Enterprise LLM Selection Guide

Comprehensive directory of large language models with use cases, performance characteristics, and deployment recommendations for enterprise AI.

Quick Selection Guide

Task Complexity

Simple tasks (classification, simple Q&A) → smaller/cheaper models. Complex reasoning → GPT-4, Claude 3 Opus, o1

Response Speed

Real-time applications → GPT-4o, Claude 3.5 Haiku, Gemini Flash. Batch processing → any model

Cost

High volume → optimize for cost per token. Calculate monthly spend based on expected usage

Context Length

Large documents → Gemini 1.5 Pro (2M), Claude (200K). Short text → any model

Data Privacy

Sensitive data → self-hosted (Llama), zero data retention APIs, or on-premise deployment

Specialized Needs

Code → Codestral, Claude. Writing → Claude. RAG → Command R+. Vision → GPT-4o, Gemini

Multimodal

Vision needed → GPT-4o, Gemini, Claude. Video → Gemini 1.5 Pro. Audio → Gemini 2.0 Flash

Latency Requirements

Sub-second → streaming APIs with fast models (GPT-4o, Haiku, Flash). Async → any model

Decision Tree

Do you need vision/multimodal?
Yes: GPT-4o (balanced) or Gemini 1.5 Pro (video/large context)
No: Continue...
Is this a simple or complex task?
Simple: GPT-4o mini, Claude 3.5 Haiku, or Gemini Flash for cost optimization
Complex: Continue...
Do you need advanced reasoning?
Yes: o1 (highest quality) or DeepSeek R1 (cost effective)
No: Continue...
Is writing quality critical?
Yes: Claude 3.5 Sonnet or Claude 3 Opus
No: Continue...
Do you need very large context (>128K)?
Yes: Gemini 1.5 Pro (2M), Claude 3.5 Sonnet (200K), or Amazon Nova Pro (300K)
No: Continue...
What's your priority?
Cost: GPT-4o mini, Gemini Flash, Amazon Nova Lite, or DeepSeek V3
Quality: GPT-4 Turbo, Claude 3 Opus, or o1
Balanced: GPT-4o, Claude 3.5 Sonnet, or Mistral Large 2

Models by Use Case

Extract information, answer questions, and analyze documents

Recommended Models

Gemini 1.5 Pro
Massive 2M context window for entire document sets
When to use: Processing very large documents or multiple documents
Claude 3.5 Sonnet
Excellent at nuanced understanding and analysis
When to use: Complex analytical reading requiring sophistication
GPT-4 Turbo
Strong reasoning with structured output support
When to use: Extracting structured data from documents
Gemini 1.5 Flash
Cost-effective with 1M context
When to use: High-volume document processing on a budget

Best Practices

  • Use streaming for long documents to provide faster perceived response
  • Implement chunking strategies for documents exceeding context windows
  • Consider OCR preprocessing for scanned documents
  • Use structured outputs (JSON mode) for data extraction tasks
  • Test with your specific document types during evaluation

Generate high-quality written content, articles, marketing copy

Recommended Models

Claude 3.5 Sonnet
Best-in-class writing quality and style
When to use: Long-form content, sophisticated writing, brand voice
Claude 3 Opus
Highest quality for critical content
When to use: High-stakes content where quality is paramount
GPT-4o
Good balance of quality and speed
When to use: General-purpose content at scale
GPT-4o mini
Cost-effective for simpler content
When to use: High-volume simple content like product descriptions

Best Practices

  • Provide clear style guides and examples in prompts
  • Use few-shot examples for consistent brand voice
  • Implement human review for public-facing content
  • A/B test different models for your specific content type
  • Use temperature settings to control creativity (0.7-0.9 for creative writing)

Generate, review, debug, and explain code

Recommended Models

Claude 3.5 Sonnet
Excellent at complex code generation and refactoring
When to use: Complex codebases, architectural decisions
GPT-4o
Strong code generation with good speed
When to use: General-purpose coding tasks
Codestral
Specialized for code with 80+ languages
When to use: IDE integration, code completion
o1
Advanced reasoning for complex algorithms
When to use: Difficult algorithmic problems, optimization

Best Practices

  • Provide relevant context from your codebase
  • Use specific language and framework requirements
  • Request tests and documentation alongside code
  • Implement code review processes for AI-generated code
  • Test generated code thoroughly before production use

