Mistral Large 2 (2411)
Mistral Commercial LicenseDeveloped by Mistral AI · Dense Transformer · Modalities: Text · Released 2024-11-18
What are the token costs and operational benchmarks for Mistral Large 2 (2411)?
Verified Capability Benchmarks
Composite Intelligence: 60.7/100Architectural & Production Profile
European data-sovereign 123B enterprise flagship tuned for multilingual accuracy, strict JSON schemas, and EU regulatory compliance.
Sovereign enterprise multilingual flagship tuned for reasoning, strict JSON schemas, and European regulatory compliance.
- Architecture
- Dense Transformer
- Modalities
- Text
- Max Output Tokens
- 8,192 tokens
- Blended Rate (3:1)
- $3.000 / 1M
Interactive Monthly Token Economics & ROI Forecaster
Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.
Estimated Monthly Spend
$2.00/1M in · $6.00/1M out
Prompt Cache: $0.200/1M read · $2.00/1M write
$2.00/1M in · $10.00/1M out
Prompt Cache: $0.100/1M read · $0.50/1M write
Head-to-Head Comparisons Involving Mistral Large 2 (2411) (36)
Mistral Large 2 (2411) vs Gemini 4 Argon
Gemini 4 Argon 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 (470ms faster than Gemini 4 Argon) with 75 vs. 115 tok/s throughput. Gemini 4 Argon leads coding evaluations at 84.5% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 93.8% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Claude 4.5 Sonnet
Mistral Large 2 (2411) is 33.3% cheaper for input tokens ($2.00 vs. $3.00 per 1M tokens) and $6.00 vs. $15.00 for output tokens (1.5x cost advantage). In terms of operational performance, Both models demonstrate comparable response latency around 380ms TTFT (84 vs. 75 tok/s). Claude 4.5 Sonnet leads coding evaluations at 75.8% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 84.2% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Claude Opus 5.5
Mistral Large 2 (2411) is 50.0% cheaper for input tokens ($2.00 vs. $4.00 per 1M tokens) and $6.00 vs. $20.00 for output tokens (2.0x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (300ms faster than Claude Opus 5.5) with 75 vs. 95 tok/s throughput. Claude Opus 5.5 leads coding evaluations at 89.9% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 93.2% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Gemini 3.8 Flash
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.
Mistral Large 2 (2411) vs GPT-5
Mistral Large 2 (2411) is 20.0% cheaper for input tokens ($2.00 vs. $2.50 per 1M tokens) and $6.00 vs. $10.00 for output tokens (1.2x cost advantage). In terms of operational performance, GPT-5 delivers lower response latency at 340ms TTFT (40ms faster than Mistral Large 2 (2411)) with 105 vs. 75 tok/s throughput. GPT-5 leads coding evaluations at 74.9% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 85.4% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs GPT-6 Astra
Mistral Large 2 (2411) is 80.0% cheaper for input tokens ($2.00 vs. $10.00 per 1M tokens) and $6.00 vs. $50.00 for output tokens (5.0x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (360ms faster than GPT-6 Astra) with 75 vs. 74 tok/s throughput. GPT-6 Astra leads coding evaluations at 75.7% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 96.0% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs DeepSeek V4 Pro
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.
Mistral Large 2 (2411) vs DeepSeek R1
DeepSeek R1 is 72.5% cheaper for input tokens ($0.55 vs. $2.00 per 1M tokens) and $2.19 vs. $6.00 for output tokens (3.6x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (1070ms faster than DeepSeek R1) with 75 vs. 58 tok/s throughput. DeepSeek R1 leads coding evaluations at 49.2% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 71.5% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs DeepSeek V4 Flash Vision (Exp)
DeepSeek V4 Flash Vision (Exp) is 89.0% cheaper for input tokens ($0.22 vs. $2.00 per 1M tokens) and $0.65 vs. $6.00 for output tokens (9.1x cost advantage). In terms of operational performance, DeepSeek V4 Flash Vision (Exp) delivers lower response latency at 310ms TTFT (70ms faster than Mistral Large 2 (2411)) with 165 vs. 75 tok/s throughput. DeepSeek V4 Flash Vision (Exp) leads coding evaluations at 77.4% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 91.3% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs OpenAI o3
Mistral Large 2 (2411) and OpenAI o3 share identical input pricing at $2.00 per 1M tokens ($6.00 vs. $8.00 output). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (770ms faster than OpenAI o3) with 75 vs. 82 tok/s throughput. OpenAI o3 leads coding evaluations at 71.7% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 87.7% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Claude 4 Opus
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.
