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Gemini 2.5 Pro vs DeepSeek V3.1

Detailed technical comparison between Gemini 2.5 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.

⚑ Executive Summary & Verdict

Comparison Snapshot

Gemini 2.5 Pro: 6 WinsvsDeepSeek V3.1: 0 Wins
Context Leader

Gemini 2.5 Pro

1,048,576 tokens
Agentic Tool-Calling

Tie

Equal Capability
Lowest Latency (TTFT)

Tie

Equal Speed
Input Price Leader

DeepSeek V3.1

$0.25 / MTok
Googleactive

Gemini 2.5 Pro

Gemini 2.5 Pro is Google’s state-of-the-art AI model designed for advanced reasoning, coding, mathematics, and scientific tasks. It employs β€œthinking” capabilities, enabling it to reason through responses with enhanced accuracy...

View Gemini 2.5 Pro Full Specs β†’
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 β†’

Technical Specifications

πŸ† = Superior Spec
SpecificationGemini 2.5 ProDeepSeek V3.1
ProviderGoogleDeepSeek
Context Window1,048,576 tokensπŸ†163,840 tokens
Agent Suitability90/100 (est.)Not yet benchmarked
Time to First Token (TTFT)450 ms (est.)No public TTFT data
Deployment Modelmanaged apiself hostable
Production StabilityStable GA (est.)Stable GA (est.)
API AvailableYesYes
Released Date2025-06-172025-08-21

API Pricing Comparison

Input Price per Million Tokens

Gemini 2.5 Pro

$1.25

DeepSeek V3.1

$0.25

Output Price per Million Tokens

Gemini 2.5 Pro

$10.00

DeepSeek V3.1

$0.95

πŸ’‘ Cost Ratio: DeepSeek V3.1 is 5.0x cheaper per input token than Gemini 2.5 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 (0–100%)

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

MMLUGeneral knowledge & multi-task understanding
89.9%vs80.0%+9.9% Gemini 2.5 Pro
Gemini 2.5 Pro πŸ†
DeepSeek V3.1
HumanEvalPython coding & logic synthesis
91.5%vs78.2%+13.3% Gemini 2.5 Pro
Gemini 2.5 Pro πŸ†
DeepSeek V3.1
MATHComplex mathematical problem solving
82.0%vs55.4%+26.6% Gemini 2.5 Pro
Gemini 2.5 Pro πŸ†
DeepSeek V3.1
GPQAGraduate-level expert reasoning
72.0%vs40.8%+31.2% Gemini 2.5 Pro
Gemini 2.5 Pro πŸ†
DeepSeek V3.1
HellaSwagCommonsense reasoning and inference
96.2%vs83.0%+13.2% Gemini 2.5 Pro
Gemini 2.5 Pro πŸ†
DeepSeek V3.1
MT-BenchMulti-turn conversation flow quality
9.3%vs8.6%+0.7% Gemini 2.5 Pro
Gemini 2.5 Pro πŸ†
DeepSeek V3.1

Gemini 2.5 Pro Quirks & Gotchas

  • β–ΈLegacy model β€” migrate to Gemini 3.1 Pro for better tool calling and lower latency

DeepSeek V3.1 Quirks & Gotchas

No developer gotchas reported.

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