Which model is better: DeepSeek V3 or Llama 3.3 70B Instruct?
Llama 3.3 70B Instruct is 14.3% cheaper for input tokens ($0.12 vs. $0.14 per 1M tokens) and $0.30 vs. $0.28 for output tokens (1.2x cost advantage). In terms of operational performance, Llama 3.3 70B Instruct delivers lower response latency at 145ms TTFT (265ms faster than DeepSeek V3) with 165 vs. 78 tok/s throughput. Llama 3.3 70B Instruct leads coding evaluations at 42.5% SWE-bench Verified vs. 42.0% for DeepSeek V3 and 55.6% 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 V3
Llama 3.3 70B Instruct
Net Delta / Advantage
Input Cost / 1M Tokens
$0.14
$0.12
Llama 3.3 70B Instruct is 1.2x cheaper
Output Cost / 1M Tokens
$0.28
$0.30
DeepSeek V3 (6.7% lower)
Prompt Cache Read / 1M
$0.014
$0.030
DeepSeek V3 is 2.1x cheaper
Prompt Cache Write / 1M
$0.14
$0.12
Llama 3.3 70B Instruct is 1.2x cheaper
Context Window (Max Output)
131k (8k out)
131k (33k out)
Equal Context Window
Avg TTFT Response Latency
410ms
145ms
Llama 3.3 70B Instruct (265ms faster)
Generation Speed (Throughput)
78 tok/s
165 tok/s
Llama 3.3 70B Instruct (+87 tok/s faster)
SWE-bench Verified (Coding)
42%
42.5%
Llama 3.3 70B Instruct (+0.5% lead)
GPQA Diamond (PhD STEM)
59.1%
55.6%
DeepSeek V3 (+3.5% lead)
MMLU-Pro (Multi-Discipline)
75.9%
76.8%
Llama 3.3 70B Instruct (+0.9% lead)
MATH-500 (Quantitative Logic)
90.2%
77%
DeepSeek V3 (+13.2% lead)
Inference Value Score (IVR)
75 / 100
74.6 / 100
DeepSeek V3 (+0.4 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: DeepSeek V3 or Llama 3.3 70B Instruct?
Llama 3.3 70B Instruct is cheaper at $0.12/1M input tokens ($0.30/1M output) compared to $0.14/1M input ($0.28/1M output) for DeepSeek V3.
Which model has lower TTFT latency and higher tok/s throughput: DeepSeek V3 or Llama 3.3 70B Instruct?
Llama 3.3 70B Instruct delivers faster first-token latency at 145ms TTFT (165 tok/s throughput) compared to 410ms TTFT (78 tok/s) for DeepSeek V3.
How do DeepSeek V3 and Llama 3.3 70B Instruct compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek V3 scores 42% versus 42.5% for Llama 3.3 70B Instruct. On GPQA Diamond graduate-level STEM reasoning, DeepSeek V3 scores 59.1% versus 55.6% for Llama 3.3 70B Instruct (and 90.2% vs 77% on MATH-500).
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).
When should you choose Llama 3.3 70B Instruct?
Choose Llama 3.3 70B Instruct (Meta) for cost-optimized on-premise deployments, fast text transformation, structured entity extraction, and enterprise dialogue pipelines — offering a 131k context window, 145ms TTFT, and $0.12/1M input pricing ($0.030/1M cached reads).
