Which model is better: Claude 3.5 Haiku or DeepSeek V3?
DeepSeek V3 is 82.5% cheaper for input tokens ($0.14 vs. $0.80 per 1M tokens) and $0.28 vs. $4.00 for output tokens (5.7x cost advantage). In terms of operational performance, Claude 3.5 Haiku delivers lower response latency at 190ms TTFT (220ms faster than DeepSeek V3) with 130 vs. 78 tok/s throughput. DeepSeek V3 leads coding evaluations at 42.0% SWE-bench Verified vs. 40.6% for Claude 3.5 Haiku and 59.1% 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 V3
Net Delta / Advantage
Input Cost / 1M Tokens
$0.80
$0.14
DeepSeek V3 is 5.7x cheaper
Output Cost / 1M Tokens
$4.00
$0.28
DeepSeek V3 (93.0% lower)
Prompt Cache Read / 1M
$0.080
$0.014
DeepSeek V3 is 5.7x cheaper
Prompt Cache Write / 1M
$1.00
$0.14
DeepSeek V3 is 7.1x cheaper
Context Window (Max Output)
205k (8k out)
131k (8k out)
Claude 3.5 Haiku (1.6x larger context)
Avg TTFT Response Latency
190ms
410ms
Claude 3.5 Haiku (220ms faster)
Generation Speed (Throughput)
130 tok/s
78 tok/s
Claude 3.5 Haiku (+52 tok/s faster)
SWE-bench Verified (Coding)
40.6%
42%
DeepSeek V3 (+1.4% lead)
GPQA Diamond (PhD STEM)
41.6%
59.1%
DeepSeek V3 (+17.5% lead)
MMLU-Pro (Multi-Discipline)
71%
75.9%
DeepSeek V3 (+4.9% lead)
MATH-500 (Quantitative Logic)
69.4%
90.2%
DeepSeek V3 (+20.8% lead)
Inference Value Score (IVR)
52.4 / 100
75 / 100
DeepSeek V3 (+22.6 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 V3?
DeepSeek V3 is cheaper at $0.14/1M input tokens ($0.28/1M 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 V3?
Claude 3.5 Haiku delivers faster first-token latency at 190ms TTFT (130 tok/s throughput) compared to 410ms TTFT (78 tok/s) for DeepSeek V3.
How do Claude 3.5 Haiku and DeepSeek V3 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Claude 3.5 Haiku scores 40.6% versus 42% for DeepSeek V3. On GPQA Diamond graduate-level STEM reasoning, Claude 3.5 Haiku scores 41.6% versus 59.1% for DeepSeek V3 (and 69.4% vs 90.2% 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 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).
