| { |
| "title": "LLM Model Comparison for Enterprise Use Cases (2026)", |
| "version": "Q1 2026 v2", |
| "lastUpdated": "2026-02-18", |
| "license": "CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)", |
| "publisher": "Salt Technologies AI (https://www.salttechno.ai)", |
| "methodology": "This dataset combines three categories of data. (1) Specifications and pricing: sourced directly from official provider documentation and API pricing pages as of February 2026. Pricing reflects pay-as-you-go API rates in USD; volume discounts, committed-use pricing, and prompt caching discounts are excluded. Open-source model pricing reflects median costs across major inference providers (Together AI, Groq, Fireworks AI, DeepInfra). (2) Benchmark scores: MMLU, HumanEval, MATH, and MT-Bench scores are taken from the original model papers, provider-published technical reports, or verified third-party evaluations (LMSYS Chatbot Arena, Stanford HELM, Artificial Analysis). Where multiple evaluations exist, we use the official provider-reported score. Null values indicate that the provider has not published a verified score for that benchmark. (3) Latency and throughput: time-to-first-token (TTFT) and throughput (tokens per second) are measured using standardized prompts (500-token input, 200-token output) against each provider's production API endpoint from US-East regions. Measurements represent the median of 100 sequential requests during off-peak hours. Self-hosted and inference-provider latency varies by hardware and provider; ranges shown reflect typical deployments on H100/H200 GPUs. API feature flags (function calling, JSON mode, streaming, fine-tuning) reflect documented GA features as of the dataset date.", |
| "schema": { |
| "model": { "type": "string", "description": "Model name" }, |
| "provider": { "type": "string", "description": "Company that created/offers the model" }, |
| "parametersBillions": { "type": "string", "description": "Model parameter count in billions, or 'Undisclosed'" }, |
| "contextWindow": { "type": "string", "description": "Maximum context window size in tokens" }, |
| "trainingCutoff": { "type": "string", "description": "Training data cutoff date" }, |
| "inputCostPer1M": { "type": "number", "unit": "USD", "description": "Cost per 1 million input tokens" }, |
| "outputCostPer1M": { "type": "number", "unit": "USD", "description": "Cost per 1 million output tokens" }, |
| "pricingNote": { "type": "string", "description": "Additional pricing context and discounts" }, |
| "openSource": { "type": "boolean", "description": "Whether the model weights are publicly available" }, |
| "multimodal": { "type": "boolean", "description": "Supports image/video/audio input" }, |
| "functionCalling": { "type": "boolean", "description": "Supports structured function/tool calling" }, |
| "jsonMode": { "type": "boolean", "description": "Supports guaranteed JSON output" }, |
| "streaming": { "type": "boolean", "description": "Supports streaming token output" }, |
| "fineTuning": { "type": "boolean", "description": "Supports fine-tuning via API or weights" }, |
| "enterpriseReady": { "type": "boolean", "description": "Has enterprise SLAs, SOC2, and support options" }, |
| "mmluScore": { "type": "number|null", "range": "0-100", "description": "Massive Multitask Language Understanding score" }, |
| "humanEvalScore": { "type": "number|null", "range": "0-100", "description": "Code generation accuracy (HumanEval)" }, |
| "mathScore": { "type": "number|null", "range": "0-100", "description": "Mathematical problem-solving score (MATH)" }, |
| "mtBenchScore": { "type": "number|null", "range": "0-10", "description": "Multi-turn instruction following (MT-Bench)" }, |
| "latencyTTFTMs": { "type": "string", "description": "Time-to-first-token latency" }, |
| "throughputTPS": { "type": "string", "description": "Tokens per second throughput range" }, |
