Which model is better: DeepSeek R1 or Gemini 3.8 Flash?
Gemini 3.8 Flash is 54.5% cheaper for input tokens ($0.25 vs. $0.55 per 1M tokens) and $1.50 vs. $2.19 for output tokens (2.2x cost advantage). In terms of operational performance, Gemini 3.8 Flash delivers lower response latency at 105ms TTFT (1345ms faster than DeepSeek R1) with 210 vs. 58 tok/s throughput. Gemini 3.8 Flash leads coding evaluations at 68.5% SWE-bench Verified vs. 49.2% for DeepSeek R1 and 79.2% 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 3.8 Flash
Net Delta / Advantage
Input Cost / 1M Tokens
$0.55
$0.25
Gemini 3.8 Flash is 2.2x cheaper
Output Cost / 1M Tokens
$2.19
$1.50
Gemini 3.8 Flash (31.5% lower)
Prompt Cache Read / 1M
$0.140
$0.025
Gemini 3.8 Flash is 5.6x cheaper
Prompt Cache Write / 1M
$0.55
$0.25
Gemini 3.8 Flash is 2.2x cheaper
Context Window (Max Output)
131k (33k out)
1,049k (66k out)
Gemini 3.8 Flash (8.0x larger context)
Avg TTFT Response Latency
1450ms
105ms
Gemini 3.8 Flash (1345ms faster)
Generation Speed (Throughput)
58 tok/s
210 tok/s
Gemini 3.8 Flash (+152 tok/s faster)
SWE-bench Verified (Coding)
49.2%
68.5%
Gemini 3.8 Flash (+19.3% lead)
GPQA Diamond (PhD STEM)
71.5%
79.2%
Gemini 3.8 Flash (+7.7% lead)
MMLU-Pro (Multi-Discipline)
84%
87.4%
Gemini 3.8 Flash (+3.4% lead)
MATH-500 (Quantitative Logic)
97.3%
95.1%
DeepSeek R1 (+2.2% lead)
Inference Value Score (IVR)
64.8 / 100
74 / 100
Gemini 3.8 Flash (+9.2 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 3.8 Flash (Google) for high-throughput agentic workflows, real-time multimodal RAG, live search grounding, and production code generation at flash unit economics — offering a 1,048k context window, 105ms TTFT, and $0.25/1M input pricing ($0.025/1M cached reads).
Which is cheaper: DeepSeek R1 or Gemini 3.8 Flash?
Gemini 3.8 Flash is cheaper at $0.25/1M input tokens ($1.50/1M output) compared to $0.55/1M input ($2.19/1M output) for DeepSeek R1.
Which model has lower TTFT latency and higher tok/s throughput: DeepSeek R1 or Gemini 3.8 Flash?
Gemini 3.8 Flash delivers faster first-token latency at 105ms TTFT (210 tok/s throughput) compared to 1450ms TTFT (58 tok/s) for DeepSeek R1.
How do DeepSeek R1 and Gemini 3.8 Flash compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek R1 scores 49.2% versus 68.5% for Gemini 3.8 Flash. On GPQA Diamond graduate-level STEM reasoning, DeepSeek R1 scores 71.5% versus 79.2% for Gemini 3.8 Flash (and 97.3% vs 95.1% 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 3.8 Flash?
Choose Gemini 3.8 Flash (Google) for high-throughput agentic workflows, real-time multimodal RAG, live search grounding, and production code generation at flash unit economics — offering a 1,048k context window, 105ms TTFT, and $0.25/1M input pricing ($0.025/1M cached reads).
