Which model is better: Mistral Large 2 (2411) or o1?
Mistral Large 2 (2411) is 86.7% cheaper for input tokens ($2.00 vs. $15.00 per 1M tokens) and $6.00 vs. $60.00 for output tokens (7.5x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (2220ms faster than o1) with 75 vs. 48 tok/s throughput. o1 leads coding evaluations at 48.9% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 78.0% 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)
o1
Net Delta / Advantage
Input Cost / 1M Tokens
$2.00
$15.00
Mistral Large 2 (2411) is 7.5x cheaper
Output Cost / 1M Tokens
$6.00
$60.00
Mistral Large 2 (2411) (90.0% lower)
Prompt Cache Read / 1M
$0.200
$7.500
Mistral Large 2 (2411) is 37.5x cheaper
Prompt Cache Write / 1M
$2.00
$15.00
Mistral Large 2 (2411) is 7.5x cheaper
Context Window (Max Output)
131k (8k out)
205k (100k out)
o1 (1.6x larger context)
Avg TTFT Response Latency
380ms
2600ms
Mistral Large 2 (2411) (2220ms faster)
Generation Speed (Throughput)
75 tok/s
48 tok/s
Mistral Large 2 (2411) (+27 tok/s faster)
SWE-bench Verified (Coding)
45.2%
48.9%
o1 (+3.7% lead)
GPQA Diamond (PhD STEM)
54.2%
78%
o1 (+23.8% lead)
MMLU-Pro (Multi-Discipline)
74.8%
83.3%
o1 (+8.5% lead)
MATH-500 (Quantitative Logic)
76.5%
96.4%
o1 (+19.9% lead)
Inference Value Score (IVR)
50.1 / 100
37.2 / 100
Mistral Large 2 (2411) (+12.9 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).
Mistral Large 2 (2411) is cheaper at $2.00/1M input tokens ($6.00/1M output) compared to $15.00/1M input ($60.00/1M output) for o1.
Which model has lower TTFT latency and higher tok/s throughput: Mistral Large 2 (2411) or o1?
Mistral Large 2 (2411) delivers faster first-token latency at 380ms TTFT (75 tok/s throughput) compared to 2600ms TTFT (48 tok/s) for o1.
How do Mistral Large 2 (2411) and o1 compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Mistral Large 2 (2411) scores 45.2% versus 48.9% for o1. On GPQA Diamond graduate-level STEM reasoning, Mistral Large 2 (2411) scores 54.2% versus 78% for o1 (and 76.5% vs 96.4% 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 o1?
Choose o1 (OpenAI) for legacy reasoning benchmarks, scientific literature review, and complex mathematical proofs — offering a 204k context window, 2600ms TTFT, and $15.00/1M input pricing ($7.500/1M cached reads).