Mistral Large 2 (2411) vs Claude 3.7 Sonnet
Mistral Large 2 (2411) is 33.3% cheaper for input tokens ($2.00 vs. $3.00 per 1M tokens) and $6.00 vs. $15.00 for output tokens (1.5x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (160ms faster than Claude 3.7 Sonnet) with 75 vs. 72 tok/s throughput. Claude 3.7 Sonnet leads coding evaluations at 70.3% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 78.5% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Gemini 3.1 Pro
Gemini 3.1 Pro is 37.5% cheaper for input tokens ($1.25 vs. $2.00 per 1M tokens) and $10.00 vs. $6.00 for output tokens (1.6x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (40ms faster than Gemini 3.1 Pro) with 75 vs. 98 tok/s throughput. Gemini 3.1 Pro leads coding evaluations at 71.8% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 82.4% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Grok 4
Mistral Large 2 (2411) is 20.0% cheaper for input tokens ($2.00 vs. $2.50 per 1M tokens) and $6.00 vs. $12.50 for output tokens (1.2x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (100ms faster than Grok 4) with 75 vs. 95 tok/s throughput. Grok 4 leads coding evaluations at 73.2% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 86.2% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Llama 4 Maverick
Llama 4 Maverick is 90.0% cheaper for input tokens ($0.20 vs. $2.00 per 1M tokens) and $0.60 vs. $6.00 for output tokens (10.0x cost advantage). In terms of operational performance, Llama 4 Maverick delivers lower response latency at 135ms TTFT (245ms faster than Mistral Large 2 (2411)) with 175 vs. 75 tok/s throughput. Llama 4 Maverick leads coding evaluations at 62.4% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 73.8% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Qwen 3.8 Flash Next
Qwen 3.8 Flash Next is 92.0% cheaper for input tokens ($0.16 vs. $2.00 per 1M tokens) and $0.47 vs. $6.00 for output tokens (12.5x cost advantage). In terms of operational performance, Qwen 3.8 Flash Next delivers lower response latency at 280ms TTFT (100ms faster than Mistral Large 2 (2411)) with 185 vs. 75 tok/s throughput. Qwen 3.8 Flash Next leads coding evaluations at 81.0% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 91.7% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Gemini 3.5 Flash-Lite
Gemini 3.5 Flash-Lite is 96.2% cheaper for input tokens ($0.07 vs. $2.00 per 1M tokens) and $0.30 vs. $6.00 for output tokens (26.7x cost advantage). In terms of operational performance, Gemini 3.5 Flash-Lite delivers lower response latency at 78ms TTFT (302ms faster than Mistral Large 2 (2411)) with 265 vs. 75 tok/s throughput. Gemini 3.5 Flash-Lite leads coding evaluations at 55.4% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 68.4% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs OpenAI o4-mini
OpenAI o4-mini is 45.0% cheaper for input tokens ($1.10 vs. $2.00 per 1M tokens) and $4.40 vs. $6.00 for output tokens (1.8x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (300ms faster than OpenAI o4-mini) with 75 vs. 125 tok/s throughput. OpenAI o4-mini leads coding evaluations at 68.1% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 81.4% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs DeepSeek V3
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.
Mistral Large 2 (2411) vs Gemma 4 31B IT
Gemma 4 31B IT is 94.0% cheaper for input tokens ($0.12 vs. $2.00 per 1M tokens) and $0.36 vs. $6.00 for output tokens (16.7x cost advantage). In terms of operational performance, Gemma 4 31B IT delivers lower response latency at 115ms TTFT (265ms faster than Mistral Large 2 (2411)) with 155 vs. 75 tok/s throughput. Gemma 4 31B IT leads coding evaluations at 59.2% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 71.2% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs OpenAI o3-mini
OpenAI o3-mini is 45.0% cheaper for input tokens ($1.10 vs. $2.00 per 1M tokens) and $4.40 vs. $6.00 for output tokens (1.8x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (570ms faster than OpenAI o3-mini) with 75 vs. 98 tok/s throughput. OpenAI o3-mini leads coding evaluations at 49.3% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 79.7% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Claude 3.5 Haiku
Claude 3.5 Haiku is 60.0% cheaper for input tokens ($0.80 vs. $2.00 per 1M tokens) and $4.00 vs. $6.00 for output tokens (2.5x cost advantage). In terms of operational performance, Claude 3.5 Haiku delivers lower response latency at 190ms TTFT (190ms faster than Mistral Large 2 (2411)) with 130 vs. 75 tok/s throughput. Mistral Large 2 (2411) leads coding evaluations at 45.2% SWE-bench Verified vs. 40.6% for Claude 3.5 Haiku and 54.2% vs. 41.6% on GPQA Diamond.