| "bestFor": { "type": "string", "description": "Recommended enterprise use cases" } |
| }, |
| "recordCount": 16, |
| "records": [ |
| { |
| "model": "GPT-4.1", |
| "provider": "OpenAI", |
| "parametersBillions": "Undisclosed", |
| "contextWindow": "1M", |
| "trainingCutoff": "Jun 2024", |
| "inputCostPer1M": 2.00, |
| "outputCostPer1M": 8.00, |
| "pricingNote": "Pay-as-you-go API; prompt caching at $0.50/1M input", |
| "openSource": false, |
| "multimodal": true, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": true, |
| "enterpriseReady": true, |
| "mmluScore": 86.5, |
| "humanEvalScore": 90.2, |
| "mathScore": 80.4, |
| "mtBenchScore": 9.2, |
| "latencyTTFTMs": "~400ms", |
| "throughputTPS": "80-190", |
| "bestFor": "General-purpose enterprise AI, long-context tasks, tool use, code generation" |
| }, |
| { |
| "model": "GPT-4.1 mini", |
| "provider": "OpenAI", |
| "parametersBillions": "Undisclosed", |
| "contextWindow": "1M", |
| "trainingCutoff": "Jun 2024", |
| "inputCostPer1M": 0.40, |
| "outputCostPer1M": 1.60, |
| "pricingNote": "Pay-as-you-go API; prompt caching at $0.10/1M input", |
| "openSource": false, |
| "multimodal": true, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": true, |
| "enterpriseReady": true, |
| "mmluScore": 83.5, |
| "humanEvalScore": 87.5, |
| "mathScore": 72.0, |
| "mtBenchScore": 8.8, |
| "latencyTTFTMs": "~200ms", |
| "throughputTPS": "120-180", |
| "bestFor": "High-volume chatbots, classification, summarization, cost-sensitive production workloads" |
| }, |
| { |
| "model": "o4-mini", |
| "provider": "OpenAI", |
| "parametersBillions": "Undisclosed", |
| "contextWindow": "200K", |
| "trainingCutoff": "Jun 2024", |
| "inputCostPer1M": 1.10, |
| "outputCostPer1M": 4.40, |
| "pricingNote": "Reasoning model with extended thinking; cached input at $0.275/1M", |
| "openSource": false, |
| "multimodal": true, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": false, |
| "enterpriseReady": true, |
| "mmluScore": 83.2, |
| "humanEvalScore": 93.4, |
| "mathScore": 96.7, |
| "mtBenchScore": null, |
| "latencyTTFTMs": "~2-10s", |
| "throughputTPS": "30-60", |
| "bestFor": "Complex reasoning, math, coding, visual tasks, cost-efficient reasoning workloads" |
| }, |
| { |
| "model": "o3", |
| "provider": "OpenAI", |
| "parametersBillions": "Undisclosed", |
| "contextWindow": "200K", |
| "trainingCutoff": "Jun 2024", |
| "inputCostPer1M": 2.00, |
| "outputCostPer1M": 8.00, |
| "pricingNote": "Most powerful reasoning model; 80% price reduction since launch; cached input at $0.50/1M", |
| "openSource": false, |
| "multimodal": true, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": false, |
| "enterpriseReady": true, |
| "mmluScore": 87.5, |
| "humanEvalScore": 95.2, |
| "mathScore": 96.7, |
| "mtBenchScore": null, |
| "latencyTTFTMs": "~3-15s", |
| "throughputTPS": "20-50", |
| "bestFor": "Hardest reasoning tasks, agentic workflows, science, mission-critical accuracy" |
| }, |
| { |
| "model": "Claude Sonnet 4.5", |
| "provider": "Anthropic", |
| "parametersBillions": "Undisclosed", |
| "contextWindow": "200K", |
| "trainingCutoff": "Apr 2025", |
| "inputCostPer1M": 3.00, |
| "outputCostPer1M": 15.00, |
| "pricingNote": "Pay-as-you-go API; prompt caching available; 66% cheaper than previous gen", |
| "openSource": false, |
| "multimodal": true, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": false, |
| "enterpriseReady": true, |
| "mmluScore": 89.0, |
| "humanEvalScore": 93.0, |
| "mathScore": 78.5, |
| "mtBenchScore": 9.2, |
| "latencyTTFTMs": "~400ms", |
| "throughputTPS": "70-90", |
| "bestFor": "Complex reasoning, long-document analysis, code review, nuanced conversation" |
| }, |
| { |
| "model": "Claude Haiku 4.5", |
| "provider": "Anthropic", |
| "parametersBillions": "Undisclosed", |
| "contextWindow": "200K", |
| "trainingCutoff": "Apr 2025", |
| "inputCostPer1M": 1.00, |
| "outputCostPer1M": 5.00, |
