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OpenAI's original GPT-4: a proprietary, text-only instruct model for professional writing, reasoning, and basic tool-calling workflows, with an 8k-token context window and a 2021 training cutoff.
Overview. GPT-4 is OpenAI's proprietary, closed-weight large language model, released in March 2023. It's a full-scale instruction-tuned model built for complex professional writing, reasoning, and tool-calling workflows, accessed through OpenAI's Chat Completions API. Developers reach for it when they need a general-purpose assistant with a long track record in production rather than the newest architecture.
Key strengths. GPT-4 was originally designed as a professional-grade writing and reasoning assistant, and remains capable on writing and communication-oriented tasks. It supports tool calling, letting it participate in workflows that invoke external functions. Its Artificial Analysis coding index (13.1) trails the higher-scoring GPT-4.1-mini variant (20.2), though it remains ahead of the smaller GPT-4.1-nano (11.1), so it is not the strongest choice for code-heavy tasks even though it remains capable of general-purpose reasoning and complex instructions.
When to use it. Use GPT-4 for complex professional writing, drafting, and reasoning tasks where an interactive, few-second response time is acceptable. It fits workflows that need basic tool-calling support but don't require parallel tool calls, since that capability arrived in later OpenAI releases. It's a reasonable default for general assistant use cases that don't hinge on the newest benchmark performance or multimodal input.
Limitations. The context window is limited to 8,191 tokens with a 4,096-token max output, small by current standards, and the training data cuts off in September 2021. GPT-4 is text-only, with no vision, audio, or document understanding, and it lacks the parallel tool-calling support found in newer OpenAI models. Within its own family, later GPT-4.1-series models measurably outperform it on quality benchmarks.
Sovereignty note. GPT-4 is created by OpenAI, a US company, and its inference is subject to US CLOUD Act exposure. It is not offered as a Sovereign, EU-resident option; data residency depends on how the endpoint is configured for a given deployment.
| Inference Provider | Sovereignty | Runs in | In / out per 1M | Status | Pin |
|---|---|---|---|---|---|
| L0 | €27.22 / 54.45 | Online |
30 use cases classified by the curator. The note says why.
Curated description highlights strength in complex professional writing — a core fit for short-form instruct tasks like email drafting.
Instruct-tuned reasoning is applicable to audit assistance tasks scoped to documents within the 8K context limit.
General reasoning strength applies to bug diagnosis on limited code snippets, constrained by the small context window.
Well-documented instruct-tuned reasoning is sufficient for standard classification tasks.
Instruct-tuned reasoning supports code explanation tasks within the 8K context limit.
Reasoning capability supports code review, but 8K context restricts review to small diffs/files rather than full repositories.
General-purpose instruct model with documented strength in complex writing tasks, though the 8K window limits long narrative arcs.
8K context window is a hard constraint for agentic coding workflows that require holding large codebases and long tool-call chains.
No browser-specific tooling documented and the small context window is a poor fit for the large DOM/state payloads typical of browser automation.
No vision capability documented — unable to process chart images.
Text-only API with no vision capability; cannot process image-based documents.
8,191-token context window is a hard limiter for document Q&A over anything beyond short documents.
No vision capability documented — text-only API per the model card.
Sourced numbers, not our own evaluations. Percentiles are against the whole Stav catalogue.
Computed from aa-intelligence-index, gpqa-diamond, aa-engineering-index, aa-coding-index, livecodebench, terminal-bench-v4, ifbench.
curl https://api.stav.ai/v1/chat/completions \
-H "Authorization: Bearer $STAV_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai/gpt-4",
"messages": [{"role": "user", "content": "Hello!"}]
}'→ X-Stav-Request-Id · X-Stav-Model · X-Stav-Provider → X-Stav-Sovereignty-Level — the rung the request was served at