Which model is better: Claude 4 Opus or Mistral Large 2 (2411)?
Mistral Large 2 (2411) is 86.7% cheaper for input tokens ($2.00 vs. $15.00 per 1M tokens) and $6.00 vs. $75.00 for output tokens (7.5x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (540ms faster than Claude 4 Opus) with 75 vs. 46 tok/s throughput. Claude 4 Opus leads coding evaluations at 77.2% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 87.1% 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
Claude 4 Opus
Mistral Large 2 (2411)
Net Delta / Advantage
Input Cost / 1M Tokens
$15.00
$2.00
Mistral Large 2 (2411) is 7.5x cheaper
Output Cost / 1M Tokens
$75.00
$6.00
Mistral Large 2 (2411) (92.0% lower)
Prompt Cache Read / 1M
$1.500
$0.200
Mistral Large 2 (2411) is 7.5x cheaper
Prompt Cache Write / 1M
$18.75
$2.00
Mistral Large 2 (2411) is 9.4x cheaper
Context Window (Max Output)
205k (64k out)
131k (8k out)
Claude 4 Opus (1.6x larger context)
Avg TTFT Response Latency
920ms
380ms
Mistral Large 2 (2411) (540ms faster)
Generation Speed (Throughput)
46 tok/s
75 tok/s
Mistral Large 2 (2411) (+29 tok/s faster)
SWE-bench Verified (Coding)
77.2%
45.2%
Claude 4 Opus (+32.0% lead)
GPQA Diamond (PhD STEM)
87.1%
54.2%
Claude 4 Opus (+32.9% lead)
MMLU-Pro (Multi-Discipline)
91.8%
74.8%
Claude 4 Opus (+17.0% lead)
MATH-500 (Quantitative Logic)
98.1%
76.5%
Claude 4 Opus (+21.6% lead)
Inference Value Score (IVR)
43.6 / 100
50.1 / 100
Mistral Large 2 (2411) (+6.5 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: Claude 4 Opus or Mistral Large 2 (2411)?
Mistral Large 2 (2411) is cheaper at $2.00/1M input tokens ($6.00/1M output) compared to $15.00/1M input ($75.00/1M output) for Claude 4 Opus.
Which model has lower TTFT latency and higher tok/s throughput: Claude 4 Opus or Mistral Large 2 (2411)?
Mistral Large 2 (2411) delivers faster first-token latency at 380ms TTFT (75 tok/s throughput) compared to 920ms TTFT (46 tok/s) for Claude 4 Opus.
How do Claude 4 Opus and Mistral Large 2 (2411) compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Claude 4 Opus scores 77.2% versus 45.2% for Mistral Large 2 (2411). On GPQA Diamond graduate-level STEM reasoning, Claude 4 Opus scores 87.1% versus 54.2% for Mistral Large 2 (2411) (and 98.1% vs 76.5% on MATH-500).
When should you choose Claude 4 Opus?
Choose Claude 4 Opus (Anthropic) for mission-critical R&D, long-horizon autonomous coding tasks, complex theorem proving, and executive strategic synthesis — offering a 204k context window, 920ms TTFT, and $15.00/1M input pricing ($1.500/1M 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).