Mistral Large 2 (2411) vs Claude 3.5 Sonnet
Mistral Large 2 (2411) is 33.3% cheaper for input tokens ($2.00 vs. $3.00 per 1M tokens) and $6.00 vs. $15.00 for output tokens (1.5x cost advantage). In terms of operational performance, Claude 3.5 Sonnet delivers lower response latency at 310ms TTFT (70ms faster than Mistral Large 2 (2411)) with 80 vs. 75 tok/s throughput. Claude 3.5 Sonnet leads coding evaluations at 49.0% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 59.4% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Gemini 2.0 Flash
Gemini 2.0 Flash is 95.0% cheaper for input tokens ($0.10 vs. $2.00 per 1M tokens) and $0.40 vs. $6.00 for output tokens (20.0x cost advantage). In terms of operational performance, Gemini 2.0 Flash delivers lower response latency at 280ms TTFT (100ms faster than Mistral Large 2 (2411)) with 185 vs. 75 tok/s throughput. Gemini 2.0 Flash leads coding evaluations at 51.8% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 63.6% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Gemini 2.5 Flash
Gemini 2.5 Flash is 85.0% cheaper for input tokens ($0.30 vs. $2.00 per 1M tokens) and $2.50 vs. $6.00 for output tokens (6.7x cost advantage). In terms of operational performance, Gemini 2.5 Flash delivers lower response latency at 110ms TTFT (270ms faster than Mistral Large 2 (2411)) with 180 vs. 75 tok/s throughput. Gemini 2.5 Flash leads coding evaluations at 58.0% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 70.5% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Gemini 2.5 Pro
Gemini 2.5 Pro is 37.5% cheaper for input tokens ($1.25 vs. $2.00 per 1M tokens) and $10.00 vs. $6.00 for output tokens (1.6x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (320ms faster than Gemini 2.5 Pro) with 75 vs. 80 tok/s throughput. Gemini 2.5 Pro leads coding evaluations at 63.8% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 74.0% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs GLM-5.3-Flash
GLM-5.3-Flash is 94.0% cheaper for input tokens ($0.12 vs. $2.00 per 1M tokens) and $0.40 vs. $6.00 for output tokens (16.7x cost advantage). In terms of operational performance, GLM-5.3-Flash delivers lower response latency at 90ms TTFT (290ms faster than Mistral Large 2 (2411)) with 175 vs. 75 tok/s throughput. GLM-5.3-Flash leads coding evaluations at 52.8% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 63.5% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs GLM-5.3
GLM-5.3 is 82.5% cheaper for input tokens ($0.35 vs. $2.00 per 1M tokens) and $1.00 vs. $6.00 for output tokens (5.7x cost advantage). In terms of operational performance, GLM-5.3 delivers lower response latency at 160ms TTFT (220ms faster than Mistral Large 2 (2411)) with 120 vs. 75 tok/s throughput. GLM-5.3 leads coding evaluations at 56.0% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 67.0% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs GPT-4o Mini
GPT-4o Mini is 92.5% cheaper for input tokens ($0.15 vs. $2.00 per 1M tokens) and $0.60 vs. $6.00 for output tokens (13.3x cost advantage). In terms of operational performance, GPT-4o Mini delivers lower response latency at 220ms TTFT (160ms faster than Mistral Large 2 (2411)) with 140 vs. 75 tok/s throughput. Mistral Large 2 (2411) leads coding evaluations at 45.2% SWE-bench Verified vs. 41.0% for GPT-4o Mini and 54.2% vs. 40.2% on GPQA Diamond.
