ModelRefs / GPT-4.1 Mini by OpenAI — Benchmarks, Pricing & Review (2026)

GPT-4.1 Mini by OpenAI — Benchmarks, Pricing & Review (2026)

GPT-4.1 Mini (OpenAI): GPT-4.1 Mini by OpenAI.. 1M context. Pricing: from $0.00040/1K in. Specs, benchmarks and code examples.

What this reference supports

GPT-4.1 Mini is the smaller hosted member of OpenAI's GPT-4.1 API family. It is relevant when teams need the family's instruction-following, coding, tool, and long-input surface while evaluating a different cost, latency, and quality trade-off from GPT-4.1.

GPT-4.1 Mini is attributed to OpenAI in ModelRefs' canonical registry. Tracked modalities: Text input and output, Image input. Primary use cases considered on ModelRefs: High-volume structured language processing; Coding assistance and tool-driven workflows with measured quality targets.

This ModelRefs profile is Provisional and pending review — decision-support material, not a final or universal ranking. Confirm current behavior, access, pricing, limits, licensing, and lifecycle in OpenAI's own documentation, and evaluate GPT-4.1 Mini on representative workloads before implementation.

Benchmark & Evaluation

ModelRefs currently has partial, narrow benchmark coverage for GPT-4.1 Mini. Treat the available benchmark evidence as one input to the decision, not a guarantee that GPT-4.1 Mini is the strongest option for your workload, and evaluate it on representative workloads before selecting it.

  • Provider-reported benchmark results should be interpreted with methodology, dataset, prompting, tool, sampling, and recency limitations in mind.
  • G.18 registers OpenAI's source-scoped simple-evals GPQA result for gpt-4.1-mini-2025-04-14. It supports Partial eligibility only and is not transferred to other GPT-4.1 variants.

Implementation considerations

  • Benchmark the mini variant directly; family-level claims do not establish parity with GPT-4.1.
  • Pin model snapshots and test structured-output, tool, and long-input failure modes.
  • Hosted through eligible OpenAI API endpoints.
  • Verify current model status, endpoint support, quotas, and rates before rollout.

Risks and limitations

  • Outputs can be incorrect or unsuitable for the intended task; use task-specific evaluation, grounding, and human review where consequences are material.
  • API availability, model aliases, rate limits, data controls, regions, and prices are mutable and differ by product channel.

Source coverage

This reference is Provisional. Model behavior, access, pricing, limits, and lifecycle can change; verify the linked provider documentation and run task-specific evaluations before implementation.

Known coverage gaps:

  • Independent reproduction and canonical run metadata for variant-specific evaluations are incomplete.
  • Current data-control and rate-limit coverage is not attached.

Sources

Continue your research

Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to GPT-4.1 Mini by OpenAI — Benchmarks, Pricing & Review (2026).