Which model is better: Claude Opus 5.5 or DeepSeek R1?
DeepSeek R1 is 86.2% cheaper for input tokens ($0.55 vs. $4.00 per 1M tokens) and $2.19 vs. $20.00 for output tokens (7.3x cost advantage). In terms of operational performance, Claude Opus 5.5 delivers lower response latency at 680ms TTFT (770ms faster than DeepSeek R1) with 95 vs. 58 tok/s throughput. Claude Opus 5.5 leads coding evaluations at 89.9% SWE-bench Verified vs. 49.2% for DeepSeek R1 and 93.2% 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
Claude Opus 5.5
DeepSeek R1
Net Delta / Advantage
Input Cost / 1M Tokens
$4.00
$0.55
DeepSeek R1 is 7.3x cheaper
Output Cost / 1M Tokens
$20.00
$2.19
DeepSeek R1 (89.0% lower)
Prompt Cache Read / 1M
$0.200
$0.140
DeepSeek R1 is 1.4x cheaper
Prompt Cache Write / 1M
$5.00
$0.55
DeepSeek R1 is 9.1x cheaper
Context Window (Max Output)
1,024k (128k out)
131k (33k out)
Claude Opus 5.5 (7.8x larger context)
Avg TTFT Response Latency
680ms
1450ms
Claude Opus 5.5 (770ms faster)
Generation Speed (Throughput)
95 tok/s
58 tok/s
Claude Opus 5.5 (+37 tok/s faster)
SWE-bench Verified (Coding)
89.9%
49.2%
Claude Opus 5.5 (+40.7% lead)
GPQA Diamond (PhD STEM)
93.2%
71.5%
Claude Opus 5.5 (+21.7% lead)
MMLU-Pro (Multi-Discipline)
92.1%
84%
Claude Opus 5.5 (+8.1% lead)
MATH-500 (Quantitative Logic)
98%
97.3%
Claude Opus 5.5 (+0.7% lead)
Inference Value Score (IVR)
57.8 / 100
64.8 / 100
DeepSeek R1 (+7 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose Claude Opus 5.5 (Anthropic) for top-ranked frontier intelligence leader for autonomous multi-step agentic coding, repository-scale migrations, and complex scientific reasoning at a 40% lower workload cost than Opus 5 — offering a 1,024k context window, 680ms TTFT, and $4.00/1M input pricing ($0.200/1M cached reads).
DeepSeek R1 is cheaper at $0.55/1M input tokens ($2.19/1M output) compared to $4.00/1M input ($20.00/1M output) for Claude Opus 5.5.
Which model has lower TTFT latency and higher tok/s throughput: Claude Opus 5.5 or DeepSeek R1?
Claude Opus 5.5 delivers faster first-token latency at 680ms TTFT (95 tok/s throughput) compared to 1450ms TTFT (58 tok/s) for DeepSeek R1.
How do Claude Opus 5.5 and DeepSeek R1 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Claude Opus 5.5 scores 89.9% versus 49.2% for DeepSeek R1. On GPQA Diamond graduate-level STEM reasoning, Claude Opus 5.5 scores 93.2% versus 71.5% for DeepSeek R1 (and 98% vs 97.3% on MATH-500).
When should you choose Claude Opus 5.5?
Choose Claude Opus 5.5 (Anthropic) for top-ranked frontier intelligence leader for autonomous multi-step agentic coding, repository-scale migrations, and complex scientific reasoning at a 40% lower workload cost than Opus 5 — offering a 1,024k context window, 680ms TTFT, and $4.00/1M input pricing ($0.200/1M cached reads).
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).
