GPT-5 in 2026: Features, Benchmarks, Pricing, and How to Use It in Slack
GPT-5 features in 2026: benchmarks vs Claude and Gemini, model variants (mini, pro, thinking), API pricing, and how to use GPT-5 inside Slack with Runbear.
GPT-5 is OpenAI's flagship language model, generally available since August 2025. It runs as the default ChatGPT model across all plans and ships in four API variants: gpt-5, gpt-5-mini, gpt-5-pro, and a 'thinking' mode picked automatically by a router. Per OpenAI's GPT-5 system card, the model hallucinates roughly 80% less than GPT-4o and scores 74.9% on SWE-bench Verified, the highest result of any major foundation model in 2026.
May 2026 Update
GPT-5 has been generally available since August 2025 and is now nine months into production. ChatGPT users got a smarter default model. Developers got three API tiers (mini, standard, pro) plus a router that picks 'thinking mode' automatically when a question is hard.
Runbear now runs on GPT-5 via the OpenAI API, powering context assembly and automated actions across 2,000+ connected tools in Slack. The improvement in instruction following (GPT-5 scored 99% on COLLIE vs earlier baselines) shows up directly in how precisely Runbear agents route requests, draft responses, and take action. See the Aloware case study for a real example: a Zoom transcript agent that logs CRM deals with a single emoji, built on this model layer.
The rest of this post covers everything you need to know: what GPT-5 is, how it compares to prior models, availability, pricing, and what it means for ops teams using AI in Slack.
What Is GPT-5?
GPT-5 is OpenAI's most advanced language model yet—built to be more robust, reliable, and helpful than any of its predecessors. It delivers state-of-the-art accuracy on real-world tasks while significantly reducing hallucinations and deceptive responses. Designed with real workflows in mind, it powers real-time AI agents, developer tools, and enterprise copilots across platforms like Slack, HubSpot, and Microsoft Teams.
Key Improvements in GPT-5
State-of-the-art performance on leading AI benchmarks:
Fewer hallucinations: GPT-5 responses are up to 80% more factual than previous models like GPT-4o or o3.
Safer and more honest: Reduced deceptive behavior in edge cases or underspecified prompts.
Improved instruction following: More reliable for agents, workflows, and multi-step tasks.
Multimodal reasoning: Enhanced capabilities across text, image, video, and charts.
What makes GPT-5 different?
Rather than a single monolithic model, GPT-5 introduces a router-based model architecture:
GPT-5: Fast, general-purpose response generation
GPT-5 Thinking: Deep reasoning for complex tasks
GPT-5 Pro: Long-context, high-precision model tuned for advanced applications
These models are deployed intelligently behind the scenes, depending on query difficulty, user intent, and context. This allows GPT-5 to feel both fast and deeply capable—delivering expert-level answers where needed, while still handling everyday queries with speed and grace.
Why GPT-5 Feels More Trustworthy
GPT-5 doesn't just score higher—it acts more responsibly, explains better, and lies less.
Fewer Hallucinations, Even When Reasoning
GPT-5 is significantly more factually accurate:
80% fewer hallucinations than GPT-4o when reasoning ("thinking" mode)
~6x fewer factual errors on open-ended benchmarks like LongFact and FActScore
Whether answering complex science questions or writing long-form content, GPT-5 produces more grounded, verifiable answers.
More Honest When Tasks Can't Be Done
GPT-5 is trained to say “I don't know” when the task is impossible, underspecified, or missing key inputs:
In deception benchmarks, GPT-5 reduced false claims from 4.8% (o3) to just 2.1%
In multimodal tests with missing images, GPT-5 hallucinated only 9% of the time, compared to o3's 86.7%
This means better transparency and fewer misleading answers.
Safety with Nuance
With GPT-5, OpenAI introduced safe completions — a new training paradigm that:
Avoids over-refusing ambiguous prompts
Answers safely when possible
Explains why a task can't be done, instead of deflecting
This enables GPT-5 to be safer without feeling frustratingly limited.
Less Sycophantic, More Thoughtful
GPT-5 feels less like a cheerleader and more like a thoughtful colleague:
Sycophantic replies reduced by over 50%
Clearer follow-ups and fewer unnecessary flattery
The result? Conversations that are more productive, respectful, and grounded in truth.
Evaluations: How Smart Is GPT-5?
Math Mastery
GPT-5 dominates math evaluations:
AIME 2025: 94.6% (no tools) — new state-of-the-art.
HMMT: 96.7% (no tools), 100% (with tools).
FrontierMath: 26.3% → 32.1% with tool support.
GPQA (PhD-level): 88.4% (no tools) → 89.4% (with thinking).
Real-World Coding
On practical software engineering and code editing benchmarks:
SWE-bench Verified: 74.9% accuracy (GPT-5) vs 69.1% (OpenAI o3) and 30.8% (GPT-4o).
Aider Polyglot: 88% accuracy (GPT-5), far ahead of all previous models.
These improvements suggest GPT-5 can handle significantly more complex engineering workflows.
Instruction Following & Tool Use
GPT-5 is vastly better at multi-step reasoning and agentic behaviors:
Scale MultiChallenge (multi-turn): 69.6% vs GPT-4o's 40.3%.
