Which model is better: Llama 3.3 70B Instruct or OpenAI o3-mini?
Llama 3.3 70B Instruct is 89.1% cheaper for input tokens ($0.12 vs. $1.10 per 1M tokens) and $0.30 vs. $4.40 for output tokens (9.2x cost advantage). In terms of operational performance, Llama 3.3 70B Instruct delivers lower response latency at 145ms TTFT (805ms faster than OpenAI o3-mini) with 165 vs. 98 tok/s throughput. OpenAI o3-mini leads coding evaluations at 49.3% SWE-bench Verified vs. 42.5% for Llama 3.3 70B Instruct and 79.7% 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-mini
Net Delta / Advantage
Input Cost / 1M Tokens
$0.12
$1.10
Llama 3.3 70B Instruct is 9.2x cheaper
Output Cost / 1M Tokens
$0.30
$4.40
Llama 3.3 70B Instruct (93.2% lower)
Prompt Cache Read / 1M
$0.030
$0.550
Llama 3.3 70B Instruct is 18.3x cheaper
Prompt Cache Write / 1M
$0.12
$1.10
Llama 3.3 70B Instruct is 9.2x cheaper
Context Window (Max Output)
131k (33k out)
205k (100k out)
OpenAI o3-mini (1.6x larger context)
Avg TTFT Response Latency
145ms
950ms
Llama 3.3 70B Instruct (805ms faster)
Generation Speed (Throughput)
165 tok/s
98 tok/s
Llama 3.3 70B Instruct (+67 tok/s faster)
SWE-bench Verified (Coding)
42.5%
49.3%
OpenAI o3-mini (+6.8% lead)
GPQA Diamond (PhD STEM)
55.6%
79.7%
OpenAI o3-mini (+24.1% lead)
MMLU-Pro (Multi-Discipline)
76.8%
83.2%
OpenAI o3-mini (+6.4% lead)
MATH-500 (Quantitative Logic)
77%
97.9%
OpenAI o3-mini (+20.9% lead)
Inference Value Score (IVR)
74.6 / 100
59.7 / 100
Llama 3.3 70B Instruct (+14.9 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose OpenAI o3-mini (OpenAI) for competitive math reasoning, automated unit test generation, and structured logic pipelines — offering a 204k context window, 950ms TTFT, and $1.10/1M input pricing ($0.550/1M cached reads).
Which is cheaper: Llama 3.3 70B Instruct or OpenAI o3-mini?
Llama 3.3 70B Instruct is cheaper at $0.12/1M input tokens ($0.30/1M output) compared to $1.10/1M input ($4.40/1M output) for OpenAI o3-mini.
Which model has lower TTFT latency and higher tok/s throughput: Llama 3.3 70B Instruct or OpenAI o3-mini?
Llama 3.3 70B Instruct delivers faster first-token latency at 145ms TTFT (165 tok/s throughput) compared to 950ms TTFT (98 tok/s) for OpenAI o3-mini.
How do Llama 3.3 70B Instruct and OpenAI o3-mini compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Llama 3.3 70B Instruct scores 42.5% versus 49.3% for OpenAI o3-mini. On GPQA Diamond graduate-level STEM reasoning, Llama 3.3 70B Instruct scores 55.6% versus 79.7% for OpenAI o3-mini (and 77% vs 97.9% 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-mini?
Choose OpenAI o3-mini (OpenAI) for competitive math reasoning, automated unit test generation, and structured logic pipelines — offering a 204k context window, 950ms TTFT, and $1.10/1M input pricing ($0.550/1M cached reads).
