Which model is better: GPT-4o Mini or Mistral Large 2 (2411)?
GPT-4o Mini is 92.5% cheaper for input tokens ($0.15 vs. $2.00 per 1M tokens) and $0.60 vs. $6.00 for output tokens (13.3x cost advantage). In terms of operational performance, GPT-4o Mini delivers lower response latency at 220ms TTFT (160ms faster than Mistral Large 2 (2411)) with 140 vs. 75 tok/s throughput. Mistral Large 2 (2411) leads coding evaluations at 45.2% SWE-bench Verified vs. 41.0% for GPT-4o Mini and 54.2% vs. 40.2% 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-4o Mini
Mistral Large 2 (2411)
Net Delta / Advantage
Input Cost / 1M Tokens
$0.15
$2.00
GPT-4o Mini is 13.3x cheaper
Output Cost / 1M Tokens
$0.60
$6.00
GPT-4o Mini (90.0% lower)
Prompt Cache Read / 1M
$0.075
$0.200
GPT-4o Mini is 2.7x cheaper
Prompt Cache Write / 1M
$0.15
$2.00
GPT-4o Mini is 13.3x cheaper
Context Window (Max Output)
131k (16k out)
131k (8k out)
Equal Context Window
Avg TTFT Response Latency
220ms
380ms
GPT-4o Mini (160ms faster)
Generation Speed (Throughput)
140 tok/s
75 tok/s
GPT-4o Mini (+65 tok/s faster)
SWE-bench Verified (Coding)
41%
45.2%
Mistral Large 2 (2411) (+4.2% lead)
GPQA Diamond (PhD STEM)
40.2%
54.2%
Mistral Large 2 (2411) (+14.0% lead)
MMLU-Pro (Multi-Discipline)
68%
74.8%
Mistral Large 2 (2411) (+6.8% lead)
MATH-500 (Quantitative Logic)
70.2%
76.5%
Mistral Large 2 (2411) (+6.3% lead)
Inference Value Score (IVR)
67.2 / 100
50.1 / 100
GPT-4o Mini (+17.1 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: GPT-4o Mini or Mistral Large 2 (2411)?
GPT-4o Mini is cheaper at $0.15/1M input tokens ($0.60/1M 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: GPT-4o Mini or Mistral Large 2 (2411)?
GPT-4o Mini delivers faster first-token latency at 220ms TTFT (140 tok/s throughput) compared to 380ms TTFT (75 tok/s) for Mistral Large 2 (2411).
How do GPT-4o Mini and Mistral Large 2 (2411) compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GPT-4o Mini scores 41% versus 45.2% for Mistral Large 2 (2411). On GPQA Diamond graduate-level STEM reasoning, GPT-4o Mini scores 40.2% versus 54.2% for Mistral Large 2 (2411) (and 70.2% vs 76.5% on MATH-500).
When should you choose GPT-4o Mini?
Choose GPT-4o Mini (OpenAI) for high-volume classification, lightweight RAG chatbots, and structured JSON extraction — offering a 131k context window, 220ms TTFT, and $0.15/1M input pricing ($0.075/1M 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).
