What We Actually Run
Claude vs GPT vs Gemini in production
We've shipped production systems on Claude and GPT. Here's the honest call on five platforms — latency, cost, vendor risk, and when we'd pick each one.
No "best overall" verdict. The best model is the one that hits your latency budget at your cost ceiling on your workload. We benchmark on your data before we lock the choice in.
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Every project, signed up front
Why this is the right kind of proof →
Claude (Sonnet 4.6 / Opus 4.7)
AnthropicLatency
Low–medium. Streaming first token ~400ms. Cache hits cut latency 5–10x.
Cost
Sonnet ~$3 in / $15 out per 1M tokens. Opus ~$15 / $75. Prompt caching cuts input cost up to 90%.
Multimodal
Vision (images, PDFs). No audio in/out yet.
Tool-use
Best-in-class. Stable function-calling, parallel tools, computer use.
Vendor risk
Single vendor, no on-prem. Strong API uptime. SOC 2 Type II.
We’d pick it when
Default. Long-context reasoning, code, agent loops, structured extraction. We ship Claude on most builds.
GPT (GPT-5 / 4o / o-series)
OpenAILatency
Low. 4o streams fast. o-series adds reasoning latency (3–30s) on hard tasks.
Cost
4o ~$2.50 in / $10 out per 1M. GPT-5 higher. Cheap mini variants for high-volume.
Multimodal
Vision + audio in/out. Realtime API for voice agents.
Tool-use
Excellent. Mature function-calling, structured outputs (JSON schema enforced).
Vendor risk
Single vendor. Azure OpenAI deployment available for enterprise governance.
We’d pick it when
Voice agents, vision-heavy pipelines, when GPT-5 reasoning beats Claude on a benchmark we ran on your data.
Gemini (2.5 Pro / Flash)
GoogleLatency
Low. Flash is the cheapest fast model on the market right now.
Cost
Pro ~$1.25 in / $5 out per 1M. Flash <$0.50 in. Cheap, fast, good for high-volume.
Multimodal
Vision + audio + 1M-token context window (largest in production).
Tool-use
Good. Function-calling stable; not as battle-tested as Claude/GPT for agent loops.
Vendor risk
Single vendor. Tied to Google Cloud for enterprise. HIPAA via Vertex AI.
We’d pick it when
High-volume document processing where 1M context replaces RAG. Cost-sensitive pipelines. Vertex AI shop.
Llama (3.3 70B / 3.1 405B)
Meta (open-weights)Latency
Variable. AWS Bedrock or Together AI: ~500ms first token. Self-hosted: depends on your GPU.
Cost
Bedrock: $2–8 / 1M tokens. Self-host: GPU rental + ops cost. Free weights.
Multimodal
3.2 has vision. No audio. No native tool-use; needs prompting framework.
Tool-use
Workable but you build the scaffolding. Not as reliable as closed models.
Vendor risk
Lowest. Open weights mean no provider lock-in, no surprise deprecation, on-prem possible.
We’d pick it when
Data residency or air-gapped deploys. When you need provable on-prem AI for compliance. We have not shipped on-prem Llama in production yet — be honest with you about that.
Mistral (Large 2 / Codestral)
Mistral AILatency
Low. EU-hosted option for data residency.
Cost
Large 2 ~$2 in / $6 out per 1M. Cheaper than GPT/Claude for similar tier.
Multimodal
Vision on Pixtral. No audio.
Tool-use
Decent function-calling. Codestral is strong on code-specific tasks.
Vendor risk
Single vendor, EU-domiciled. Open-weights for some models.
We’d pick it when
EU data residency hard requirement. Cost-sensitive code-gen. Edge cases where Claude/GPT both fail and we need a third opinion.
The honest call
- Default: Claude Sonnet 4.6 with prompt caching. Best reasoning-to-cost ratio for most workloads.
- High-stakes reasoning: Claude Opus 4.7 or GPT-5 with extended thinking. Slow, expensive, worth it on $10K+ decisions.
- Voice or vision-heavy: GPT-4o Realtime or Gemini 2.5 Pro. Claude doesn't do audio yet.
- High-volume cheap inference: Gemini Flash or Claude Haiku. Pennies per request.
- On-prem / air-gapped: Llama 3.3 70B on your hardware. Hardest to operate, only choice if data can't leave your network.
We build provider-agnostic from day 1: a thin abstraction over the model API so we can swap Claude → GPT → Gemini in a config flip. If a provider deprecates a model, your platform doesn't care.
Want the call on your workload?
Free 45-min architecture audit. We benchmark Claude, GPT, and Gemini on your actual data and tell you which one wins on latency, cost, and accuracy. No sales pitch.