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OpenAI's compact GPT-5 variant with tunable reasoning effort, a 400K-token context window, and multimodal input for interactive document and image tasks.
Overview. GPT-5 mini is OpenAI's compact variant in the GPT-5 family, released 2025-08-07. It's a closed-weight, proprietary model accessed through OpenAI's API, offering a 400,000-token context window with up to 128,000 tokens of output. Developers reach for it when they need multimodal input handling — text, images, and documents — without the footprint of the full GPT-5 model.
Key strengths. GPT-5 mini supports mandatory, tunable reasoning-effort levels, giving it more multi-step capacity than a plain instruction-following model even though it sits in the family's 'instruct' tier rather than the dedicated reasoning tier. Its 400,000-token context window and native document understanding (via file input) make it well suited to long-document and multimodal workflows. Artificial Analysis places its intelligence index at 25.8, positioning it below the larger GPT-5 siblings but ahead of the smallest nano variant — consistent with a mid-to-low complexity workload profile rather than frontier reasoning tasks.
When to use it. Use GPT-5 mini for interactive, multimodal tasks — document analysis, image-plus-text queries, and general writing or communication workloads — where medium task complexity and low latency matter more than maximum reasoning depth. It's a good fit when you need a large context window and structured tool-calling on a compact model rather than the flagship GPT-5.
Limitations. Training data is capped at May 2024, so it won't have knowledge of more recent events. Its aggregate intelligence index trails the larger GPT-5 family members, so it isn't the right choice for complex multi-step reasoning or top-tier coding tasks. OpenAI has also scheduled this specific model snapshot for API shutdown on 2026-12-11, so long-lived integrations should plan for migration ahead of that date.
Sovereignty note. GPT-5 mini is built by OpenAI, a US-based creator, and is exposed to CLOUD Act jurisdiction — it is not a Sovereign offering under Stav's EU-residency definition.
| Inference Provider | Sovereignty | Runs in | In / out per 1M | Status | Pin |
|---|---|---|---|---|---|
| L0 | €0.23 / 1.81+3 rates | Online |
15 use cases classified by the curator. The note says why.
Low-latency inference and tunable reasoning effort make this variant well suited for high-throughput classification tasks.
Low-latency, tunable-reasoning design is purpose-built for interactive chat workloads at scale, with 400K context for long conversation history.
Compact, low-latency variant with 400K context is a strong cost/performance fit for high-volume entity extraction pipelines.
Native tool-calling and prompt-caching make this a cost-efficient choice for high-volume function-calling applications where the flagship's latency/cost would be excessive.
Vision capability combined with low-latency design fits interactive image Q&A workloads well.
Vision plus tool-calling support directly targets screenshot-driven agentic workflows like browser/UI automation.
Tool-calling plus vision supports screenshot-driven browser automation loops; compact size favors latency over deep multi-page reasoning.
Tool-calling and extended-thinking support code tasks; compact tier is cost-efficient for high-frequency completion requests versus flagship reasoning models.
Vision capability supports OCR-style document understanding, though not a specialized OCR model.
400K context window supports long-document Q&A, though the compact tier trades some reasoning depth versus the flagship variant.
Extended-thinking mode enables step-by-step planning, but as the compact variant it trades reasoning depth for speed versus the flagship gpt-5.6-sol tier.
400K context handles long-document summarisation; compact design prioritizes speed/cost over the flagship's deeper synthesis capability.
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, aa-multilingual-index, aa-lcr.
curl https://api.stav.ai/v1/chat/completions \
-H "Authorization: Bearer $STAV_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai/gpt-5-mini",
"reasoning_effort": "high",
"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