💻 Coding (SWE) WinnerGPT-6.1 Sol 86.4% SWE-bench · 96.8% HumanEval
🧠 STEM Reasoning WinnerGPT-6.1 Sol 92.4% GPQA · 98.8% MATH-500
Which model is better: GPT-6.1 Sol or Mistral Large 2 (2411)?
GPT-6.1 Sol and Mistral Large 2 (2411) share identical input pricing at $2.00 per 1M tokens ($10.00 vs. $6.00 output). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (140ms faster than GPT-6.1 Sol) with 75 vs. 135 tok/s throughput. GPT-6.1 Sol leads coding evaluations at 86.4% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 92.4% 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
GPT-6.1 Sol
Mistral Large 2 (2411)
Net Delta / Advantage
Input Cost / 1M Tokens
$2.00
$2.00
Identical Pricing
Output Cost / 1M Tokens
$10.00
$6.00
Mistral Large 2 (2411) (40.0% lower)
Prompt Cache Read / 1M
$0.100
$0.200
GPT-6.1 Sol is 2.0x cheaper
Prompt Cache Write / 1M
$2.00
$2.00
Identical Cache Write Pricing
Context Window (Max Output)
1,075k (128k out)
131k (8k out)
GPT-6.1 Sol (8.2x larger context)
Avg TTFT Response Latency
520ms
380ms
Mistral Large 2 (2411) (140ms faster)
Generation Speed (Throughput)
135 tok/s
75 tok/s
GPT-6.1 Sol (+60 tok/s faster)
SWE-bench Verified (Coding)
86.4%
45.2%
GPT-6.1 Sol (+41.2% lead)
GPQA Diamond (PhD STEM)
92.4%
54.2%
GPT-6.1 Sol (+38.2% lead)
MMLU-Pro (Multi-Discipline)
91%
74.8%
GPT-6.1 Sol (+16.2% lead)
MATH-500 (Quantitative Logic)
98.8%
76.5%
GPT-6.1 Sol (+22.3% lead)
Inference Value Score (IVR)
62.9 / 100
50.1 / 100
GPT-6.1 Sol (+12.8 pts)
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Choose GPT-6.1 Sol (OpenAI) for delivers near-GPT-6 Astra frontier accuracy at one-fifth the token cost with a 95% cache read discount for high-efficiency agentic coding, computer use, and enterprise workflow automation — offering a 1,075k context window, 520ms TTFT, and $2.00/1M input pricing ($0.100/1M 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: GPT-6.1 Sol or Mistral Large 2 (2411)?
Both GPT-6.1 Sol and Mistral Large 2 (2411) share identical input pricing at $2.00/1M tokens.
Which model has lower TTFT latency and higher tok/s throughput: GPT-6.1 Sol 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 (135 tok/s) for GPT-6.1 Sol.
How do GPT-6.1 Sol and Mistral Large 2 (2411) compare on SWE-bench coding and GPQA Diamond reasoning?
On SWE-bench Verified software engineering, GPT-6.1 Sol scores 86.4% versus 45.2% for Mistral Large 2 (2411). On GPQA Diamond graduate-level STEM reasoning, GPT-6.1 Sol scores 92.4% versus 54.2% for Mistral Large 2 (2411) (and 98.8% vs 76.5% on MATH-500).
When should you choose GPT-6.1 Sol?
Choose GPT-6.1 Sol (OpenAI) for delivers near-GPT-6 Astra frontier accuracy at one-fifth the token cost with a 95% cache read discount for high-efficiency agentic coding, computer use, and enterprise workflow automation — offering a 1,075k context window, 520ms TTFT, and $2.00/1M input pricing ($0.100/1M 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).
