is class-leading
  • โ–ธTool calling requires explicit schema definition in Google AI Studio

DeepSeek V3.1 Quirks & Gotchas

No developer gotchas reported.

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