Which model is better: DeepSeek R1 or Gemini 2.5 Pro?
DeepSeek R1 is 56.0% cheaper for input tokens ($0.55 vs. $1.25 per 1M tokens) and $2.19 vs. $10.00 for output tokens (2.3x cost advantage). In terms of operational performance, Gemini 2.5 Pro delivers lower response latency at 700ms TTFT (750ms faster than DeepSeek R1) with 80 vs. 58 tok/s throughput. Gemini 2.5 Pro leads coding evaluations at 63.8% SWE-bench Verified vs. 49.2% for DeepSeek R1 and 74.0% vs. 71.5% 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 R1
Gemini 2.5 Pro
Net Delta / Advantage
Input Cost / 1M Tokens
$0.55
$1.25
DeepSeek R1 is 2.3x cheaper
Output Cost / 1M Tokens
$2.19
$10.00
DeepSeek R1 (78.1% lower)
Prompt Cache Read / 1M
$0.140
$0.313
DeepSeek R1 is 2.2x cheaper
Prompt Cache Write / 1M
$0.55
$1.25
DeepSeek R1 is 2.3x cheaper
Context Window (Max Output)
131k (33k out)
1,024k (66k out)
Gemini 2.5 Pro (7.8x larger context)
Avg TTFT Response Latency
1450ms
700ms
Gemini 2.5 Pro (750ms faster)
Generation Speed (Throughput)
58 tok/s
80 tok/s
Gemini 2.5 Pro (+22 tok/s faster)
SWE-bench Verified (Coding)
49.2%
63.8%
Gemini 2.5 Pro (+14.6% lead)
GPQA Diamond (PhD STEM)
71.5%
74%
Gemini 2.5 Pro (+2.5% lead)
MMLU-Pro (Multi-Discipline)
84%
85.2%
Gemini 2.5 Pro (+1.2% lead)
MATH-500 (Quantitative Logic)
97.3%
95%
DeepSeek R1 (+2.3% lead)
Inference Value Score (IVR)
64.8 / 100
56.8 / 100
DeepSeek R1 (+8 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 R1 is cheaper at $0.55/1M input tokens ($2.19/1M 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 R1 or Gemini 2.5 Pro?
Gemini 2.5 Pro delivers faster first-token latency at 700ms TTFT (80 tok/s throughput) compared to 1450ms TTFT (58 tok/s) for DeepSeek R1.
How do DeepSeek R1 and Gemini 2.5 Pro compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek R1 scores 49.2% versus 63.8% for Gemini 2.5 Pro. On GPQA Diamond graduate-level STEM reasoning, DeepSeek R1 scores 71.5% versus 74% for Gemini 2.5 Pro (and 97.3% vs 95% on MATH-500).
When should you choose DeepSeek R1?
Choose DeepSeek R1 (DeepSeek) for open-weight chain-of-thought reasoning, synthetic data distillation, and complex mathematical verification — offering a 131k context window, 1450ms TTFT, and $0.55/1M input pricing ($0.140/1M 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).