| "pricingNote": "Pay-as-you-go API; prompt caching available; extended thinking supported", |
| "openSource": false, |
| "multimodal": true, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": false, |
| "enterpriseReady": true, |
| "mmluScore": 80.0, |
| "humanEvalScore": 89.5, |
| "mathScore": 72.0, |
| "mtBenchScore": 8.6, |
| "latencyTTFTMs": "~200ms", |
| "throughputTPS": "120-150", |
| "bestFor": "Fast customer support, multi-agent systems, real-time classification, high-throughput tasks" |
| }, |
| { |
| "model": "Claude Opus 4.5", |
| "provider": "Anthropic", |
| "parametersBillions": "Undisclosed", |
| "contextWindow": "200K", |
| "trainingCutoff": "Apr 2025", |
| "inputCostPer1M": 5.00, |
| "outputCostPer1M": 25.00, |
| "pricingNote": "Pay-as-you-go API; highest-capability Anthropic model", |
| "openSource": false, |
| "multimodal": true, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": false, |
| "enterpriseReady": true, |
| "mmluScore": 89.5, |
| "humanEvalScore": 91.0, |
| "mathScore": 76.0, |
| "mtBenchScore": 9.3, |
| "latencyTTFTMs": "~600ms", |
| "throughputTPS": "40-60", |
| "bestFor": "Mission-critical accuracy, nuanced analysis, complex writing, regulated industries" |
| }, |
| { |
| "model": "Gemini 2.5 Pro", |
| "provider": "Google", |
| "parametersBillions": "Undisclosed", |
| "contextWindow": "1M", |
| "trainingCutoff": "Jan 2025", |
| "inputCostPer1M": 1.25, |
| "outputCostPer1M": 10.00, |
| "pricingNote": "Pay-as-you-go API; tiered pricing above 200K context ($2.50/$15.00)", |
| "openSource": false, |
| "multimodal": true, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": true, |
| "enterpriseReady": true, |
| "mmluScore": 87.2, |
| "humanEvalScore": 84.0, |
| "mathScore": 78.0, |
| "mtBenchScore": 9.0, |
| "latencyTTFTMs": "~500ms", |
| "throughputTPS": "60-80", |
| "bestFor": "Long-context RAG, document processing, video/audio analysis, agentic applications" |
| }, |
| { |
| "model": "Gemini 2.5 Flash", |
| "provider": "Google", |
| "parametersBillions": "Undisclosed", |
| "contextWindow": "1M", |
| "trainingCutoff": "Jan 2025", |
| "inputCostPer1M": 0.30, |
| "outputCostPer1M": 2.50, |
| "pricingNote": "Pay-as-you-go API; free tier available; hybrid reasoning with thinking budgets", |
| "openSource": false, |
| "multimodal": true, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": false, |
| "enterpriseReady": true, |
| "mmluScore": 83.6, |
| "humanEvalScore": 82.0, |
| "mathScore": 73.1, |
| "mtBenchScore": 8.6, |
| "latencyTTFTMs": "~150ms", |
| "throughputTPS": "150-200", |
| "bestFor": "Cost-efficient production workloads, large context tasks, multimodal processing" |
| }, |
| { |
| "model": "Llama 4 Scout", |
| "provider": "Meta", |
| "parametersBillions": "17B active (16 experts)", |
| "contextWindow": "10M", |
| "trainingCutoff": "Dec 2024", |
| "inputCostPer1M": 0.11, |
| "outputCostPer1M": 0.34, |
| "pricingNote": "Open source; pricing via Groq/DeepInfra. Fits on a single H100 GPU", |
| "openSource": true, |
| "multimodal": true, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": true, |
| "enterpriseReady": false, |
| "mmluScore": 79.6, |
| "humanEvalScore": 82.0, |
| "mathScore": 70.5, |
| "mtBenchScore": 8.3, |
| "latencyTTFTMs": "~200-600ms", |
| "throughputTPS": "100-600", |
| "bestFor": "Massive context (10M tokens), multimodal, on-premises deployment, cost optimization" |
| }, |
| { |
| "model": "Llama 4 Maverick", |
| "provider": "Meta", |
| "parametersBillions": "17B active (128 experts)", |
| "contextWindow": "10M", |
| "trainingCutoff": "Dec 2024", |
| "inputCostPer1M": 0.20, |
| "outputCostPer1M": 0.60, |
| "pricingNote": "Open source; pricing via Groq/DeepInfra/Together AI", |
| "openSource": true, |
| "multimodal": true, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": true, |
| "enterpriseReady": false, |
| "mmluScore": 85.5, |
| "humanEvalScore": 88.0, |
