Which model is better: Claude 3.5 Haiku or DeepSeek R1?
DeepSeek R1 is 31.2% cheaper for input tokens ($0.55 vs. $0.80 per 1M tokens) and $2.19 vs. $4.00 for output tokens (1.5x cost advantage). In terms of operational performance, Claude 3.5 Haiku delivers lower response latency at 190ms TTFT (1260ms faster than DeepSeek R1) with 130 vs. 58 tok/s throughput. DeepSeek R1 leads coding evaluations at 49.2% SWE-bench Verified vs. 40.6% for Claude 3.5 Haiku and 71.5% vs. 41.6% 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 3.5 Haiku
DeepSeek R1
Net Delta / Advantage
Input Cost / 1M Tokens
$0.80
$0.55
DeepSeek R1 is 1.5x cheaper
Output Cost / 1M Tokens
$4.00
$2.19
DeepSeek R1 (45.3% lower)
Prompt Cache Read / 1M
$0.080
$0.140
Claude 3.5 Haiku is 1.8x cheaper
Prompt Cache Write / 1M
$1.00
$0.55
DeepSeek R1 is 1.8x cheaper
Context Window (Max Output)
205k (8k out)
131k (33k out)
Claude 3.5 Haiku (1.6x larger context)
Avg TTFT Response Latency
190ms
1450ms
Claude 3.5 Haiku (1260ms faster)
Generation Speed (Throughput)
130 tok/s
58 tok/s
Claude 3.5 Haiku (+72 tok/s faster)
SWE-bench Verified (Coding)
40.6%
49.2%
DeepSeek R1 (+8.6% lead)
GPQA Diamond (PhD STEM)
41.6%
71.5%
DeepSeek R1 (+29.9% lead)
MMLU-Pro (Multi-Discipline)
71%
84%
DeepSeek R1 (+13.0% lead)
MATH-500 (Quantitative Logic)
69.4%
97.3%
DeepSeek R1 (+27.9% lead)
Inference Value Score (IVR)
52.4 / 100
64.8 / 100
DeepSeek R1 (+12.4 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 3.5 Haiku or DeepSeek R1?
DeepSeek R1 is cheaper at $0.55/1M input tokens ($2.19/1M output) compared to $0.80/1M input ($4.00/1M output) for Claude 3.5 Haiku.
Which model has lower TTFT latency and higher tok/s throughput: Claude 3.5 Haiku or DeepSeek R1?
Claude 3.5 Haiku delivers faster first-token latency at 190ms TTFT (130 tok/s throughput) compared to 1450ms TTFT (58 tok/s) for DeepSeek R1.
How do Claude 3.5 Haiku and DeepSeek R1 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Claude 3.5 Haiku scores 40.6% versus 49.2% for DeepSeek R1. On GPQA Diamond graduate-level STEM reasoning, Claude 3.5 Haiku scores 41.6% versus 71.5% for DeepSeek R1 (and 69.4% vs 97.3% on MATH-500).
When should you choose Claude 3.5 Haiku?
Choose Claude 3.5 Haiku (Anthropic) for rapid customer-facing chat, sub-agent routing, and real-time code autocomplete — offering a 204k context window, 190ms TTFT, and $0.80/1M input pricing ($0.080/1M 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).
