💰 Unit Cost Winner Gemini 3.8 Flash $0.25/1M in · $1.50/1M out
⚡ Latency & Speed Winner Gemini 3.8 Flash 105ms TTFT · 210 tok/s
💻 Coding (SWE) Winner DeepSeek V4 Pro 80.6% SWE-bench · 94.5% HumanEval
🧠 STEM Reasoning Winner DeepSeek V4 Pro 90.1% GPQA · 97.3% MATH-500

Which model is better: DeepSeek V4 Pro or Gemini 3.8 Flash?

Gemini 3.8 Flash is 81.1% cheaper for input tokens ($0.25 vs. $1.32 per 1M tokens) and $1.50 vs. $3.96 for output tokens (5.3x cost advantage). In terms of operational performance, Gemini 3.8 Flash delivers lower response latency at 105ms TTFT (415ms faster than DeepSeek V4 Pro) with 210 vs. 78 tok/s throughput. DeepSeek V4 Pro leads coding evaluations at 80.6% SWE-bench Verified vs. 68.5% for Gemini 3.8 Flash and 90.1% vs. 79.2% 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 V4 Pro Gemini 3.8 Flash Net Delta / Advantage
Input Cost / 1M Tokens $1.32 $0.25 Gemini 3.8 Flash is 5.3x cheaper
Output Cost / 1M Tokens $3.96 $1.50 Gemini 3.8 Flash (62.1% lower)
Prompt Cache Read / 1M $0.145 $0.025 Gemini 3.8 Flash is 5.8x cheaper
Prompt Cache Write / 1M $1.32 $0.25 Gemini 3.8 Flash is 5.3x cheaper
Context Window (Max Output) 1,024k (128k out) 1,049k (66k out) Gemini 3.8 Flash (1.0x larger context)
Avg TTFT Response Latency 520ms 105ms Gemini 3.8 Flash (415ms faster)
Generation Speed (Throughput) 78 tok/s 210 tok/s Gemini 3.8 Flash (+132 tok/s faster)
SWE-bench Verified (Coding) 80.6% 68.5% DeepSeek V4 Pro (+12.1% lead)
GPQA Diamond (PhD STEM) 90.1% 79.2% DeepSeek V4 Pro (+10.9% lead)
MMLU-Pro (Multi-Discipline) 88.4% 87.4% DeepSeek V4 Pro (+1.0% lead)
MATH-500 (Quantitative Logic) 97.3% 95.1% DeepSeek V4 Pro (+2.2% lead)
Inference Value Score (IVR) 67 / 100 74 / 100 Gemini 3.8 Flash (+7 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 V4 Pro $38.11

$1.32/1M in · $3.96/1M out

Prompt Cache: $0.145/1M read · $1.32/1M write

Gemini 3.8 Flash $10.94

$0.25/1M in · $1.50/1M out

Prompt Cache: $0.025/1M read · $0.25/1M write

Projected Monthly Cost Reduction
$27.17 / mo
(71.3% lower cost with Gemini 3.8 Flash)
Open Full Matchup Analysis →
A

When to Choose DeepSeek V4 Pro

Choose DeepSeek V4 Pro (DeepSeek) for open-weight 1.6T MoE powerhouse designed for cost-effective full-repository code generation, mathematical reasoning, and persistent chain-of-thought multi-step agent workflows — offering a 1,024k context window, 520ms TTFT, and $1.32/1M input pricing ($0.145/1M cached reads).

B

When to 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).

Related Questions & Decision Factors

Which is cheaper: DeepSeek V4 Pro or Gemini 3.8 Flash?

Gemini 3.8 Flash is cheaper at $0.25/1M input tokens ($1.50/1M output) compared to $1.32/1M input ($3.96/1M output) for DeepSeek V4 Pro.

Which model has lower TTFT latency and higher tok/s throughput: DeepSeek V4 Pro or Gemini 3.8 Flash?

Gemini 3.8 Flash delivers faster first-token latency at 105ms TTFT (210 tok/s throughput) compared to 520ms TTFT (78 tok/s) for DeepSeek V4 Pro.

How do DeepSeek V4 Pro and Gemini 3.8 Flash compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, DeepSeek V4 Pro scores 80.6% versus 68.5% for Gemini 3.8 Flash. On GPQA Diamond graduate-level STEM reasoning, DeepSeek V4 Pro scores 90.1% versus 79.2% for Gemini 3.8 Flash (and 97.3% vs 95.1% on MATH-500).

When should you choose DeepSeek V4 Pro?

Choose DeepSeek V4 Pro (DeepSeek) for open-weight 1.6T MoE powerhouse designed for cost-effective full-repository code generation, mathematical reasoning, and persistent chain-of-thought multi-step agent workflows — offering a 1,024k context window, 520ms TTFT, and $1.32/1M input pricing ($0.145/1M 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).

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