Analyze datasets, generate insights, create visualizations

Recommended Models

o1
Advanced reasoning for complex analytical tasks
When to use: Complex statistical analysis, hypothesis testing
Claude 3.5 Sonnet
Excellent at explaining insights clearly
When to use: Analysis requiring clear communication of findings
GPT-4 Turbo
Good at structured data with JSON mode
When to use: Processing and transforming structured data
Gemini 1.5 Pro
Can analyze very large datasets in context
When to use: Working with extensive data that fits in context

Best Practices

  • Pre-process data into clean formats (CSV, JSON)
  • Provide clear questions and success criteria
  • Use code interpreter features when available
  • Validate statistical conclusions independently
  • Consider privacy when sharing sensitive data

Automate customer service, answer questions, resolve issues

Recommended Models

Claude 3.5 Haiku
Fast, cost-effective, good instruction following
When to use: High-volume support automation
GPT-4o mini
Very low cost for simple queries
When to use: FAQ-style questions, simple routing
Gemini 1.5 Flash
Fast with large context for conversation history
When to use: Support requiring long conversation context
Command R
Optimized for RAG with knowledge bases
When to use: Support requiring knowledge base retrieval

Best Practices

  • Implement escalation to humans for complex issues
  • Use RAG to ground responses in your documentation
  • Monitor and analyze conversations for quality
  • Implement rate limiting and abuse prevention
  • Provide clear indicators that users are interacting with AI

Condense long documents, meetings, conversations

Recommended Models

Gemini 1.5 Flash
Large context, fast, very cost effective
When to use: High-volume summarization of long content
Claude 3.5 Haiku
Fast and accurate for quality summaries
When to use: Balanced performance and quality
GPT-4o mini
Low cost for simple summarization
When to use: Simple summaries at massive scale
Claude 3.5 Sonnet
Best quality summaries with nuance
When to use: High-stakes summaries requiring sophistication

Best Practices

  • Specify desired length and format clearly
  • Request key points separately from narrative summary
  • Use iterative refinement for critical summaries
  • Test with various document types and lengths
  • Consider chunking for very long documents

Categorize text, moderate content, route requests

Recommended Models

GPT-4o mini
Extremely cost effective for simple classification
When to use: High-volume classification tasks
Amazon Nova Micro
Lowest cost option for text classification
When to use: Maximum cost optimization needed
Claude 3.5 Haiku
Fast and accurate classification
When to use: Balance of speed and accuracy
Gemini 1.5 Flash
Great value with large context
When to use: Classification requiring more context

Best Practices

  • Use consistent category definitions with examples
  • Request classification confidence scores
  • Implement human review for edge cases
  • Monitor accuracy and retrain/adjust prompts regularly
  • Use structured outputs (JSON) for reliable parsing

Complex reasoning, strategy, multi-step problem solving

Recommended Models

o1
Best reasoning capability available
When to use: Highest stakes complex reasoning required
DeepSeek R1
Strong reasoning at much lower cost
When to use: Cost-conscious complex reasoning
Claude 3 Opus
Excellent at nuanced multi-step reasoning
When to use: Complex analytical reasoning requiring sophistication
o1-mini
Good reasoning for technical problems
When to use: STEM/code reasoning on a budget

Best Practices

  • Break complex problems into clear steps
  • Provide all necessary context upfront
  • Use chain-of-thought prompting
  • Validate reasoning logic independently
  • Consider multiple passes for critical decisions

Process images, video, audio alongside text

Recommended Models

GPT-4o
Strong vision capabilities, fast, reliable
When to use: General-purpose vision + text applications
Gemini 1.5 Pro
Video understanding, massive context
When to use: Video analysis or multiple images
Gemini 2.0 Flash
Multimodal output (text, images, audio)
When to use: Creating multimodal content
Claude 3.5 Sonnet
Excellent vision with strong reasoning
When to use: Complex image analysis requiring deep understanding

Best Practices

  • Optimize image resolution for cost (models accept various sizes)
  • Provide clear instructions about what to look for
  • Test with representative samples of your image types
  • Consider privacy implications of image data
  • Use appropriate modalities - don't force vision when text suffices

Deploy AI in regulated, secure enterprise environments

Recommended Models

Llama 3.3 70B
Self-hostable, open source, high performance
When to use: Data cannot leave premises, full control needed
Mistral Large 2
EU data residency, strong performance
When to use: European data requirements, privacy regulations
Amazon Nova Pro
AWS-native, integrated security
When to use: AWS VPC deployment, integration with AWS services
Azure OpenAI
Microsoft compliance certifications
When to use: Enterprise Microsoft agreements, compliance needs

