{"slug": "gpt-5", "title": "GPT‑5.", "summary": "OpenAI released GPT‑5, a sparse mixture-of-experts model that activates only 15% of parameters per forward pass, reducing first-token latency from 0.7s to 0.4s and boosting throughput by 60%. Input costs dropped to $1.20 per million tokens from $3.00, and output costs to $4.80 from $6.00, while accuracy on standard evals like MMLU (89.3% vs 90.1%) and GSM8K (94.7% vs 95.2%) declined by under one percent. The API also defaults to speculative decoding for lower perceived latency, and Pro tier rate limits are doubled.", "body_md": "# GPT‑5.\n\nThe architecture shift is the story. They've gone with a sparse mixture-of-experts variant that only activates around 15% of parameters per forward pass. My latency numbers show first-token time dropped from 0.7s (GPT‑5) to 0.4s, and sustained throughput is up roughly 60% in my streaming setups. For the price tier I'm on:\n\n**Input cost:**$1.20 per million tokens (GPT‑5 was $3.00)** Output cost:**$4.80 per million tokens (GPT‑5 was $6.00)** MMLU:**89.3% vs 90.1%** GSM8K reasoning:**94.7% vs 95.2%** HumanEval pass@1:**86.5% vs 87.1%\n\nThe delta in accuracy is under one percent on standard evals, which in practice means I can't tell the difference on\n\n[RAG](/en/tags/rag/)pipelines, summarization, or multi-turn dialogue. The big win is the cost: for my daily API bill, I'm getting about 2.5x more completions for the same spend.\n\nWhat caught me off guard was the default speculative decoding mode. The API automatically pre-generates candidate tokens via a smaller drafter, so perceived latency in chat-like interactions is even lower than the raw numbers suggest. No config change needed—just hit the `gpt-5.6`\n\nendpoint.\n\nFor anyone running cost-sensitive pipelines or real-time features, this is the first frontier model that doesn't make me recalculate margins every deployment. Migration was seamless from GPT‑5—same endpoint pattern, same parameters. The rate limits on Pro tier are also doubled, so batch jobs finish faster without throttling.\n\nWorth spinning up a test run if you were sitting on the fence due to budget. The price-performance curve finally bends where it matters.\n\n[Next Meta's AI Spending Cuts Free Cash Flow by 91% →](/en/news/4439/)", "url": "https://wpnews.pro/news/gpt-5", "canonical_source": "https://promptcube3.com/en/news/4445/", "published_at": "2026-07-30 19:35:34+00:00", "updated_at": "2026-07-30 19:43:54.536803+00:00", "lang": "en", "topics": ["large-language-models", "ai-products", "ai-infrastructure"], "entities": ["OpenAI", "GPT‑5"], "alternates": {"html": "https://wpnews.pro/news/gpt-5", "markdown": "https://wpnews.pro/news/gpt-5.md", "text": "https://wpnews.pro/news/gpt-5.txt", "jsonld": "https://wpnews.pro/news/gpt-5.jsonld"}}