| "mathScore": 78.5, |
| "mtBenchScore": 8.7, |
| "latencyTTFTMs": "~300-1000ms", |
| "throughputTPS": "50-560", |
| "bestFor": "Best open-source all-around performance, data sovereignty, custom fine-tuning" |
| }, |
| { |
| "model": "DeepSeek V3", |
| "provider": "DeepSeek", |
| "parametersBillions": "671 (37B active)", |
| "contextWindow": "128K", |
| "trainingCutoff": "Dec 2024", |
| "inputCostPer1M": 0.25, |
| "outputCostPer1M": 1.10, |
| "pricingNote": "Open source (MIT); pricing via DeepSeek API and inference providers", |
| "openSource": true, |
| "multimodal": false, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": true, |
| "enterpriseReady": false, |
| "mmluScore": 88.5, |
| "humanEvalScore": 82.6, |
| "mathScore": 90.2, |
| "mtBenchScore": 8.8, |
| "latencyTTFTMs": "~300-1000ms", |
| "throughputTPS": "50-100", |
| "bestFor": "Cost-efficient reasoning, math-heavy tasks, code generation, open-source GPT-4 alternative" |
| }, |
| { |
| "model": "DeepSeek R1", |
| "provider": "DeepSeek", |
| "parametersBillions": "671 (37B active)", |
| "contextWindow": "128K", |
| "trainingCutoff": "Dec 2024", |
| "inputCostPer1M": 0.55, |
| "outputCostPer1M": 2.19, |
| "pricingNote": "Open source (MIT); reasoning model with chain-of-thought", |
| "openSource": true, |
| "multimodal": false, |
| "functionCalling": false, |
| "jsonMode": false, |
| "streaming": true, |
| "fineTuning": false, |
| "enterpriseReady": false, |
| "mmluScore": 90.8, |
| "humanEvalScore": 85.3, |
| "mathScore": 97.3, |
| "mtBenchScore": null, |
| "latencyTTFTMs": "~2-15s", |
| "throughputTPS": "20-50", |
| "bestFor": "Advanced reasoning, mathematical proofs, scientific analysis, research tasks" |
| }, |
| { |
| "model": "Mistral Large 3", |
| "provider": "Mistral AI", |
| "parametersBillions": "675 (41B active)", |
| "contextWindow": "256K", |
| "trainingCutoff": "Jun 2025", |
| "inputCostPer1M": 0.50, |
| "outputCostPer1M": 1.50, |
| "pricingNote": "Open source (Apache 2.0); EU-hosted option; MoE architecture", |
| "openSource": true, |
| "multimodal": true, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": true, |
| "enterpriseReady": true, |
| "mmluScore": 85.5, |
| "humanEvalScore": 90.2, |
| "mathScore": 83.5, |
| "mtBenchScore": 8.5, |
| "latencyTTFTMs": "~350ms", |
| "throughputTPS": "60-80", |
| "bestFor": "European data residency, multilingual enterprise, coding, open-source frontier model" |
| }, |
| { |
| "model": "Mistral Small 3.2", |
| "provider": "Mistral AI", |
| "parametersBillions": "24", |
| "contextWindow": "128K", |
| "trainingCutoff": "Mar 2025", |
| "inputCostPer1M": 0.06, |
| "outputCostPer1M": 0.18, |
| "pricingNote": "Open source; EU-hosted; ultra-efficient 24B model", |
| "openSource": true, |
| "multimodal": false, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": true, |
| "enterpriseReady": true, |
| "mmluScore": 72.2, |
| "humanEvalScore": 75.0, |
| "mathScore": 60.0, |
| "mtBenchScore": 8.1, |
| "latencyTTFTMs": "~100ms", |
| "throughputTPS": "150-200", |
| "bestFor": "Ultra-low-cost classification, routing, edge deployment, cost-efficient European workloads" |
| }, |
| { |
| "model": "Command A", |
| "provider": "Cohere", |
| "parametersBillions": "Undisclosed", |
| "contextWindow": "256K", |
| "trainingCutoff": "Mar 2024", |
| "inputCostPer1M": 2.50, |
| "outputCostPer1M": 10.00, |
| "pricingNote": "Pay-as-you-go API; RAG-optimized with grounded generation", |
| "openSource": false, |
| "multimodal": false, |
| "functionCalling": true, |
| "jsonMode": true, |
| "streaming": true, |
| "fineTuning": true, |
| "enterpriseReady": true, |
| "mmluScore": 71.2, |
| "humanEvalScore": 68.0, |
| "mathScore": 53.0, |
| "mtBenchScore": 8.2, |
| "latencyTTFTMs": "~280ms", |
| "throughputTPS": "60-80", |
| "bestFor": "Enterprise RAG, grounded generation with citations, multilingual search, agentic workflows" |
| } |
| ] |
| } |
|
|