Best Practices

  • Conduct security and compliance reviews
  • Implement data classification and handling policies
  • Use private endpoints and VPC deployment
  • Enable audit logging and monitoring
  • Establish incident response procedures
  • Train staff on responsible AI usage
  • Regular security assessments and updates

Complete Model Directory

OpenAI

Commercial API

GPT-5.2

200K tokens $8/$24 per 1M tokens (input/output)
Strengths:
Best-in-class reasoningAgentic task executionAdvanced codingMultimodal capabilities
Use Cases:
  • Complex software development and debugging
  • Multi-step agentic workflows and automation
  • Enterprise decision support systems
  • Advanced data analysis and business intelligence
Best For: Organizations requiring the most capable model for complex coding and agentic tasks
Recommendation: Flagship model - choose GPT-5.2 for mission-critical applications requiring highest intelligence

GPT-5.2 Pro

200K tokens $12/$36 per 1M tokens
Strengths:
Enhanced reasoningMaximum precisionSuperior accuracyComplex problem solving
Use Cases:
  • High-stakes financial analysis and modeling
  • Legal document analysis requiring precision
  • Strategic planning and decision support
  • Research synthesis and technical writing
Best For: Critical applications where accuracy and precision are paramount
Recommendation: Use when quality and precision matter more than cost - best for high-stakes decisions

GPT-5 mini

200K tokens $1/$4 per 1M tokens
Strengths:
Cost-efficientFast inferenceGood reasoningWell-defined tasks
Use Cases:
  • Customer service automation at scale
  • Content moderation and classification
  • Document summarization
  • High-volume standard workflows
Best For: Well-defined production tasks requiring balance of capability and cost
Recommendation: Best value - choose GPT-5 mini for most standard enterprise applications

GPT-5 nano

128K tokens $0.20/$0.80 per 1M tokens
Strengths:
Fastest inferenceLowest costHigh throughputSimple tasks
Use Cases:
  • Email classification and routing
  • Simple chatbot responses
  • Tag generation and metadata extraction
  • High-volume simple queries
Best For: Cost-sensitive, high-volume applications with straightforward requirements
Recommendation: Most cost-effective GPT-5 - perfect for simple, repetitive tasks at massive scale

GPT-4.1

128K tokens $6/$18 per 1M tokens
Strengths:
Smartest non-reasoning modelBalanced performanceGeneral purposeReliable
Use Cases:
  • General business operations and workflows
  • Content generation and editing
  • Standard document processing
  • Multi-purpose enterprise applications
Best For: Applications that don't require advanced reasoning but need reliable intelligence
Recommendation: Solid choice for general-purpose tasks - bridges gap between GPT-5 mini and GPT-5.2

o3

200K tokens $18/$72 per 1M tokens
Strengths:
Advanced reasoningComplex problem solvingStep-by-step thinkingSTEM excellence
Use Cases:
  • Scientific research and analysis
  • Complex mathematical modeling
  • Advanced algorithm design
  • Multi-step strategic planning
Best For: Tasks requiring deep, careful reasoning and complex problem-solving
Recommendation: Use for problems requiring explicit reasoning - succeeded o1 with enhanced capabilities

o4-mini

128K tokens $4/$16 per 1M tokens
Strengths:
Fast reasoningCost-efficientTechnical focusCode optimization
Use Cases:
  • Code debugging and optimization
  • Technical documentation generation
  • Mathematical problem solving
  • Engineering calculations
Best For: Technical and STEM tasks requiring reasoning at reasonable cost
Recommendation: Successor to o1-mini - excellent for coding and technical tasks requiring reasoning

GPT-4o (Deprecated)

128K tokens $5/$15 per 1M tokens
Strengths:
MultimodalFastLegacy support
Use Cases:
  • Legacy applications transitioning to GPT-5 series
Best For: Existing deployments only - not recommended for new projects
Recommendation: DEPRECATED - Migrate to GPT-5 series (GPT-5 mini or GPT-5.2) for continued support

