Which model is better: DeepSeek R1 or DeepSeek V3?
DeepSeek V3 is 74.5% cheaper for input tokens ($0.14 vs. $0.55 per 1M tokens) and $0.28 vs. $2.19 for output tokens (3.9x cost advantage). In terms of operational performance, DeepSeek V3 delivers lower response latency at 410ms TTFT (1040ms faster than DeepSeek R1) with 78 vs. 58 tok/s throughput. DeepSeek R1 leads coding evaluations at 49.2% SWE-bench Verified vs. 42.0% for DeepSeek V3 and 71.5% 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 R1
DeepSeek V3
Net Delta / Advantage
Input Cost / 1M Tokens
$0.55
$0.14
DeepSeek V3 is 3.9x cheaper
Output Cost / 1M Tokens
$2.19
$0.28
DeepSeek V3 (87.2% lower)
Prompt Cache Read / 1M
$0.140
$0.014
DeepSeek V3 is 10.0x cheaper
Prompt Cache Write / 1M
$0.55
$0.14
DeepSeek V3 is 3.9x cheaper
Context Window (Max Output)
131k (33k out)
131k (8k out)
Equal Context Window
Avg TTFT Response Latency
1450ms
410ms
DeepSeek V3 (1040ms faster)
Generation Speed (Throughput)
58 tok/s
78 tok/s
DeepSeek V3 (+20 tok/s faster)
SWE-bench Verified (Coding)
49.2%
42%
DeepSeek R1 (+7.2% lead)
GPQA Diamond (PhD STEM)
71.5%
59.1%
DeepSeek R1 (+12.4% lead)
MMLU-Pro (Multi-Discipline)
84%
75.9%
DeepSeek R1 (+8.1% lead)
MATH-500 (Quantitative Logic)
97.3%
90.2%
DeepSeek R1 (+7.1% lead)
Inference Value Score (IVR)
64.8 / 100
75 / 100
DeepSeek V3 (+10.2 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
DeepSeek V3 is cheaper at $0.14/1M input tokens ($0.28/1M 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 DeepSeek V3?
DeepSeek V3 delivers faster first-token latency at 410ms TTFT (78 tok/s throughput) compared to 1450ms TTFT (58 tok/s) for DeepSeek R1.
How do DeepSeek R1 and DeepSeek V3 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek R1 scores 49.2% versus 42% for DeepSeek V3. On GPQA Diamond graduate-level STEM reasoning, DeepSeek R1 scores 71.5% versus 59.1% for DeepSeek V3 (and 97.3% vs 90.2% 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 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).
