Which model is better: Grok 3 or Llama 3.3 70B Instruct?
Llama 3.3 70B Instruct is 96.0% cheaper for input tokens ($0.12 vs. $3.00 per 1M tokens) and $0.30 vs. $15.00 for output tokens (25.0x cost advantage). In terms of operational performance, Llama 3.3 70B Instruct delivers lower response latency at 145ms TTFT (475ms faster than Grok 3) with 165 vs. 88 tok/s throughput. Grok 3 leads coding evaluations at 65.8% SWE-bench Verified vs. 42.5% for Llama 3.3 70B Instruct and 84.6% 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
Grok 3
Llama 3.3 70B Instruct
Net Delta / Advantage
Input Cost / 1M Tokens
$3.00
$0.12
Llama 3.3 70B Instruct is 25.0x cheaper
Output Cost / 1M Tokens
$15.00
$0.30
Llama 3.3 70B Instruct (98.0% lower)
Prompt Cache Read / 1M
$0.750
$0.030
Llama 3.3 70B Instruct is 25.0x cheaper
Prompt Cache Write / 1M
$3.00
$0.12
Llama 3.3 70B Instruct is 25.0x cheaper
Context Window (Max Output)
134k (16k out)
131k (33k out)
Grok 3 (1.0x larger context)
Avg TTFT Response Latency
620ms
145ms
Llama 3.3 70B Instruct (475ms faster)
Generation Speed (Throughput)
88 tok/s
165 tok/s
Llama 3.3 70B Instruct (+77 tok/s faster)
SWE-bench Verified (Coding)
65.8%
42.5%
Grok 3 (+23.3% lead)
GPQA Diamond (PhD STEM)
84.6%
55.6%
Grok 3 (+29.0% lead)
MMLU-Pro (Multi-Discipline)
80%
76.8%
Grok 3 (+3.2% lead)
MATH-500 (Quantitative Logic)
89.8%
77%
Grok 3 (+12.8% lead)
Inference Value Score (IVR)
52.7 / 100
74.6 / 100
Llama 3.3 70B Instruct (+21.9 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose Grok 3 (xAI) for massive compute foundation model specialized in PhD-level science reasoning, real-time data analysis, and enterprise logic — offering a 134k context window, 620ms TTFT, and $3.00/1M input pricing ($0.750/1M cached reads).
Which is cheaper: Grok 3 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 $3.00/1M input ($15.00/1M output) for Grok 3.
Which model has lower TTFT latency and higher tok/s throughput: Grok 3 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 620ms TTFT (88 tok/s) for Grok 3.
How do Grok 3 and Llama 3.3 70B Instruct compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Grok 3 scores 65.8% versus 42.5% for Llama 3.3 70B Instruct. On GPQA Diamond graduate-level STEM reasoning, Grok 3 scores 84.6% versus 55.6% for Llama 3.3 70B Instruct (and 89.8% vs 77% on MATH-500).
When should you choose Grok 3?
Choose Grok 3 (xAI) for massive compute foundation model specialized in PhD-level science reasoning, real-time data analysis, and enterprise logic — offering a 134k context window, 620ms TTFT, and $3.00/1M input pricing ($0.750/1M 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).