BrowseComp (search + browsing): 54.9% vs 49.7%.
COLLIE (freeform following): 99.0% accuracy.
It not only follows instructions better but coordinates tools to complete tasks more reliably.
Multimodal Understanding
GPT-5 outperforms on visual, video, and diagram-based tasks:
MMMU: 84.2% vs GPT-4o's 72.2%.
ERQA: 65.7% vs 35.2% (GPT-4o).
CharXiv Reasoning: 81.1% vs 58.8%.
This means stronger capabilities for interpreting images, visual documents, and presentations.
Health Conversations
GPT-5 is the most accurate and least hallucinatory model for medical applications:
HealthBench: 67.2% vs GPT-4o's 32.0%.
Hallucination Rate: 1.6% (with thinking), down from GPT-4o's 15.8%.
Its performance on sensitive conversations makes it viable for high-trust settings.
Economically Valuable Tasks
GPT-5 beats both o3 and ChatGPT Agent on complex, real-world professional tasks:
Outperforms in law, logistics, sales, and engineering.
Achieves 47.1% wins over industry experts in internal benchmarks.
This suggests GPT-5 is not just smarter — it's more useful in economically important domains.
Faster, More Efficient Thinking
GPT-5 achieves better performance with fewer output tokens than OpenAI o3:
50–80% fewer tokens across reasoning, coding, and scientific benchmarks.
Better performance with less effort and latency — critical for real-time use.
Detailed Benchmarks
Who is GPT-5 for?
Business leaders & teams: Analyze documents, monitor operations, and plan strategy with better context awareness and safer outputs.
Developers: Use GPT-5 to generate production-quality frontends, debug codebases, and automate software tasks.
Healthcare professionals & patients: Understand diagnoses and treatment options with greater clarity and proactive reasoning (GPT-5 scored highest ever on HealthBench).
Knowledge workers & writers: Get help crafting thoughtful reports, articles, or even poetry—with deeper structure and emotional impact.
Real-World Use Cases with Runbear
Slack-based AI teammates: Use GPT-5 to power intelligent agents in Slack that summarize daily updates, answer policy questions, and track tasks with long-context memory.
AI-driven sales agents: Combine GPT-5 with your CRM via Runbear to generate weekly client reports, respond to customer FAQs, and prep for sales calls with context from past interactions.
Meeting intelligence agents: Let GPT-5 summarize meetings, surface action items, and connect them to your docs and workflows in Notion or Confluence.
Slack MCP integration: Connect GPT-5 agents to every tool in your stack through the Model Context Protocol — Runbear handles the context routing so your agents always have what they need before they respond.
Zoom transcript agents: Aloware built a GPT-5 powered agent on Runbear that watches Zoom transcripts and logs CRM deals automatically — triggered by a single emoji in Slack. A live production example of what’s possible today.
Availability & Pricing
GPT-5 is now available across ChatGPT, the OpenAI API platform. Here's how you can access it and what it costs.
Access Options
ChatGPT
Rolling out now to Plus, Pro, Team, and Free users.
Enterprise and Education access starts in one week.
Available in the Codex CLI for Pro, Plus, and Team users.
OpenAI API
Available in three model sizes: gpt-5 (standard, general-purpose), gpt-5-mini (fast and cost-optimized), and gpt-5-pro (long-context, high-precision for complex workflows)
Supports function calling, tool use, vision, structured outputs, and streaming — with a 128K context window across all model sizes
Non-reasoning version available as gpt-5-chat-latest
GPT-5 sets a new standard in reasoning, reliability, and real-world AI performance. With better benchmarks and lower hallucination rates, it's shaping up to be the most capable foundation model to date.
Runbear agents are powered by GPT-5 via the OpenAI API. That means every context assembly, Slack response, and automated action your team runs through Runbear benefits from GPT-5's improved reasoning and lower hallucination rates. Aloware built a Zoom transcript agent on Runbear that logs CRM deals in a single emoji — a live example of what GPT-5-powered agents can do in production.
Frequently Asked Questions
Is GPT-5 available now?
Yes. GPT-5 has been generally available since August 2025 across ChatGPT (Plus, Pro, Team, Free) and the OpenAI API. Enterprise and Education access followed shortly after launch. There is no waitlist.
How is GPT-5 different from GPT-4?
GPT-5 is significantly more accurate, more honest, and more capable at multi-step tasks than GPT-4 or GPT-4o. It hallucinates 80% less than GPT-4o in reasoning mode, scores 69.6% on multi-turn instruction benchmarks versus GPT-4o's 40.3%, and uses 50-80% fewer tokens to achieve better results. The router-based architecture (GPT-5, GPT-5 Thinking, GPT-5 Pro) also means the model automatically selects the right level of reasoning depth for each query.
Can I use GPT-5 in Slack?
Yes. Tools like Runbear bring GPT-5 into Slack natively — no separate app or context-switching required. Runbear agents use GPT-5 to answer questions, assemble context from 2,000+ connected tools, and take action (creating tickets, updating CRM records, routing requests) directly inside Slack. See how Slack MCP works with AI agents for more on the underlying protocol.
