Gemini vs Claude vs Llama on Vertex AI: Which Model to Pick
Quality, cost, latency, governance — practical decision criteria for picking between Gemini 2.5, Claude, Llama 4, and Mistral on Vertex AI Model Garden.
Fabiano Brito
CEO & Founder
“Which model is best?” is the wrong question. The right question is “which model for which case?” — and the answer varies by dimension. This post compiles what we’ve learned running all of them in production in Autenticare projects during 2025–2026.
The catalog (summary)
| Model | Provider | Vertex Availability | Differentiator |
|---|---|---|---|
| Gemini 2.5 Pro / Flash | Native | Top multimodal, 1M context, Workspace integration | |
| Claude Sonnet 4.6 / Opus 4.7 | Anthropic | Vertex Model Garden | Reasoning + long-form writing |
| Llama 4 (various sizes) | Meta (open weights) | Vertex + self-host | Open, customizable, on-prem possible |
| Mistral Large 3 | Mistral AI | Vertex Model Garden | Aggressive cost, European multilingual |
| Codestral | Mistral AI | Vertex Model Garden | Specialized in code |
Other models are in the catalog (legacy PaLM, vertical models), but these 5 cover 95% of enterprise cases.
The 4 candidates, at a glance
🟢 Gemini 2.5
Pro / Flash
80% of cases. Native multimodal, 1M context, only path for Workspace.
🔵 Claude 4.6 / 4.7
Sonnet / Opus
Long-form writing, legal reasoning, brand copy. Frequent second choice.
🟠 Llama 4
Open weights
On-prem, real fine-tuning, data that cannot leave. Defense, government, sensitive healthcare.
⚪ Mistral / Codestral
Large 3
30–50% cheaper at volume. Codestral for dev agents. Strong in FR/DE/IT/ES.
Gemini 2.5 Pro / Flash — when to choose
- Native multimodal: PDF, image, audio, video in the same call.
- 1M token context: read entire databases without heroic chunking.
- Workspace integration — only path for agents in corporate Gmail/Docs/Drive.
sa-east1with models running in the region.- Competitive cost, especially Flash at high volume.
- Robust function calling.
- In long-form narrative writing, Claude still has a more natural voice.
- In complex code, Codestral / Claude sometimes surprise.
When to choose: default in Gemini Enterprise. Cases: enterprise agents, RAG, multimodal, Workspace integrations. It’s the “first model to try” for any new case.
Claude Sonnet 4.6 / Opus 4.7 — when to choose
- Long-form writing with natural tone in PT-BR, especially in deliberative content.
- Reasoning in long chains: legal analysis, technical opinion, detailed comparison.
- Robust tool use, especially in multi-step chains.
- Constitutional AI: conservative refusal, useful in enterprise environments.
- No native video multimodal (image only).
- Does not access Workspace natively.
- Opus cost high for volume.
- Opus latency higher than Gemini Pro.
When to choose: cases where writing or deep reasoning dominates — drafting legal opinions, long comparative analysis, technical writing agent, brand copy.
Llama 4 — when to choose
- Open weights: runs on-premise, in a dedicated VPC, on your own GPU.
- Customizable: real fine-tuning (LoRA, full).
- Restrictive sector compliance: sectors where data cannot leave your own infrastructure.
- Predictable cost: infrastructure license, no per-token billing.
- Quality below Gemini Pro / Claude on complex reasoning (depends on size chosen).
- Operations require a mature MLOps team.
- Limited multimodal.
When to choose: defense, government, critical infrastructure, sensitive healthcare with no-exfiltration requirement. Projects with heavy fine-tuning. Companies with idle GPUs wanting to make use of them.
Mistral Large 3 / Codestral — when to choose
- Cost: typically 30–50% cheaper than peers at the same quality tier.
- Codestral specialized in code, great for dev agents.
- European multilingual: strong in FR, DE, IT, ES.
- Open weights in smaller models: on-prem option.
- PT-BR slightly below Gemini/Claude in fluency.
- Multimodal at early stage.
When to choose: high volume with cost sensitivity, where “good enough” is acceptable. Continuous dev agents. Operations in European markets.
Decision by use case
| Use case | Recommended model |
|---|---|
| Standard enterprise RAG agent | Gemini 2.5 Pro (Flash for routing) |
| Multimodal (PDF + image + audio) | Gemini 2.5 Pro |
| Long legal analysis | Claude Opus 4.7 |
| Brand copy drafting | Claude Sonnet 4.6 |
| High-volume triage | Gemini Flash or Mistral Large |
| Code review / dev assistant | Claude Sonnet 4.6 or Codestral |
| Defense / mandatory on-prem | Llama 4 |
| Native Workspace agents | Gemini (only option) |
| Heavy fine-tuning | Llama 4 or Gemini (Vertex tuning) |
Advantage of Vertex Model Garden
Even if you choose Claude or Llama, using them via Vertex Model Garden is the difference between a unified governance layer and five scattered contracts.
Using via Vertex Model Garden brings:
- Unified billing on Google Cloud.
- Centralized logs and audit.
- Data residency in
sa-east1. - IAM and VPC Service Controls applied.
- Integration with Vertex AI Pipelines, Endpoints, Evaluation.
Versus consuming directly from Anthropic/Meta: you lose the unified governance layer. For enterprises, the overhead is worth it.
What changed in 2026 vs 2024
- The quality gap between the top-3 (Gemini, Claude, GPT) narrowed in general use — differentiation lies in specific cases.
- Llama 4 reached a competitive level in reasoning.
- Mistral consolidated its position as “cost-effective alternative without heavy sacrifice”.
- Real multimodal became a decisive criterion — Gemini leads, others catch up.
- Overall cost dropped 60–80% in 2 years. “Which model” decision is less about budget, more about fit.
How to evaluate in your company
Real cases from your product, not synthetic examples. Without this, the evaluation won't generalize.
Gemini Pro, Claude Sonnet and one more depending on context (Llama, Mistral, Codestral).
Faithfulness, relevance, completeness, safety. Each dimension scored 0 to 5 — without a rubric, "gut feeling" wins.
There's no absolute "best" — there's a Pareto frontier. The chosen model comes off it, justified.
The spreadsheet becomes a decision record. In 6 months, when the next model "changes everything", you revisit the same spreadsheet — not the LinkedIn thread.
Details in agent evaluation in production and embeddings and semantic search.
Which model fits your cases?
In Autenticare projects, the standard is Gemini Enterprise as the product layer + Vertex Model Garden when another model adds value. We bring the rubric and the evaluation spreadsheet.