In 2026 OpenAI's GPT-4o and Anthropic's Claude remain the two strongest general-purpose LLM stacks. Both run over a stateless HTTP API, both stream tokens, both support tool/function calling, and both have an OpenAI-compatible interface. What decides the choice is the workload, latency needs, ability to pay and model behavior.
| Model | Input / 1M | Output / 1M | Cache read / 1M | Cache write / 1M | Context |
|---|---|---|---|---|---|
| GPT-5.6 Luna (codexkey) | $0.04 | $0.2 | $0.02 | $0.06 | No data |
| GPT-4o (OpenAI) | $2.50 | $10.00 | No price | No price | 128K |
| GPT-4o-mini (OpenAI) | $0.15 | $0.60 | No price | No price | 128K |
| o1 (OpenAI) | $15.00 | $60.00 | No price | No price | 200K |
Prices change. Before you plan a budget, check the current codexkey page and OpenAI's pricing page.
Both stacks cover the same set of features (chat, tools, streaming, vision). The difference shows up under load and on hard tasks.
| Capability | Claude via codexkey | OpenAI |
|---|---|---|
| Long-context coding | Excellent (200K) | Good (128K) |
| Tool / function calling | Yes (native + OpenAI-compat) | Yes |
| Streaming SSE | Yes | Yes |
| Vision (images) | Yes | Yes |
| Realtime audio | No | Yes (Realtime API) |
| Image generation | No | Yes (DALL·E) |
| Fine-tuning | No | Yes |
| RU/CIS payments (SBP, crypto) | Yes | No |
| Pay-as-you-go, no minimums | $1 minimum | $5 minimum, tiers |
codexkey has an OpenAI-compatible endpoint at https://api.codexkey.online/v1. Most code written against the OpenAI SDK will run after you change two values:
from openai import OpenAI
client = OpenAI(api_key="sk-...")
resp = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Hello"}],
)from openai import OpenAI
client = OpenAI(
api_key="sk_cdx_...",
base_url="https://api.codexkey.online/v1",
)
resp = client.chat.completions.create(
model="claude-sonnet-5",
messages=[{"role": "user", "content": "Hello"}],
)import OpenAI from 'openai'
const client = new OpenAI({
apiKey: process.env.CODEXKEY_API_KEY,
baseURL: 'https://api.codexkey.online/v1',
})
const resp = await client.chat.completions.create({
model: 'claude-sonnet-5',
messages: [{ role: 'user', content: 'Hello' }],
})On short prompts (under 1k input tokens) with short answers, GPT-4o from OpenAI is usually faster by TTFT: 200-400 ms against 350-600 ms for Claude Sonnet. Once a prompt grows past 8k tokens, Claude's optimized long-context path narrows the gap or even reverses it. In agentic workloads with loops of several tools, total time is set by tool execution rather than the model, so the difference in a single call rarely matters.
Both APIs offer tool/function calling. OpenAI's `tools` parameter validates JSON Schema strictly; Claude accepts the same format through codexkey's OpenAI-compatible interface, while native Anthropic clients get `tool_use` blocks. Structured outputs (JSON mode) are on par: Claude follows a JSON schema via `response_format`, and on benchmarks such as JSONSchemaBench its success rate is close to GPT-4o. The main difference is caution: Claude will turn down a malformed schema where GPT-4o sometimes invents JSON that merely looks valid.
Per-token prices of Claude Sonnet 4.6 and GPT-4o are within 10% of each other. Other factors weigh more: prompt caching (Claude saves up to 90% on cached input), the batch API (both give 50% off asynchronous requests) and prompt size (Claude's wide context spares you extra retrieval round-trips). For users in Russia and the CIS, going straight to OpenAI is often impossible because of payment restrictions, and paying through SBP, crypto and cards in codexkey makes Claude a practical default.
Take Claude (via codexkey) if you need a very long context, careful tool use in agents, precise code edits, payment from Russia and the CIS, or separate billing with no Anthropic account.
Take OpenAI directly if you need realtime audio (Realtime API), DALL·E image generation, fine-tuning, or if everything you have is already built on the Assistants/Responses API.