GPT-4o
gpt-4ogpt-4o-2024-11-20openai-gpt-4o-2024-11-20- 🧠 OpenAI's omni flagship reasoning across text, vision, and audio.
- 🆕 The November 2024 update sharpened instruction-following, coding, and STEM.
- 👁️ Single model trained end-to-end across text, vision, and audio.
- 📏 128K-token context window with text and image input.
- 🔧 Supports function calling, structured outputs, and web search.
- 📚 Knowledge cutoff extended to June 2024 in this version.
- 🌐 Strong multilingual gains versus earlier GPT-4 models.
- 🎯 Balanced general-purpose model widely used across everyday tasks.
OpenAI is an American artificial intelligence research organization headquartered in San Francisco, structured as both a for-profit public benefit corporation and a nonprofit foundation. The lab developed the GPT family of large language models, the DALL-E image generation…
Explore 29 more models by OpenAI →GPT-4o ("o" for "omni") is OpenAI's flagship from the GPT-4 generation, accepting text and image inputs and producing text outputs including structured outputs. Architecturally it marked a shift: OpenAI trained a single new model end-to-end across text, vision, and audio, rather than feeding a separate vision encoder into a language model. This catalog entry refers to the 2024-11-20 revision.
Against its own predecessors, OpenAI reports that GPT-4o matches GPT-4 Turbo-level performance on text, reasoning, and coding while setting new high watermarks on multilingual, audio, and vision capabilities—running faster and at lower API cost than GPT-4 Turbo. The 2024-11-20 update specifically made the model, per OpenAI's release notes, "smarter across the board," with more up-to-date knowledge (training cutoff moved from November 2023 to June 2024), deeper image analysis, and gains on academic evaluations like GPQA, MATH, and MMLU.
For context on later siblings, OpenAI reports that on its SWE-bench Verified, GPT-4.1 completed 54.6% of tasks versus 33.2% for GPT-4o (2024-11-20). Within this family, GPT-4o has since been succeeded by reasoning-focused flagships such as GPT-5.2, GPT-5.4, and GPT-5.5, alongside smaller options like GPT-4o Mini.
GPT-4o is a multimodal model accepting text and image inputs, used for multimodal tasks, function-calling workflows, and web-search-augmented applications.
This About section is AI-generated from public sources via VeniceStats + Venice inference, with no human editing. It may contain inaccuracies.
| Seller | Reputation↓ | Routing | Input $/M | Cached $/M | Output $/M | Categories | API |
|---|---|---|---|---|---|---|---|
| Venice.ai Proxy 0x1f22…18c9 | 70.55 | gated | $1.5625 | $1.5625 | $6.25 | chat,vision,multimodal,web-search | openai-chat-completions |
| Fire Ant 🔥🐜 0xbe05…bc5d | 50.00 | gated | $2.7198 | $2.7198 | $10.8792 | — | — |
| Meridian AI 0x8c8c…06f5 | 44.01 | gated | $0.5373 | $0.5373 | $2.1492 | chat,coding,reasoning | openai-chat-completions |
| antseed-neon-puma-944e 0x6650…944e | 35.09 | gated | $1.0656 | $1.0656 | $4.2625 | chat | openai-chat-completions |
| Leftermute 0x388b…5389 | 28.39 | gated | $0.2841 | $0.2841 | $1.1363 | chat,coding,json,tools | openai-chat-completions |
| Apex TEE Test 0xe672…7955 | 15.22 | gated | $0.4628 | $0.2805 | $1.8513 | chat,tasks,writing,study,translate,vision,multimodal,agents | openai-chat-completions |
"Best price" and the seller table are live AntSeed catalog data (advertised $/1M tokens — or $ per generated image for unit-billed image models — not settled amounts). Reputation = buyer trust score (0-100, the AntSeed SDK's own formula). "Routing" = the SDK's default buyer routing (what the VPR desktop app ships with): a trust ≥ 60 gate on the effective reputation, then cheapest-first among routable sellers; live failover state (per-peer cooldowns) is buyer-side runtime and not included. Model knowledge (TLDR, provider, About) via the VeniceStats enrichment layer. Advertised catalog, not the model used in any specific purchase. "Usage on AntSeed" counts only settlements whose buyers share the per-model split on-chain (metadata v2/v3, opt-in), so every usage figure is a lower bound.