Which model is better: Mistral Large 2 (2411) or OpenAI o3-mini?
OpenAI o3-mini is 45.0% cheaper for input tokens ($1.10 vs. $2.00 per 1M tokens) and $4.40 vs. $6.00 for output tokens (1.8x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (570ms faster than OpenAI o3-mini) with 75 vs. 98 tok/s throughput. OpenAI o3-mini leads coding evaluations at 49.3% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 79.7% vs. 54.2% 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
Mistral Large 2 (2411)
OpenAI o3-mini
Net Delta / Advantage
Input Cost / 1M Tokens
$2.00
$1.10
OpenAI o3-mini is 1.8x cheaper
Output Cost / 1M Tokens
$6.00
$4.40
OpenAI o3-mini (26.7% lower)
Prompt Cache Read / 1M
$0.200
$0.550
Mistral Large 2 (2411) is 2.8x cheaper
Prompt Cache Write / 1M
$2.00
$1.10
OpenAI o3-mini is 1.8x cheaper
Context Window (Max Output)
131k (8k out)
205k (100k out)
OpenAI o3-mini (1.6x larger context)
Avg TTFT Response Latency
380ms
950ms
Mistral Large 2 (2411) (570ms faster)
Generation Speed (Throughput)
75 tok/s
98 tok/s
OpenAI o3-mini (+23 tok/s faster)
SWE-bench Verified (Coding)
45.2%
49.3%
OpenAI o3-mini (+4.1% lead)
GPQA Diamond (PhD STEM)
54.2%
79.7%
OpenAI o3-mini (+25.5% lead)
MMLU-Pro (Multi-Discipline)
74.8%
83.2%
OpenAI o3-mini (+8.4% lead)
MATH-500 (Quantitative Logic)
76.5%
97.9%
OpenAI o3-mini (+21.4% lead)
Inference Value Score (IVR)
50.1 / 100
59.7 / 100
OpenAI o3-mini (+9.6 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).
Choose OpenAI o3-mini (OpenAI) for competitive math reasoning, automated unit test generation, and structured logic pipelines — offering a 204k context window, 950ms TTFT, and $1.10/1M input pricing ($0.550/1M cached reads).
Which is cheaper: Mistral Large 2 (2411) or OpenAI o3-mini?
OpenAI o3-mini is cheaper at $1.10/1M input tokens ($4.40/1M 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: Mistral Large 2 (2411) or OpenAI o3-mini?
Mistral Large 2 (2411) delivers faster first-token latency at 380ms TTFT (75 tok/s throughput) compared to 950ms TTFT (98 tok/s) for OpenAI o3-mini.
How do Mistral Large 2 (2411) and OpenAI o3-mini compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Mistral Large 2 (2411) scores 45.2% versus 49.3% for OpenAI o3-mini. On GPQA Diamond graduate-level STEM reasoning, Mistral Large 2 (2411) scores 54.2% versus 79.7% for OpenAI o3-mini (and 76.5% vs 97.9% on MATH-500).
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).
When should you choose OpenAI o3-mini?
Choose OpenAI o3-mini (OpenAI) for competitive math reasoning, automated unit test generation, and structured logic pipelines — offering a 204k context window, 950ms TTFT, and $1.10/1M input pricing ($0.550/1M cached reads).
