💰 Unit Cost Winner DeepSeek V3 $0.14/1M in · $0.28/1M out
⚡ Latency & Speed Winner DeepSeek V3 410ms TTFT · 78 tok/s
💻 Coding (SWE) Winner Gemini 3.1 Pro 71.8% SWE-bench · 94.8% HumanEval
🧠 STEM Reasoning Winner Gemini 3.1 Pro 82.4% GPQA · 96.8% MATH-500

Which model is better: DeepSeek V3 or Gemini 3.1 Pro?

DeepSeek V3 is 88.8% cheaper for input tokens ($0.14 vs. $1.25 per 1M tokens) and $0.28 vs. $10.00 for output tokens (8.9x cost advantage). In terms of operational performance, DeepSeek V3 delivers lower response latency at 410ms TTFT (10ms faster than Gemini 3.1 Pro) with 78 vs. 98 tok/s throughput. Gemini 3.1 Pro leads coding evaluations at 71.8% SWE-bench Verified vs. 42.0% for DeepSeek V3 and 82.4% vs. 59.1% on GPQA Diamond.
Verified daily via automated API latency tests and official documentation.

Verified Performance & Unit Economics Delta (12 Dimensions)

Daily synchronized metrics across token pricing, prompt cache economics, latency, throughput, and 5 capability benchmarks.

Metric / Dimension DeepSeek V3 Gemini 3.1 Pro Net Delta / Advantage
Input Cost / 1M Tokens $0.14 $1.25 DeepSeek V3 is 8.9x cheaper
Output Cost / 1M Tokens $0.28 $10.00 DeepSeek V3 (97.2% lower)
Prompt Cache Read / 1M $0.014 $0.310 DeepSeek V3 is 22.1x cheaper
Prompt Cache Write / 1M $0.14 $1.25 DeepSeek V3 is 8.9x cheaper
Context Window (Max Output) 131k (8k out) 1,049k (66k out) Gemini 3.1 Pro (8.0x larger context)
Avg TTFT Response Latency 410ms 420ms DeepSeek V3 (10ms faster)
Generation Speed (Throughput) 78 tok/s 98 tok/s Gemini 3.1 Pro (+20 tok/s faster)
SWE-bench Verified (Coding) 42% 71.8% Gemini 3.1 Pro (+29.8% lead)
GPQA Diamond (PhD STEM) 59.1% 82.4% Gemini 3.1 Pro (+23.3% lead)
MMLU-Pro (Multi-Discipline) 75.9% 89.5% Gemini 3.1 Pro (+13.6% lead)
MATH-500 (Quantitative Logic) 90.2% 96.8% Gemini 3.1 Pro (+6.6% lead)
Inference Value Score (IVR) 75 / 100 60 / 100 DeepSeek V3 (+15 pts)

Interactive Monthly Token Economics & ROI Forecaster

Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.

25.0M Tokens
500K 50M 250M 500M+
5.0M Tokens
100K 25M 75M 150M+
50% Cached
0% (Uncached) 25% 50% (Typical Agent) 95% Max

Estimated Monthly Spend

DeepSeek V3 $3.33

$0.14/1M in · $0.28/1M out

Prompt Cache: $0.014/1M read · $0.14/1M write

Gemini 3.1 Pro $69.50

$1.25/1M in · $10.00/1M out

Prompt Cache: $0.310/1M read · $1.25/1M write

Projected Monthly Cost Reduction
$66.18 / mo
(95.2% lower cost with DeepSeek V3)
Open Full Matchup Analysis →
A

When to Choose DeepSeek V3

Choose DeepSeek V3 (DeepSeek) for cost-sensitive batch text processing, drafting, and open-weight self-hosted inference — offering a 131k context window, 410ms TTFT, and $0.14/1M input pricing ($0.014/1M cached reads).

B

When to Choose Gemini 3.1 Pro

Choose Gemini 3.1 Pro (Google) for complex enterprise architecture planning, multi-file code refactoring, legal/financial corpus auditing, and multimodal research — offering a 1,048k context window, 420ms TTFT, and $1.25/1M input pricing ($0.310/1M cached reads).

Related Questions & Decision Factors

Which is cheaper: DeepSeek V3 or Gemini 3.1 Pro?

DeepSeek V3 is cheaper at $0.14/1M input tokens ($0.28/1M output) compared to $1.25/1M input ($10.00/1M output) for Gemini 3.1 Pro.

Which model has lower TTFT latency and higher tok/s throughput: DeepSeek V3 or Gemini 3.1 Pro?

DeepSeek V3 delivers faster first-token latency at 410ms TTFT (78 tok/s throughput) compared to 420ms TTFT (98 tok/s) for Gemini 3.1 Pro.

How do DeepSeek V3 and Gemini 3.1 Pro compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, DeepSeek V3 scores 42% versus 71.8% for Gemini 3.1 Pro. On GPQA Diamond graduate-level STEM reasoning, DeepSeek V3 scores 59.1% versus 82.4% for Gemini 3.1 Pro (and 90.2% vs 96.8% on MATH-500).

When should you choose DeepSeek V3?

Choose DeepSeek V3 (DeepSeek) for cost-sensitive batch text processing, drafting, and open-weight self-hosted inference — offering a 131k context window, 410ms TTFT, and $0.14/1M input pricing ($0.014/1M cached reads).

When should you choose Gemini 3.1 Pro?

Choose Gemini 3.1 Pro (Google) for complex enterprise architecture planning, multi-file code refactoring, legal/financial corpus auditing, and multimodal research — offering a 1,048k context window, 420ms TTFT, and $1.25/1M input pricing ($0.310/1M cached reads).

Explore High-Priority Related Model Matchups