Which model is better: DeepSeek V4 Pro or Mistral Large 2 (2411)?
DeepSeek V4 Pro is 34.0% cheaper for input tokens ($1.32 vs. $2.00 per 1M tokens) and $3.96 vs. $6.00 for output tokens (1.5x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (140ms faster than DeepSeek V4 Pro) with 75 vs. 78 tok/s throughput. DeepSeek V4 Pro leads coding evaluations at 80.6% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 90.1% 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
DeepSeek V4 Pro
Mistral Large 2 (2411)
Net Delta / Advantage
Input Cost / 1M Tokens
$1.32
$2.00
DeepSeek V4 Pro is 1.5x cheaper
Output Cost / 1M Tokens
$3.96
$6.00
DeepSeek V4 Pro (34.0% lower)
Prompt Cache Read / 1M
$0.145
$0.200
DeepSeek V4 Pro is 1.4x cheaper
Prompt Cache Write / 1M
$1.32
$2.00
DeepSeek V4 Pro is 1.5x cheaper
Context Window (Max Output)
1,024k (128k out)
131k (8k out)
DeepSeek V4 Pro (7.8x larger context)
Avg TTFT Response Latency
520ms
380ms
Mistral Large 2 (2411) (140ms faster)
Generation Speed (Throughput)
78 tok/s
75 tok/s
DeepSeek V4 Pro (+3 tok/s faster)
SWE-bench Verified (Coding)
80.6%
45.2%
DeepSeek V4 Pro (+35.4% lead)
GPQA Diamond (PhD STEM)
90.1%
54.2%
DeepSeek V4 Pro (+35.9% lead)
MMLU-Pro (Multi-Discipline)
88.4%
74.8%
DeepSeek V4 Pro (+13.6% lead)
MATH-500 (Quantitative Logic)
97.3%
76.5%
DeepSeek V4 Pro (+20.8% lead)
Inference Value Score (IVR)
67 / 100
50.1 / 100
DeepSeek V4 Pro (+16.9 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).
Which is cheaper: DeepSeek V4 Pro or Mistral Large 2 (2411)?
DeepSeek V4 Pro is cheaper at $1.32/1M input tokens ($3.96/1M 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: DeepSeek V4 Pro or Mistral Large 2 (2411)?
Mistral Large 2 (2411) delivers faster first-token latency at 380ms TTFT (75 tok/s throughput) compared to 520ms TTFT (78 tok/s) for DeepSeek V4 Pro.
How do DeepSeek V4 Pro and Mistral Large 2 (2411) compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek V4 Pro scores 80.6% versus 45.2% for Mistral Large 2 (2411). On GPQA Diamond graduate-level STEM reasoning, DeepSeek V4 Pro scores 90.1% versus 54.2% for Mistral Large 2 (2411) (and 97.3% vs 76.5% on MATH-500).
When should you choose DeepSeek V4 Pro?
Choose DeepSeek V4 Pro (DeepSeek) for open-weight 1.6T MoE powerhouse designed for cost-effective full-repository code generation, mathematical reasoning, and persistent chain-of-thought multi-step agent workflows — offering a 1,024k context window, 520ms TTFT, and $1.32/1M input pricing ($0.145/1M 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).
