Which model is better: GPT-5 or Llama 3.3 70B Instruct?
Llama 3.3 70B Instruct is 95.2% cheaper for input tokens ($0.12 vs. $2.50 per 1M tokens) and $0.30 vs. $10.00 for output tokens (20.8x cost advantage). In terms of operational performance, Llama 3.3 70B Instruct delivers lower response latency at 145ms TTFT (195ms faster than GPT-5) with 165 vs. 105 tok/s throughput. GPT-5 leads coding evaluations at 74.9% SWE-bench Verified vs. 42.5% for Llama 3.3 70B Instruct and 85.4% 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
GPT-5
Llama 3.3 70B Instruct
Net Delta / Advantage
Input Cost / 1M Tokens
$2.50
$0.12
Llama 3.3 70B Instruct is 20.8x cheaper
Output Cost / 1M Tokens
$10.00
$0.30
Llama 3.3 70B Instruct (97.0% lower)
Prompt Cache Read / 1M
$0.625
$0.030
Llama 3.3 70B Instruct is 20.8x cheaper
Prompt Cache Write / 1M
$2.50
$0.12
Llama 3.3 70B Instruct is 20.8x cheaper
Context Window (Max Output)
410k (128k out)
131k (33k out)
GPT-5 (3.1x larger context)
Avg TTFT Response Latency
340ms
145ms
Llama 3.3 70B Instruct (195ms faster)
Generation Speed (Throughput)
105 tok/s
165 tok/s
Llama 3.3 70B Instruct (+60 tok/s faster)
SWE-bench Verified (Coding)
74.9%
42.5%
GPT-5 (+32.4% lead)
GPQA Diamond (PhD STEM)
85.4%
55.6%
GPT-5 (+29.8% lead)
MMLU-Pro (Multi-Discipline)
90.8%
76.8%
GPT-5 (+14.0% lead)
MATH-500 (Quantitative Logic)
98%
77%
GPT-5 (+21.0% lead)
Inference Value Score (IVR)
59.2 / 100
74.6 / 100
Llama 3.3 70B Instruct (+15.4 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: GPT-5 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 $2.50/1M input ($10.00/1M output) for GPT-5.
Which model has lower TTFT latency and higher tok/s throughput: GPT-5 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 340ms TTFT (105 tok/s) for GPT-5.
How do GPT-5 and Llama 3.3 70B Instruct compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GPT-5 scores 74.9% versus 42.5% for Llama 3.3 70B Instruct. On GPQA Diamond graduate-level STEM reasoning, GPT-5 scores 85.4% versus 55.6% for Llama 3.3 70B Instruct (and 98% vs 77% on MATH-500).
When should you choose GPT-5?
Choose GPT-5 (OpenAI) for complex enterprise automation, full-stack software engineering, multimodal agent orchestration, and scientific synthesis — offering a 409k context window, 340ms TTFT, and $2.50/1M input pricing ($0.625/1M 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).
