Which model is better: Gemini 3.8 Flash or Mistral Large 2 (2411)?
Gemini 3.8 Flash is 87.5% cheaper for input tokens ($0.25 vs. $2.00 per 1M tokens) and $1.50 vs. $6.00 for output tokens (8.0x cost advantage). In terms of operational performance, Gemini 3.8 Flash delivers lower response latency at 105ms TTFT (275ms faster than Mistral Large 2 (2411)) with 210 vs. 75 tok/s throughput. Gemini 3.8 Flash leads coding evaluations at 68.5% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 79.2% 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
Gemini 3.8 Flash
Mistral Large 2 (2411)
Net Delta / Advantage
Input Cost / 1M Tokens
$0.25
$2.00
Gemini 3.8 Flash is 8.0x cheaper
Output Cost / 1M Tokens
$1.50
$6.00
Gemini 3.8 Flash (75.0% lower)
Prompt Cache Read / 1M
$0.025
$0.200
Gemini 3.8 Flash is 8.0x cheaper
Prompt Cache Write / 1M
$0.25
$2.00
Gemini 3.8 Flash is 8.0x cheaper
Context Window (Max Output)
1,049k (66k out)
131k (8k out)
Gemini 3.8 Flash (8.0x larger context)
Avg TTFT Response Latency
105ms
380ms
Gemini 3.8 Flash (275ms faster)
Generation Speed (Throughput)
210 tok/s
75 tok/s
Gemini 3.8 Flash (+135 tok/s faster)
SWE-bench Verified (Coding)
68.5%
45.2%
Gemini 3.8 Flash (+23.3% lead)
GPQA Diamond (PhD STEM)
79.2%
54.2%
Gemini 3.8 Flash (+25.0% lead)
MMLU-Pro (Multi-Discipline)
87.4%
74.8%
Gemini 3.8 Flash (+12.6% lead)
MATH-500 (Quantitative Logic)
95.1%
76.5%
Gemini 3.8 Flash (+18.6% lead)
Inference Value Score (IVR)
74 / 100
50.1 / 100
Gemini 3.8 Flash (+23.9 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose Gemini 3.8 Flash (Google) for high-throughput agentic workflows, real-time multimodal RAG, live search grounding, and production code generation at flash unit economics — offering a 1,048k context window, 105ms TTFT, and $0.25/1M input pricing ($0.025/1M cached reads).
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: Gemini 3.8 Flash or Mistral Large 2 (2411)?
Gemini 3.8 Flash is cheaper at $0.25/1M input tokens ($1.50/1M 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: Gemini 3.8 Flash or Mistral Large 2 (2411)?
Gemini 3.8 Flash delivers faster first-token latency at 105ms TTFT (210 tok/s throughput) compared to 380ms TTFT (75 tok/s) for Mistral Large 2 (2411).
How do Gemini 3.8 Flash and Mistral Large 2 (2411) compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, Gemini 3.8 Flash scores 68.5% versus 45.2% for Mistral Large 2 (2411). On GPQA Diamond graduate-level STEM reasoning, Gemini 3.8 Flash scores 79.2% versus 54.2% for Mistral Large 2 (2411) (and 95.1% vs 76.5% on MATH-500).
When should you choose Gemini 3.8 Flash?
Choose Gemini 3.8 Flash (Google) for high-throughput agentic workflows, real-time multimodal RAG, live search grounding, and production code generation at flash unit economics — offering a 1,048k context window, 105ms TTFT, and $0.25/1M input pricing ($0.025/1M 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).
