Which model is better: Claude 4 Opus or Llama 3.3 70B Instruct?
Llama 3.3 70B Instruct is 99.2% cheaper for input tokens ($0.12 vs. $15.00 per 1M tokens) and $0.30 vs. $75.00 for output tokens (125.0x cost advantage). In terms of operational performance, Llama 3.3 70B Instruct delivers lower response latency at 145ms TTFT (775ms faster than Claude 4 Opus) with 165 vs. 46 tok/s throughput. Claude 4 Opus leads coding evaluations at 77.2% SWE-bench Verified vs. 42.5% for Llama 3.3 70B Instruct and 87.1% 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
Claude 4 Opus
Llama 3.3 70B Instruct
Net Delta / Advantage
Input Cost / 1M Tokens
$15.00
$0.12
Llama 3.3 70B Instruct is 125.0x cheaper
Output Cost / 1M Tokens
$75.00
$0.30
Llama 3.3 70B Instruct (99.6% lower)
Prompt Cache Read / 1M
$1.500
$0.030
Llama 3.3 70B Instruct is 50.0x cheaper
Prompt Cache Write / 1M
$18.75
$0.12
Llama 3.3 70B Instruct is 156.3x cheaper
Context Window (Max Output)
205k (64k out)
131k (33k out)
Claude 4 Opus (1.6x larger context)
Avg TTFT Response Latency
920ms
145ms
Llama 3.3 70B Instruct (775ms faster)
Generation Speed (Throughput)
46 tok/s
165 tok/s
Llama 3.3 70B Instruct (+119 tok/s faster)
SWE-bench Verified (Coding)
77.2%
42.5%
Claude 4 Opus (+34.7% lead)
GPQA Diamond (PhD STEM)
87.1%
55.6%
Claude 4 Opus (+31.5% lead)
MMLU-Pro (Multi-Discipline)
91.8%
76.8%
Claude 4 Opus (+15.0% lead)
MATH-500 (Quantitative Logic)
98.1%
77%
Claude 4 Opus (+21.1% lead)
Inference Value Score (IVR)
43.6 / 100
74.6 / 100
Llama 3.3 70B Instruct (+31 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 4 Opus 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 $15.00/1M input ($75.00/1M output) for Claude 4 Opus.
Which model has lower TTFT latency and higher tok/s throughput: Claude 4 Opus 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 920ms TTFT (46 tok/s) for Claude 4 Opus.
How do Claude 4 Opus and Llama 3.3 70B Instruct compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Claude 4 Opus scores 77.2% versus 42.5% for Llama 3.3 70B Instruct. On GPQA Diamond graduate-level STEM reasoning, Claude 4 Opus scores 87.1% versus 55.6% for Llama 3.3 70B Instruct (and 98.1% vs 77% on MATH-500).
When should you choose Claude 4 Opus?
Choose Claude 4 Opus (Anthropic) for mission-critical R&D, long-horizon autonomous coding tasks, complex theorem proving, and executive strategic synthesis — offering a 204k context window, 920ms TTFT, and $15.00/1M input pricing ($1.500/1M 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).