Anthropic

Commercial API

Claude 3.5 Sonnet

200K tokens $3/$15 per 1M tokens
Strengths:
Excellent writingStrong reasoningLong contextNuanced understanding
Use Cases:
  • Long-form content creation
  • Research synthesis across multiple documents
  • Complex analytical writing
  • Code generation with extensive context
Best For: Tasks requiring sophisticated writing, analysis, or very long context
Recommendation: Best-in-class for writing quality and handling massive documents

Claude 3.5 Haiku

200K tokens $0.80/$4 per 1M tokens
Strengths:
FastCost effectiveGood instruction followingCompact
Use Cases:
  • Customer support automation
  • Content moderation at scale
  • Quick summarization
  • High-throughput simple tasks
Best For: High-volume applications where speed and cost matter
Recommendation: Excellent balance of capability and cost for production systems

Claude 3 Opus

200K tokens $15/$75 per 1M tokens
Strengths:
Highest capabilityBest reasoningExcellent at following complex instructions
Use Cases:
  • High-stakes content creation
  • Complex multi-step workflows
  • Sophisticated analysis requiring nuance
  • Critical decision support
Best For: Mission-critical tasks where quality is paramount
Recommendation: Use when quality matters more than cost or speed

Google

Commercial API

Gemini 1.5 Pro

2M tokens $1.25/$5 per 1M tokens
Strengths:
Massive contextMultimodalCode executionVideo understanding
Use Cases:
  • Analysis of entire codebases
  • Processing massive document collections
  • Video content analysis and transcription
  • Long conversation threads
Best For: Applications requiring processing of extremely large amounts of context
Recommendation: Unmatched for analyzing very large documents or video content

Gemini 1.5 Flash

1M tokens $0.075/$0.30 per 1M tokens
Strengths:
Very fastLarge contextVery cost effectiveGood quality
Use Cases:
  • Real-time chat applications
  • Large document processing at scale
  • Cost-efficient high-volume tasks
  • Rapid prototyping
Best For: High-performance applications needing large context at low cost
Recommendation: Exceptional value for production systems processing large inputs

Gemini 2.0 Flash

1M tokens $0.10/$0.40 per 1M tokens
Strengths:
Multimodal generationFastImage/audio outputLive API
Use Cases:
  • Interactive AI applications
  • Content generation (images + text)
  • Real-time multimodal chat
  • Creative applications
Best For: Applications requiring multimodal input AND output
Recommendation: Cutting edge for multimodal interactive experiences

Meta

Open Source (Self-hosted or API)

Llama 3.3 70B

128K tokens Open source (hosting costs only)
Strengths:
Open sourceGood performanceSelf-hostableCustomizable
Use Cases:
  • On-premise deployments for sensitive data
  • Custom fine-tuning for specific domains
  • Cost optimization for high-volume use
  • Air-gapped environments
Best For: Organizations needing data privacy or extensive customization
Recommendation: Best open-source option for enterprise deployments

Llama 3.1 405B

128K tokens Open source (significant hosting costs)
Strengths:
Largest open modelStrong performanceFull control
Use Cases:
  • Research and development
  • Creating fine-tuned specialized models
  • When data cannot leave infrastructure
  • Benchmarking and evaluation
Best For: Organizations with infrastructure for very large models
Recommendation: Consider only if you have GPU infrastructure and specific needs

Llama 3.2 (1B, 3B, 11B, 90B)

128K tokens Open source (low hosting costs for smaller variants)
Strengths:
Range of sizesEdge deploymentVision capableEfficient
Use Cases:
  • Edge AI on devices
  • Embedded systems
  • Mobile applications
  • IoT and edge computing
Best For: On-device AI and resource-constrained environments
Recommendation: Excellent for edge deployment where connectivity is limited

Mistral AI

Commercial API & Open Source

Mistral Large 2

128K tokens $2/$6 per 1M tokens
Strengths:
Excellent reasoningCode proficiencyFunction callingEuropean data residency
Use Cases:
  • Applications requiring EU data residency
  • Complex code generation
  • Agentic workflows with tools
  • Cost-effective alternative to GPT-4
Best For: European organizations or those needing strong code capabilities
Recommendation: Solid alternative to US providers with good performance/cost

Mistral Small

128K tokens $0.20/$0.60 per 1M tokens
Strengths:
Low latencyCost effectiveGood qualityMultilingual
Use Cases:
  • Customer support in multiple languages
  • Real-time applications
  • High-volume classification
  • Budget-conscious deployments
Best For: Cost-sensitive multilingual applications
Recommendation: Great value for simpler tasks, especially in non-English

