Compare GPT 4.1 (free) from OpenAI and GPT 5.6 Luna from OpenAI on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.
GPT 4.1 (free)GPT 5.6 LunaThe latest flagship multimodal model supports million-token context, with encoding capability (SWE-bench 54.6%) and instruction-following (Scale AI 38.3%) performance significantly surpassing GPT-4o, while reducing costs by 26%, making it suitable for complex tasks. Its automatic caching mechanism offers a 75% cost reduction on cache hits.
GPT-5.6 Luna is designed for cost-sensitive, high-volume workloads. It roughly corresponds to the nano model tier used in earlier GPT-5 families.
Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.
Promotional prices show the discounted rate; see each model page for promotion windows.
Daily traffic served through AIHubMix — how demand for each model is trending.
Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.
Estimate your monthly bill for the same workload on each model.
Monthly = daily × 30. Discounted rates applied where a promotion is active.
GPT 4.1 (free): 1.1s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.
GPT 4.1 (free) accepts 1,047,576 and GPT 5.6 Luna accepts 1,050,000 input tokens. Maximum output per request is 32,768 tokens on GPT 4.1 (free) and 128,000 tokens on GPT 5.6 Luna.
GPT 5.6 Luna at 88.4 tok/s and GPT 4.1 (free) at 43.3 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.
GPT 4.1 (free) accepts text, image and PDF input and supports tool calling, function calling, structured outputs and long context; GPT 5.6 Luna accepts text and image input and supports tool calling, thinking and structured outputs.
Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.
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