Which model is better: Llama 3.3 70B Instruct or Mistral Large 2 (2411)?
Llama 3.3 70B Instruct is 94.0% cheaper for input tokens ($0.12 vs. $2.00 per 1M tokens) and $0.30 vs. $6.00 for output tokens (16.7x cost advantage). In terms of operational performance, Llama 3.3 70B Instruct delivers lower response latency at 145ms TTFT (235ms faster than Mistral Large 2 (2411)) with 165 vs. 75 tok/s throughput. Mistral Large 2 (2411) leads coding evaluations at 45.2% SWE-bench Verified vs. 42.5% for Llama 3.3 70B Instruct and 54.2% 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
Mistral Large 2 (2411)
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
$6.00
Llama 3.3 70B Instruct (95.0% lower)
Prompt Cache Read / 1M
$0.030
$0.200
Llama 3.3 70B Instruct is 6.7x 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)
131k (8k out)
Equal Context Window
Avg TTFT Response Latency
145ms
380ms
Llama 3.3 70B Instruct (235ms faster)
Generation Speed (Throughput)
165 tok/s
75 tok/s
Llama 3.3 70B Instruct (+90 tok/s faster)
SWE-bench Verified (Coding)
42.5%
45.2%
Mistral Large 2 (2411) (+2.7% lead)
GPQA Diamond (PhD STEM)
55.6%
54.2%
Llama 3.3 70B Instruct (+1.4% lead)
MMLU-Pro (Multi-Discipline)
76.8%
74.8%
Llama 3.3 70B Instruct (+2.0% lead)
MATH-500 (Quantitative Logic)
77%
76.5%
Llama 3.3 70B Instruct (+0.5% lead)
Inference Value Score (IVR)
74.6 / 100
50.1 / 100
Llama 3.3 70B Instruct (+24.5 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose Mistral Large 2 (2411) (Mistral AI) for sovereign enterprise multilingual flagship tuned for reasoning, strict JSON schemas, and European regulatory compliance — offering a 131k context window, 380ms TTFT, and $2.00/1M input pricing ($0.200/1M cached reads).
Which is cheaper: Llama 3.3 70B Instruct or Mistral Large 2 (2411)?
Llama 3.3 70B Instruct is cheaper at $0.12/1M input tokens ($0.30/1M output) compared to $2.00/1M input ($6.00/1M output) for Mistral Large 2 (2411).
Which model has lower TTFT latency and higher tok/s throughput: Llama 3.3 70B Instruct or Mistral Large 2 (2411)?
Llama 3.3 70B Instruct delivers faster first-token latency at 145ms TTFT (165 tok/s throughput) compared to 380ms TTFT (75 tok/s) for Mistral Large 2 (2411).
How do Llama 3.3 70B Instruct and Mistral Large 2 (2411) compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Llama 3.3 70B Instruct scores 42.5% versus 45.2% for Mistral Large 2 (2411). On GPQA Diamond graduate-level STEM reasoning, Llama 3.3 70B Instruct scores 55.6% versus 54.2% for Mistral Large 2 (2411) (and 77% vs 76.5% 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 Mistral Large 2 (2411)?
Choose Mistral Large 2 (2411) (Mistral AI) for sovereign enterprise multilingual flagship tuned for reasoning, strict JSON schemas, and European regulatory compliance — offering a 131k context window, 380ms TTFT, and $2.00/1M input pricing ($0.200/1M cached reads).
