Which model is better: Llama 3.3 70B Instruct or OpenAI o3?
Llama 3.3 70B Instruct is 94.0% cheaper for input tokens ($0.12 vs. $2.00 per 1M tokens) and $0.30 vs. $8.00 for output tokens (16.7x cost advantage). In terms of operational performance, Llama 3.3 70B Instruct delivers lower response latency at 145ms TTFT (1005ms faster than OpenAI o3) with 165 vs. 82 tok/s throughput. OpenAI o3 leads coding evaluations at 71.7% SWE-bench Verified vs. 42.5% for Llama 3.3 70B Instruct and 87.7% vs. 55.6% 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
Llama 3.3 70B Instruct
OpenAI o3
Net Delta / Advantage
Input Cost / 1M Tokens
$0.12
$2.00
Llama 3.3 70B Instruct is 16.7x cheaper
Output Cost / 1M Tokens
$0.30
$8.00
Llama 3.3 70B Instruct (96.3% lower)
Prompt Cache Read / 1M
$0.030
$0.500
Llama 3.3 70B Instruct is 16.7x cheaper
Prompt Cache Write / 1M
$0.12
$2.00
Llama 3.3 70B Instruct is 16.7x cheaper
Context Window (Max Output)
131k (33k out)
205k (100k out)
OpenAI o3 (1.6x larger context)
Avg TTFT Response Latency
145ms
1150ms
Llama 3.3 70B Instruct (1005ms faster)
Generation Speed (Throughput)
165 tok/s
82 tok/s
Llama 3.3 70B Instruct (+83 tok/s faster)
SWE-bench Verified (Coding)
42.5%
71.7%
OpenAI o3 (+29.2% lead)
GPQA Diamond (PhD STEM)
55.6%
87.7%
OpenAI o3 (+32.1% lead)
MMLU-Pro (Multi-Discipline)
76.8%
89.8%
OpenAI o3 (+13.0% lead)
MATH-500 (Quantitative Logic)
77%
98.6%
OpenAI o3 (+21.6% lead)
Inference Value Score (IVR)
74.6 / 100
60.6 / 100
Llama 3.3 70B Instruct (+14 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: Llama 3.3 70B Instruct or OpenAI o3?
Llama 3.3 70B Instruct is cheaper at $0.12/1M input tokens ($0.30/1M output) compared to $2.00/1M input ($8.00/1M output) for OpenAI o3.
Which model has lower TTFT latency and higher tok/s throughput: Llama 3.3 70B Instruct or OpenAI o3?
Llama 3.3 70B Instruct delivers faster first-token latency at 145ms TTFT (165 tok/s throughput) compared to 1150ms TTFT (82 tok/s) for OpenAI o3.
How do Llama 3.3 70B Instruct and OpenAI o3 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Llama 3.3 70B Instruct scores 42.5% versus 71.7% for OpenAI o3. On GPQA Diamond graduate-level STEM reasoning, Llama 3.3 70B Instruct scores 55.6% versus 87.7% for OpenAI o3 (and 77% vs 98.6% on MATH-500).
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).
When should you choose OpenAI o3?
Choose OpenAI o3 (OpenAI) for algorithmic synthesis, mathematical verification, PhD-level scientific research, and multi-step tool planning — offering a 204k context window, 1150ms TTFT, and $2.00/1M input pricing ($0.500/1M cached reads).
