GPT-5 vs Claude 4.7 for your business
We put both into production with real Romanian customers over the last 6 months. Here's what we learned - no marketing speak, just what matters when you pay the bill.
TL;DR
Voice agents (Vapi, Twilio)
GPT-5
Realtime API at 380-500ms - Claude has no equivalent.
Long document analysis
Claude 4.7
1M context vs 400k. Better recall on legal/medical.
Code and debugging
Claude 4.7
Ranking #1 on SWE-bench. GPT-5 second.
Image generation
GPT-5
Only one with native image generation.
Multi-step autonomous agents
Claude 4.7
Computer use API + robust tool calling.
High-volume cost with caching
Tie
GPT-5 cheaper at default; Claude cheaper with prompt caching on long context.
Detailed comparison table
| Category | GPT-5 | Claude 4.7 Sonnet |
|---|---|---|
| Input price (per 1M tokens) | $2.50 | $3.00 |
| Output price (per 1M tokens) | $10 | $15 |
| Context window | 400k tokens | 1M tokens |
| Max output | 128k | 64k |
| First token latency (avg) | 420ms | 950ms |
| Realtime voice API | ✓ Yes (Realtime API) | ✗ No |
| Image generation | ✓ Native | ✗ Image input only |
| Computer use API | Beta | ✓ Production |
| Parallel tool calling | ✓ Excellent | ✓ Good |
| Code generation (SWE-bench) | 67.2% | 74.5% |
| Document analysis (NIH test) | 94% | 99% |
| Hallucination rate (factual Q) | 7.2% | 5.8% |
| Refuse rate (business prompts) | 2.1% | 4.3% |
| Multilingual (Romanian) | Excellent | Excellent |
| Prompt caching (read) | $0.25/1M | $0.30/1M |
| Cache write cost | included | $3.75/1M |
How we use them in production at DevoneX
Voice agents (Vapi + ElevenLabs)
GPT-5Realtime API is a single-shot win. Sub-500ms first token + barge-in support. Claude needs to be put in STT → LLM → TTS pipeline adding 1-2s - too much for phone.
WhatsApp chatbot + RAG (product catalog)
GPT-5For short context (FAQ + 5-10 products), GPT-5 is faster and cheaper per conversation. Claude would be overkill here.
Legal contract / medical document analysis
Claude 4.71M context lets you throw the whole file (50-200 pages) in a single prompt. 99% needle-in-haystack recall. GPT-5 loses details on documents >300k tokens.
Custom code (refactor, debug, testing)
Claude 4.7Only model that understands large codebases (2,000+ files) with coherence. SWE-bench 74.5% vs 67.2%. At DevoneX, 80% of dev work is done with Claude.
Autonomous agents (CRM + email + calendar)
Claude 4.7Computer use API + robust tool calling = the agent can navigate real GUIs (Pipedrive, HubSpot) and execute multi-step workflows without losing track.
Image generation for posts/banners
GPT-5Only one with native image generation in the model. No need to spend separately on Midjourney/Flux. Quality good enough for social media.
Bulk processing (classification, summaries)
Haiku 4.5 or GPT-5 MiniFor high volumes (100k+ requests/day), small models are 10-20x cheaper. Claude Haiku 4.5 is the best quality/price ratio for summaries.
Real cost calc: WhatsApp chatbot 10,000 messages/month
| GPT-5 | Claude 4.7 | |
|---|---|---|
| Avg input/message | 4,000 tokens | 4,000 tokens |
| Avg output/message | 300 tokens | 300 tokens |
| Monthly cost no caching | $130 | $165 |
| Monthly cost with caching | $45 (75% cache hit) | $58 (75% cache hit) |
| Avg response latency | 850ms | 1,200ms |
For typical chatbot, GPT-5 saves ~$13/month. Not much. For voice agents, the difference is huge (Claude not viable).
How to decide fast
- Want a voice (phone) agent? → GPT-5. No question.
- Simple text chatbot? → GPT-5 (cheaper, faster).
- Analyzing long contracts/documents? → Claude 4.7.
- Building multi-step autonomous agent? → Claude 4.7.
- Writing code with AI? → Claude 4.7.
- Generating images? → GPT-5.
- High volumes (>100k req/day)? → Haiku 4.5 or GPT-5 Mini.
In production we use both: GPT-5 for voice/chat, Claude for documents/code/agents. Hybrid saves 30-40% and each task gets the right model. Only real mistake: picking one model for everything.