What does GPT-5 cost?
ChatGPT pricing in 2026: Free (limited GPT-5), Plus $20/month, Pro $200/month, Team $30/user/month, Enterprise (contact OpenAI). On the OpenAI API, gpt-5 is the standard tier, gpt-5-mini is the cost-optimized tier (roughly one-fifth the price of standard), and gpt-5-pro is the long-context, high-precision tier at a premium. See OpenAI's pricing page for current per-million-token rates.
How does GPT-5 handle hallucinations?
GPT-5 hallucinated 80% less than GPT-4o in reasoning mode and reduced false claims from 4.8% (o3) to 2.1% in deception benchmarks. On HealthBench, GPT-5 had a 1.6% hallucination rate versus GPT-4o’s 15.8%. It’s trained to say it does not know when information is missing rather than confabulate an answer — a meaningful shift for high-stakes workflows.
Can GPT-5 connect to my tools?
GPT-5 supports function calling, tool use, and structured outputs natively via the OpenAI API. When paired with an integration layer like Runbear, it can read from and act on 2,000+ tools including Google Drive, Notion, HubSpot, Linear, Salesforce, Fireflies, and more — all triggered from Slack. The Aloware case study shows exactly how this works end-to-end.
TL;DR. GPT-5 is OpenAI's flagship model, generally available since August 2025. It hallucinates roughly 80% less than GPT-4o, scores 74.9% on SWE-bench Verified, and ships in four variants (gpt-5, gpt-5-mini, gpt-5-pro, plus a 'thinking' mode) behind an automatic router. Gemini 2.5 Pro matches GPT-5 on API input price at the 200K context tier ($1.25 per million tokens, per Google AI), while Claude Opus 4.7 trades higher cost for longer context and stronger code review. Teams use GPT-5 in Slack via Runbear to ground answers in company context and act across 2,000+ tools.
ChatGPT 5 Features: What's New in the Consumer App
ChatGPT runs GPT-5 as its default model across the Free, Plus, Pro, Team, Enterprise, and Education plans. The key consumer-facing GPT-5 features are:
Automatic model routing: Free users get GPT-5 by default. Paid users can force 'GPT-5 Thinking' mode for harder questions.
Better long-form memory across sessions on Plus and above.
Image, chart, and PDF understanding in a single thread (multimodal by default).
Voice mode runs on GPT-5 for more natural pacing and fewer interruptions.
Custom GPTs and Projects persist instructions more reliably across turns.
Codex CLI access on Plus, Pro, and Team plans for terminal-native coding.
If you're comparing ChatGPT 5 features against Claude or Gemini for team rollouts, the consumer experience is only half the story. For deployment context, see ChatGPT in Microsoft Teams or compare it to using GPT-5 inside Slack via Runbear. The bigger question is how each model behaves when grounded in your company's tools and knowledge. That's where deployment matters more than the model.
GPT-5 vs Claude vs Gemini in 2026
The three frontier models trade off different strengths:
GPT-5 (OpenAI) leads on coding benchmarks (SWE-bench Verified 74.9%) and competition math (AIME 2025 94.6%), per OpenAI's GPT-5 system card. Strongest for general-purpose agent work where reasoning and tool use both matter. API input pricing sits at the low end of frontier models.
Claude Opus 4.7 (Anthropic) leads on long-context code review depth and on refusal/safety calibration. Higher API input cost than GPT-5 or Gemini.
Gemini 2.5 Pro (Google) offers the largest practical context window and matches GPT-5 on standard-tier input pricing ($1.25 per million tokens at the 200K context tier, per Google AI). Strong for tasks that span very large document sets.
For Slack-native team agents, model choice matters less than the orchestration layer. Runbear runs all three behind a single agent identity, so teams can swap models per use case without rebuilding workflows.
Matillion runs Runbear-deployed GPT-5 agents for its data engineering org: engineers ask their pipelines questions in natural language inside Slack and the agent answers in the channel where the work is already happening, without forcing a context switch.
Is GPT-5 better than Claude or Gemini?
GPT-5 leads on SWE-bench Verified (74.9%) and AIME 2025 (94.6%), per OpenAI's GPT-5 system card. Claude Opus 4.7 leads on long-context code review and refusal behavior. Gemini 2.5 Pro offers the largest practical context window at matched input pricing at the 200K tier ($1.25 per million tokens, per Google AI). For Slack-native team agents, model differences matter less than how grounded the agent is in your company data, which is the orchestration layer's job.
What are the new ChatGPT 5 features in 2026?
GPT-5 is now the default ChatGPT model across all plans. The 2026 consumer updates include automatic routing to 'thinking mode' for hard questions, better cross-session memory on paid plans, multimodal understanding (image, chart, PDF) in one thread, GPT-5-powered voice mode, and Codex CLI access for Plus and above.
Dust AI vs Runbear (2026): Internal AI Workspace or Customer-Facing Agents?
Dust and Runbear both connect AI agents to workplace tools. The choice that changes your implementation is whether your first problem is governing AI inside the company or deploying an agent into a customer-facing channel.
