👸 ChatGPT 5

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ChatGPT 5, explained

What changed. OpenAI’s GPT-5 is positioned as its most capable coding and agent model so far. It adds finer control over responses, longer context, and stronger multi-tool execution. That puts it in direct competition with Anthropic’s Claude 4 family and Google’s Gemini 2.x line targeted at agentic use. OpenAI says GPT-5 is rolling into ChatGPT business tiers and the API, with three sizes for developers. OpenAI provides details on features, context, and pricing on its product and developer pages.

What GPT-5 adds

  • Response control. New verbosity parameter and a minimal reasoning option so devs can trade depth for speed when they do not need long chain-of-thought. OpenAI also added custom tools so the model can call tools with plain text, optionally constrained by grammars.

  • Bigger jobs. Listed 400K token context and up to 128K output tokens on the site’s model picker, plus three sizes: GPT-5, 5-mini, and 5-nano.

  • Agent execution. OpenAI highlights improved multi-step tool use and parallel chains. On SWE-bench Verified, OpenAI reports 74.9 percent for GPT-5 vs 69.1 percent for its prior o-series baseline.

  • Pricing signals. Site copy lists GPT-5 at about $1.25 per million input tokens and $10 per million output tokens with lower prices for mini and nano. Treat pricing as subject to change and check the platform docs at time of use.

How it stacks up

Anthropic Claude 4. Claude Opus 4 and Sonnet 4 are hybrid reasoning models that can switch between fast replies and extended thinking. Anthropic keeps familiar API prices, with Sonnet in the mid tier and Opus at the high end. Anthropic has also shipped Claude 3.7 Sonnet with user-tunable “thinking time.” Anthropic publishes current consumer and API prices and makes models available on its API, Amazon Bedrock, and Google Vertex AI.

Google Gemini 2.x. Google’s Gemini 2.0 and 2.5 updates emphasize agent tooling, multimodality, and very large windows. Google’s notes reference up to 1M token context in the app and API variants, with developer pricing pages listing token rates for 2.5 Pro and 2.5 Flash. If you deploy on Vertex AI, confirm the SKU since rates vary by model and prompt length.

Meta Llama 4. Open-weight, natively multimodal releases like Llama 4 Scout and Maverick aim for long context and broad inference options. Strengths are cost control and on-prem deployment, with trade-offs in guardrails and support.

xAI Grok 3. Emphasizes long-horizon reasoning using reinforcement learning. xAI cites high Chatbot Arena Elo and positions Grok 3 Mini for lower cost tasks. Availability and enterprise controls are improving but still maturing.

DeepSeek R-series and V-series. DeepSeek pushed low-cost reasoning with R1 and keeps iterating with R1-0528 and V3.1. Docs and reporting note competitive reasoning at aggressive price points, plus recent pricing updates announced for September.

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Key specs at a glance

  • Context window. GPT-5 lists 400K. Gemini offers up to 1M in certain tiers. Claude advertises 200K on 3.5 and higher on 4 with extended thinking. Llama 4 details vary by distribution. Check the specific runtime before committing.

  • Agent features. GPT-5 adds custom tools and better multi-tool chains. Gemini 2.x highlights built-in tool use and Live. Claude 4 introduces hybrid fast or deep thinking modes.

  • Indicative API pricing. GPT-5 page shows around $1.25 input and $10 output per million tokens, with cheaper mini and nano. Google’s developer pricing lists Gemini 2.5 Pro and 2.5 Flash token rates and caching. Anthropic lists Sonnet at roughly $3 input and $15 output, Opus at $15 input and $75 output. Verify current rates before budgeting.

Where GPT-5 is strongest

  • Coding and software tasks with long, tool-heavy chains and UI generation. OpenAI cites stronger coding benchmarks and more reliable multi-step execution.

  • Response steering when teams need short, consistent answers at scale using verbosity and minimal reasoning controls.

Where competitors lead today

  • Ultra-long context and deep Google ecosystem ties favor Gemini in some enterprise stacks.

  • Visible or user-tunable thinking and conservative defaults give Claude appeal for regulated workflows.

  • Open deployment and cost control favor Llama 4 for teams that need on-prem or custom fine-tuning.

  • Aggressive price and rapid iteration make DeepSeek attractive for cost-sensitive pilots.

How to use this as an investor

  • Map workloads to model strengths. If your portfolio company builds complex coding agents, test GPT-5 and Claude Opus 4 head to head. If you need tight Google stack integrations and giant windows, trial Gemini 2.5 Pro in Vertex AI. Cite OpenAI, Anthropic, and Google’s own docs in RFPs to avoid vendor spin.

  • Budget using live rates. Token prices change. Lock in your target model and prompt length, then pull current prices from the vendor’s pricing page before approvals.

  • Design for portability. Favor tools and orchestration that can switch between GPT-5, Claude, and Gemini to avoid being trapped by a single vendor’s price or policy change.

  • Track policy exposure. Public sector deals and safety changes can shift usage limits or costs. Monitor vendor blogs and enterprise updates.

Sources: OpenAI product and developer posts on GPT-5, Anthropic model and pricing pages, Google Gemini 2.x release notes and developer pricing, Meta’s Llama 4 blog, xAI’s Grok 3 post, DeepSeek docs and recent Reuters coverage.

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