Mistral Large 2 (2411) vs GPT-4o
Mistral Large 2 (2411) is 20.0% cheaper for input tokens ($2.00 vs. $2.50 per 1M tokens) and $6.00 vs. $10.00 for output tokens (1.2x cost advantage). In terms of operational performance, GPT-4o delivers lower response latency at 280ms TTFT (100ms faster than Mistral Large 2 (2411)) with 100 vs. 75 tok/s throughput. GPT-4o leads coding evaluations at 48.0% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 53.6% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs GPT-6.1 Sol
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.
Mistral Large 2 (2411) vs Grok 3 Mini
Grok 3 Mini is 85.0% cheaper for input tokens ($0.30 vs. $2.00 per 1M tokens) and $1.20 vs. $6.00 for output tokens (6.7x cost advantage). In terms of operational performance, Grok 3 Mini delivers lower response latency at 150ms TTFT (230ms faster than Mistral Large 2 (2411)) with 160 vs. 75 tok/s throughput. Grok 3 Mini leads coding evaluations at 54.0% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 68.0% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Grok 3
Mistral Large 2 (2411) is 33.3% cheaper for input tokens ($2.00 vs. $3.00 per 1M tokens) and $6.00 vs. $15.00 for output tokens (1.5x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (240ms faster than Grok 3) with 75 vs. 88 tok/s throughput. Grok 3 leads coding evaluations at 65.8% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 84.6% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Llama 3.3 70B Instruct
Llama 3.3 70B Instruct is 94.0% cheaper for input tokens ($0.12 vs. $2.00 per 1M tokens) and $0.30 vs. $6.00 for output tokens (16.7x cost advantage). In terms of operational performance, Llama 3.3 70B Instruct delivers lower response latency at 145ms TTFT (235ms faster than Mistral Large 2 (2411)) with 165 vs. 75 tok/s throughput. Mistral Large 2 (2411) leads coding evaluations at 45.2% SWE-bench Verified vs. 42.5% for Llama 3.3 70B Instruct and 54.2% vs. 55.6% on GPQA Diamond.
Mistral Large 2 (2411) vs o1
Mistral Large 2 (2411) is 86.7% cheaper for input tokens ($2.00 vs. $15.00 per 1M tokens) and $6.00 vs. $60.00 for output tokens (7.5x cost advantage). In terms of operational performance, Mistral Large 2 (2411) delivers lower response latency at 380ms TTFT (2220ms faster than o1) with 75 vs. 48 tok/s throughput. o1 leads coding evaluations at 48.9% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 78.0% vs. 54.2% on GPQA Diamond.
Mistral Large 2 (2411) vs Qwen 3.8 27B
Qwen 3.8 27B is 90.0% cheaper for input tokens ($0.20 vs. $2.00 per 1M tokens) and $0.60 vs. $6.00 for output tokens (10.0x cost advantage). In terms of operational performance, Qwen 3.8 27B delivers lower response latency at 120ms TTFT (260ms faster than Mistral Large 2 (2411)) with 140 vs. 75 tok/s throughput. Qwen 3.8 27B leads coding evaluations at 58.4% SWE-bench Verified vs. 45.2% for Mistral Large 2 (2411) and 68.0% vs. 54.2% on GPQA Diamond.
Frequently Asked Questions & Query Fan-Out
How much does Mistral Large 2 (2411) cost per 1M tokens including prompt caching?
Mistral Large 2 (2411) costs $2.00 per million input tokens and $6.00 per million output tokens. Cached input reads cost $0.200 per 1M tokens, reducing repeated context costs by 90%.
What are Mistral Large 2 (2411)'s coding and reasoning benchmark scores?
Mistral Large 2 (2411) achieves 45.2% on SWE-bench Verified, 88.5% on HumanEval coding, 54.2% on GPQA Diamond graduate-level science, 74.8% on MMLU-Pro, and 76.5% on MATH-500, earning an overall Inference Value Ratio (IVR) of 50.1/100.
What is the context window, TTFT latency, and token throughput of Mistral Large 2 (2411)?
Mistral Large 2 (2411) supports a 131,072 token context window (8,192 max output tokens) and operates at 380ms average Time to First Token (TTFT) with 75 tokens/sec output streaming throughput.
What are the primary production use cases for Mistral Large 2 (2411)?
Sovereign enterprise multilingual flagship tuned for reasoning, strict JSON schemas, and European regulatory compliance.