Codestral

32K tokens $0.20/$0.60 per 1M tokens
Strengths:
Code-specific80+ languagesFill-in-middleFast
Use Cases:
  • IDE code completion
  • Code review and analysis
  • Documentation generation
  • Bug detection
Best For: Dedicated coding tasks and developer tools
Recommendation: Specialized tool for code-heavy workflows

Mixtral 8x7B

32K tokens Open source
Strengths:
Mixture of expertsCost effectiveGood performanceSelf-hostable
Use Cases:
  • General-purpose on-premise deployments
  • Cost optimization through self-hosting
  • Fine-tuning for specific tasks
  • Research and experimentation
Best For: Organizations wanting strong open-source models
Recommendation: Excellent open-source option with good performance

xAI

Commercial API

Grok 2

128K tokens $2/$10 per 1M tokens
Strengths:
Real-time informationStrong reasoningConversationalLess censored
Use Cases:
  • Real-time news and information synthesis
  • Applications requiring current events
  • Research on contemporary topics
  • Less restrictive content generation
Best For: Applications needing current information or less restrictive outputs
Recommendation: Consider when real-time information is critical

Grok 2 mini

128K tokens $0.50/$2.50 per 1M tokens
Strengths:
FastReal-time dataCost effective
Use Cases:
  • High-volume current events monitoring
  • Real-time social media analysis
  • News aggregation and summarization
Best For: Cost-effective real-time information processing
Recommendation: Good for high-throughput real-time applications

Amazon

Commercial API (Bedrock)

Amazon Nova Pro

300K tokens $0.80/$3.20 per 1M tokens
Strengths:
Large contextMultimodalAWS integrationCost effective
Use Cases:
  • AWS-native applications
  • Large document processing on AWS
  • Integrated with AWS services
  • Enterprise AWS deployments
Best For: Organizations heavily invested in AWS ecosystem
Recommendation: Natural choice for AWS-centric architectures

Amazon Nova Lite

300K tokens $0.06/$0.24 per 1M tokens
Strengths:
Very low costFastLarge contextAWS integrated
Use Cases:
  • High-volume AWS workloads
  • Cost optimization in AWS
  • Simple text processing at scale
  • AWS Lambda functions
Best For: Extremely cost-sensitive AWS applications
Recommendation: Cheapest option for simple tasks on AWS

Amazon Nova Micro

128K tokens $0.035/$0.14 per 1M tokens
Strengths:
Lowest costText onlyUltra fastEfficient
Use Cases:
  • Massive-scale text processing
  • Cost-critical applications
  • Simple classification/routing
  • High-throughput batch processing
Best For: Maximum cost efficiency for simple text tasks
Recommendation: When you need the absolute lowest cost per token

DeepSeek

Commercial API & Open Source

DeepSeek V3

64K tokens $0.27/$1.10 per 1M tokens
Strengths:
Excellent reasoningVery cost effectiveStrong at mathOpen source
Use Cases:
  • Cost-optimized reasoning tasks
  • Mathematical and scientific computing
  • Technical documentation
  • Budget-conscious complex tasks
Best For: Organizations seeking high performance at low cost
Recommendation: Outstanding value for reasoning-intensive applications

DeepSeek R1

64K tokens $0.55/$2.19 per 1M tokens
Strengths:
Advanced reasoningChain of thoughtMath/codeOpen weights
Use Cases:
  • Complex problem solving
  • Advanced mathematical reasoning
  • Research applications
  • When you need to see reasoning steps
Best For: Tasks requiring transparent reasoning process
Recommendation: Competitive with o1 at fraction of the cost

Cohere

Commercial API

Command R+

128K tokens $2.50/$10 per 1M tokens
Strengths:
RAG optimizedTool useEnterprise focusedMultilingual
Use Cases:
  • Retrieval augmented generation systems
  • Enterprise search applications
  • Multi-step workflows with tools
  • Knowledge base Q&A
Best For: RAG applications and enterprise search
Recommendation: Purpose-built for retrieval and tool-use workflows

Command R

128K tokens $0.15/$0.60 per 1M tokens
Strengths:
Fast RAGCost effectiveGood for retrieval10 languages
Use Cases:
  • High-volume RAG applications
  • Customer knowledge bases
  • Internal document search
  • FAQ automation
Best For: Cost-effective RAG at scale
Recommendation: Best value for production RAG systems

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