Our approach: neutrality and pragmatism
There is no universally superior LLM model. Each model has areas of excellence, cost constraints, data policies and integration ecosystems that differ. We do not receive any commission from any AI provider. This comparison reflects our field experience, without commercial affiliation.
Our final recommendation will always vary depending on your sector, your existing stack, your GDPR constraints and your processing volume. This guide is a starting point, not a conclusion.
✦
Claude 3.5 Sonnet / Claude 3 Opus
Anthropic · San Francisco, USA
Strengths
- Most reliable multi-step reasoning for autonomous agents
- Nuanced analysis of long and complex documents
- Excellent context window (200k tokens)
- Predictable behavior and faithfully followed instructions
- Advanced coding capabilities (development agents)
Limitations
- No native image generation (unlike GPT-4o)
- Data hosted with Anthropic (AWS, USA), DPA available
- API cost higher than DeepSeek for volume processing
- No real-time web search (unlike Perplexity)
Ideal for: autonomous AI agents, contract and document analysis, structured writing, strategic reasoning, tasks where precision takes precedence over cost. Our first choice for multi-step agents.
⬡
GPT-4o / GPT-4o mini
OpenAI · San Francisco, USA · via Microsoft Azure
Strengths
- Native multimodal: text, images, audio in a single API call
- Analysis of heterogeneous documents (PDF + images + tables)
- Native Microsoft Copilot integration via Azure OpenAI Service
- GPT-4o mini : excellent performance/cost ratio for volumes
- Largest integration ecosystem (OpenAI plugins, Assistants API)
Limitations
- Data hosted with OpenAI / Microsoft (USA), EU Data Boundary via Azure
- Long-term reasoning less reliable than Claude on very complex tasks
- High API cost for GPT-4o full (GPT-4o mini = low-cost alternative)
Ideal for: data extraction from PDF documents and images, Microsoft 365 and Teams integrations via Azure, visual analysis, use cases requiring native multimodality.
⟡
Mistral Large / Mistral Small / Codestral
Mistral AI · Paris, France (European hosting available)
Strengths
- Only 100% European founding large model (HQ Paris)
- On-premise deployment on OVHcloud or French infrastructure
- Mistral Small: greatly reduced cost for simple tasks
- Codestral: specialized code model, top performance for scripts
- The Platform: robust GDPR DPA, EU data location
Limitations
- Slightly lower performance than Claude/GPT-4o on very complex reasoning tasks
- Less developed plugin and integration ecosystem
- No native multimodal capability on current versions
Ideal for: regulated sectors (health, finance, defense, communities), any organization subject to strict GDPR requirements for data location, code automation via Codestral, large volumes with Mistral Small.
◈
Gemini 1.5 Pro / Gemini 2.0 Flash
Google DeepMind · Mountain View, USA · Vertex AI
Strengths
- 1M token context window, unmatched for large-scale RAG
- Native Google Workspace integration (Drive, Docs, Gmail, Sheets)
- NotebookLM: out-of-the-box RAG tool on your Google documents
- Gemini 2.0 Flash : excellent speed/cost ratio for real-time workflows
- Vertex AI: robust GCP infrastructure for enterprise deployments
Limitations
- Data hosted with Google (USA), GDPR clauses via GCP available
- Complex reasoning slightly behind Claude on very nuanced tasks
- Less suited if your organization is on Microsoft 365
Ideal for: RAG on very large document bases, native Google Workspace integrations, search in Google Drive, use cases with very long contexts (books, long transcripts, extended datasets)
Λ
Meta Llama 3.1 / Llama 3.2
Meta AI · Open-source (private deployment)
Strengths
- Fully open-source, deployed on your infrastructure: your data never leaves
- Zero inference marginal cost (you only pay for compute)
- Complete fine-tuning possible on your proprietary data
- Llama 3.1 405B: performance close to the best proprietary models
- Ideal for large volumes where API costs would become prohibitive
Limitations
- Requires a dedicated server infrastructure (GPU), with an initial infrastructure cost
- Deployment and maintenance more complex than a cloud API
- Slightly lower performance than the best proprietary models on certain tasks
Ideal for: organizations with highly sensitive data (defense secrets, critical health data, proprietary IP), large volumes where API costs are a problem, sector-specific fine-tuning on internal data.
R1
DeepSeek R1 / DeepSeek V3
DeepSeek · China (international API available)
Strengths
- Performance/cost report: 10 to 30× less expensive than GPT-4o on certain tasks
- DeepSeek R1: highly structured and mathematical reasoning
- Excellent performance on financial analysis and structured problems
- Available open-source, can be deployed on-premise
Limitations
- Primary API hosted in China, potential issue for sensitive data
- Recommended only via on-premise deployment or third-party hosting for company data
- Less versatile than Claude or GPT-4o for very open tasks
Ideal for: high-volume automations where marginal cost is critical, financial analysis and structured reasoning, on-premise deployment via a European host to avoid sovereignty issues.
⊕
Perplexity AI
Perplexity AI · San Francisco, USA (API Enterprise)
Strengths
- Access to real-time news, bypassing training date limit
- Sourced and verifiable responses with links to sources
- Ideal for automated competitive and sectoral monitoring
- API available for integration into automatic monitoring workflows
Limitations
- Less suited to complex reasoning tasks or long generation
- Depends on the quality of available web sources
- Not designed for automation tasks or autonomous agent
Ideal for: automated competitive intelligence, sourced documentary research, sectoral trend monitoring, real-time market benchmarking.
Synthetic comparative table
| Model | Reasoning | Multimodal | RAG | Sovereignty | API cost | Ideal for |
|---|---|---|---|---|---|---|
| Claude 3.5 Sonnet (Anthropic) | ●●● | ●●○ | ●●● | DPA USA | Medium-high | Agents, analysis, writing |
| GPT-4o (OpenAI) | ●●● | ●●● | ●●● | EU Boundary | High | Multimodal, Microsoft integrations |
| Mistral Large (Mistral AI) | ●●○ | ●○○ | ●●● | France/EU | Medium | Sovereignty, strict GDPR |
| Gemini 1.5 Pro (Google) | ●●○ | ●●● | ●●● | GCP EU clauses | Medium | RAG 1M tokens, G Workspace |
| Meta Llama 3.1 (Meta) | ●●○ | ●●○ | ●●● | 100% private | Infrastructure | On-premise, volumes, fine-tuning |
| DeepSeek R1 (DeepSeek) | ●●○ | ●○○ | ●●○ | China* | Very low | Structured analysis, volumes |
| Perplexity AI | ●○○ | ●●○ | ●●● | USA | Medium | Real-time monitoring, sourcing |
| Microsoft Copilot (OpenAI) | ●●○ | ●●● | ●●● | M365 DPA EU | M365 license | Microsoft Environments |
* DeepSeek on-premise via European host resolves the sovereignty issue.