Which model is better: DeepSeek V3 or Mistral Large 2 (2411)?
DeepSeek V3 is 93.0% cheaper for input tokens ($0.14 vs. $2.00 per 1M tokens) and $0.28 vs. $6.00 for output tokens (14.3x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (30ms faster than DeepSeek V3) with 75 vs. 78 tok/s throughput. Mistral Large 2 (2411) leads coding evaluations at 45.2% SWE-bench Verified vs. 42.0% for DeepSeek V3 and 54.2% vs. 59.1% 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 V3
Mistral Large 2 (2411)
Net Delta / Advantage
Input Cost / 1M Tokens
$0.14
$2.00
DeepSeek V3 is 14.3x cheaper
Output Cost / 1M Tokens
$0.28
$6.00
DeepSeek V3 (95.3% lower)
Prompt Cache Read / 1M
$0.014
$0.200
DeepSeek V3 is 14.3x cheaper
Prompt Cache Write / 1M
$0.14
$2.00
DeepSeek V3 is 14.3x cheaper
Context Window (Max Output)
131k (8k out)
131k (8k out)
Equal Context Window
Avg TTFT Response Latency
410ms
380ms
Mistral Large 2 (2411) (30ms faster)
Generation Speed (Throughput)
78 tok/s
75 tok/s
DeepSeek V3 (+3 tok/s faster)
SWE-bench Verified (Coding)
42%
45.2%
Mistral Large 2 (2411) (+3.2% lead)
GPQA Diamond (PhD STEM)
59.1%
54.2%
DeepSeek V3 (+4.9% lead)
MMLU-Pro (Multi-Discipline)
75.9%
74.8%
DeepSeek V3 (+1.1% lead)
MATH-500 (Quantitative Logic)
90.2%
76.5%
DeepSeek V3 (+13.7% lead)
Inference Value Score (IVR)
75 / 100
50.1 / 100
DeepSeek V3 (+24.9 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 V3 or Mistral Large 2 (2411)?
DeepSeek V3 is cheaper at $0.14/1M input tokens ($0.28/1M 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 V3 or Mistral Large 2 (2411)?
Mistral Large 2 (2411) delivers faster first-token latency at 380ms TTFT (75 tok/s throughput) compared to 410ms TTFT (78 tok/s) for DeepSeek V3.
How do DeepSeek V3 and Mistral Large 2 (2411) compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, DeepSeek V3 scores 42% versus 45.2% for Mistral Large 2 (2411). On GPQA Diamond graduate-level STEM reasoning, DeepSeek V3 scores 59.1% versus 54.2% for Mistral Large 2 (2411) (and 90.2% vs 76.5% on MATH-500).
When should you choose DeepSeek V3?
Choose DeepSeek V3 (DeepSeek) for cost-sensitive batch text processing, drafting, and open-weight self-hosted inference — offering a 131k context window, 410ms TTFT, and $0.14/1M input pricing ($0.014/1M 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).
