Which model is better: Claude 3.7 Sonnet or DeepSeek V4 Pro?
DeepSeek V4 Pro is 56.0% cheaper for input tokens ($1.32 vs. $3.00 per 1M tokens) and $3.96 vs. $15.00 for output tokens (2.3x cost advantage). In terms of operational performance, DeepSeek V4 Pro delivers lower response latency at 520ms TTFT (20ms faster than Claude 3.7 Sonnet) with 78 vs. 72 tok/s throughput. DeepSeek V4 Pro leads coding evaluations at 80.6% SWE-bench Verified vs. 70.3% for Claude 3.7 Sonnet and 90.1% vs. 78.5% 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
Claude 3.7 Sonnet
DeepSeek V4 Pro
Net Delta / Advantage
Input Cost / 1M Tokens
$3.00
$1.32
DeepSeek V4 Pro is 2.3x cheaper
Output Cost / 1M Tokens
$15.00
$3.96
DeepSeek V4 Pro (73.6% lower)
Prompt Cache Read / 1M
$0.300
$0.145
DeepSeek V4 Pro is 2.1x cheaper
Prompt Cache Write / 1M
$3.75
$1.32
DeepSeek V4 Pro is 2.8x cheaper
Context Window (Max Output)
205k (64k out)
1,024k (128k out)
DeepSeek V4 Pro (5.0x larger context)
Avg TTFT Response Latency
540ms
520ms
DeepSeek V4 Pro (20ms faster)
Generation Speed (Throughput)
72 tok/s
78 tok/s
DeepSeek V4 Pro (+6 tok/s faster)
SWE-bench Verified (Coding)
70.3%
80.6%
DeepSeek V4 Pro (+10.3% lead)
GPQA Diamond (PhD STEM)
78.5%
90.1%
DeepSeek V4 Pro (+11.6% lead)
MMLU-Pro (Multi-Discipline)
88%
88.4%
DeepSeek V4 Pro (+0.4% lead)
MATH-500 (Quantitative Logic)
96.2%
97.3%
DeepSeek V4 Pro (+1.1% lead)
Inference Value Score (IVR)
54.3 / 100
67 / 100
DeepSeek V4 Pro (+12.7 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Which is cheaper: Claude 3.7 Sonnet or DeepSeek V4 Pro?
DeepSeek V4 Pro is cheaper at $1.32/1M input tokens ($3.96/1M output) compared to $3.00/1M input ($15.00/1M output) for Claude 3.7 Sonnet.
Which model has lower TTFT latency and higher tok/s throughput: Claude 3.7 Sonnet or DeepSeek V4 Pro?
DeepSeek V4 Pro delivers faster first-token latency at 520ms TTFT (78 tok/s throughput) compared to 540ms TTFT (72 tok/s) for Claude 3.7 Sonnet.
How do Claude 3.7 Sonnet and DeepSeek V4 Pro compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Claude 3.7 Sonnet scores 70.3% versus 80.6% for DeepSeek V4 Pro. On GPQA Diamond graduate-level STEM reasoning, Claude 3.7 Sonnet scores 78.5% versus 90.1% for DeepSeek V4 Pro (and 96.2% vs 97.3% on MATH-500).
When should you choose Claude 3.7 Sonnet?
Choose Claude 3.7 Sonnet (Anthropic) for full-stack repository development, complex code refactoring, and agentic tool use with predictable prompt cache economics — offering a 204k context window, 540ms TTFT, and $3.00/1M input pricing ($0.300/1M cached reads).
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).
