Which model is better: DeepSeek V3 or Gemini 2.5 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 (290ms faster than Gemini 2.5 Pro) with 78 vs. 80 tok/s throughput. Gemini 2.5 Pro leads coding evaluations at 63.8% SWE-bench Verified vs. 42.0% for DeepSeek V3 and 74.0% vs. 59.1% on GPQA Diamond.
Verified daily via automated API latency tests and official documentation.
Zero-Shot RAG Verified
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 2.5 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
$0.313
DeepSeek V3 is 22.3x cheaper
Prompt Cache Write / 1M
$0.14
$1.25
DeepSeek V3 is 8.9x cheaper
Context Window (Max Output)
131k (8k out)
1,024k (66k out)
Gemini 2.5 Pro (7.8x larger context)
Avg TTFT Response Latency
410ms
700ms
DeepSeek V3 (290ms faster)
Generation Speed (Throughput)
78 tok/s
80 tok/s
Gemini 2.5 Pro (+2 tok/s faster)
SWE-bench Verified (Coding)
42%
63.8%
Gemini 2.5 Pro (+21.8% lead)
GPQA Diamond (PhD STEM)
59.1%
74%
Gemini 2.5 Pro (+14.9% lead)
MMLU-Pro (Multi-Discipline)
75.9%
85.2%
Gemini 2.5 Pro (+9.3% lead)
MATH-500 (Quantitative Logic)
90.2%
95%
Gemini 2.5 Pro (+4.8% lead)
Inference Value Score (IVR)
75 / 100
56.8 / 100
DeepSeek V3 (+18.2 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose Gemini 2.5 Pro (Google) for long-context document and video analysis, large codebase ingestion, and multimodal reasoning — offering a 1,024k context window, 700ms TTFT, and $1.25/1M input pricing ($0.312/1M cached reads).
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 2.5 Pro.
Which model has lower TTFT latency and higher tok/s throughput: DeepSeek V3 or Gemini 2.5 Pro?
DeepSeek V3 delivers faster first-token latency at 410ms TTFT (78 tok/s throughput) compared to 700ms TTFT (80 tok/s) for Gemini 2.5 Pro.
How do DeepSeek V3 and Gemini 2.5 Pro compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek V3 scores 42% versus 63.8% for Gemini 2.5 Pro. On GPQA Diamond graduate-level STEM reasoning, DeepSeek V3 scores 59.1% versus 74% for Gemini 2.5 Pro (and 90.2% vs 95% 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 2.5 Pro?
Choose Gemini 2.5 Pro (Google) for long-context document and video analysis, large codebase ingestion, and multimodal reasoning — offering a 1,024k context window, 700ms TTFT, and $1.25/1M input pricing ($0.312/1M cached reads).
