A \ V — Model Ecosystem

LLM Provider Deep-Dives

Hands-on production experience across every major provider — strengths, weaknesses, and the exact use cases each excels at.

Anthropic Claude

Proprietary API

✳️

Primary model for agentic workloads, complex reasoning, and enterprise deployments. Deep expertise in tool use, MCP integration, constitutional AI patterns, and multi-turn orchestration.

claude-opus-4Complex reasoning · Orchestration

claude-sonnet-4.6Balanced · Production default

claude-haiku-4.5Fast · High-volume tasks

Primary agentic & enterprise reasoning

OpenAI GPT-4o / o3

Proprietary API

⬛

Multimodal reasoning, function calling, Assistants API, and structured outputs. Used in multi-LLM routing architectures for vision tasks and code-heavy pipelines via the o-series reasoning models.

gpt-4oMultimodal · Vision · Function calls

o3-miniCode reasoning · Math

text-embedding-3-largeEmbeddings · RAG

Multimodal · reasoning chains

Google Gemini 2.0

Cloud-managed

🌐

Gemini Flash and Pro via Vertex AI. Long-context processing up to 2M tokens, code execution, grounding with Google Search. Preferred for GCP-native workloads with tight BigQuery integration.

gemini-2.0-proLong-context · Code execution

gemini-2.0-flashFast · GCP-native tasks

text-embedding-004Vertex embeddings

Long-context · GCP-native workloads

Meta Llama 3.x / 4

Open Source

🦙

Llama 3.1 405B, 70B, 8B. Fine-tuned with LoRA/QLoRA on proprietary datasets via HuggingFace PEFT. vLLM serving on OpenShift AI for regulated environments. Llama 4 Scout for multimodal on-prem.

llama-3.1-405bLargest OSS · Near-GPT4 quality

llama-3.1-70bFine-tuned domain models

llama-3.1-8bEdge · Low-latency serving

Self-hosted · fine-tuning · cost control

Mistral / Mixtral

Open Source

🌪️

Mistral 7B, Mixtral 8x7B MoE. Exceptional performance-per-dollar. Used for high-throughput classification and extraction tasks. Mistral Large for enterprise via La Plateforme API.

mixtral-8x7bMoE · High-throughput batch

mistral-7bClassification · Extraction

mistral-largeEnterprise API

High-throughput · batch inference

AWS Bedrock Models

Cloud-managed

☁️

Titan, Nova, and third-party models (Claude, Llama, Mistral) via Bedrock. Guardrails, Knowledge Bases, and Agents APIs for enterprise-grade safety and retrieval. IAM-native auth.

claude-3-sonnet (Bedrock)Cross-region inference

amazon-nova-proAWS-native multimodal

titan-embeddings-v2Knowledge Bases RAG

AWS-native enterprise deployments

Provider Comparison Matrix

Provider	Tool Use	Long Context	Fine-tuning	On-prem	Multimodal	Cost tier	Best for
Anthropic Claude	✓✓	✓✓	—	—	✓	Medium	Agentic, reasoning, MCP
OpenAI GPT-4o	✓✓	✓	Partial	—	✓✓	High	Vision, code, structured output
Gemini 2.0	✓	✓✓	Vertex	—	✓✓	Medium	Long context, GCP workloads
Llama 3.x	Partial	✓	✓✓	✓✓	Llama 4	Low	Fine-tuning, air-gap, cost
Mistral / Mixtral	Partial	✓	✓✓	✓✓	—	Low	Batch, classification, MoE
AWS Bedrock	✓✓	✓	Nova	—	✓	Medium	AWS-native, guardrails, RAG

Multi-LLM Routing Logic

Every request is routed to the optimal model based on four dimensions: task type, latency SLA, cost ceiling, and data residency requirements.

Task: Complex Reasoning

Route → Claude Opus

Multi-step planning, agentic loops, MCP tool orchestration, legal/compliance analysis, code architecture reviews.

claude-opus-4 · $15/Mtok input

Task: Production Default

Route → Claude Sonnet

The balanced workhorse — high quality, reasonable cost. Default for most enterprise tasks, customer-facing agentic features, summarisation.

claude-sonnet-4.6 · $3/Mtok input

Task: High Volume / Fast

Route → Claude Haiku / Mistral

Sub-100ms latency tasks, classification, entity extraction, intent detection, high-frequency webhook processing.

haiku-4.5 or mistral-7b · <$0.50/Mtok

Task: Vision / Multimodal

Route → GPT-4o / Gemini

Image analysis, document OCR, chart interpretation, video understanding. Claude for multimodal when tool-use is also required.

gpt-4o or gemini-2.0-pro

Task: Air-gap / Regulated

Route → Llama / Mistral (vLLM)

Data residency requirements, air-gapped networks, HIPAA/GDPR workloads where no data can leave the private cloud.

llama-3.1-70b · self-hosted

Task: GCP-native Analytics

Route → Gemini 2.0 Flash

BigQuery data analysis, long-context document processing, Google Search grounding, Workspace integrations.

gemini-2.0-flash · Vertex AI

Fine-tuning & Domain Adaptation

When base models aren't enough — domain-specific fine-tuning with LoRA, QLoRA, and PEFT on HuggingFace.

LoRA / QLoRA Fine-tuning

Parameter-efficient fine-tuning using Low-Rank Adaptation. Train on proprietary corpora with 4-bit quantisation — full 70B model quality at a fraction of GPU cost. Deployed via HuggingFace PEFT + vLLM.

LoRAQLoRAPEFT4-bit quantvLLMLlama 3.1

Domain Corpus Training

Curated domain-specific datasets from enterprise knowledge bases, clinical notes, financial filings, and proprietary documentation. Data pipeline: extraction → cleaning → deduplication → instruction tuning format.

Data pipelineInstruction tuningDPOSFTMLflow

Embedding Model Fine-tuning

Domain-adapted embedding models for retrieval — fine-tuned on enterprise Q&A pairs for dramatically improved RAG recall. HuggingFace sentence-transformers with contrastive learning on domain triplets.

sentence-transformersContrastive learningMTEB evalpgvector

MLOps for Fine-tuned Models

Complete lifecycle: experiment tracking, model registry, drift detection, A/B deployment, automated retraining triggers. No fine-tuned model ships without passing eval benchmarks on held-out domain data.

MLflowModel registryDrift detectionA/B deploymentCI/CD

Every model.Right task.Right cost.

LLM Provider Deep-Dives

Provider Comparison Matrix

Multi-LLM Routing Logic

Fine-tuning & Domain Adaptation

Every model.
Right task.
Right cost.