GPT-OSS 20B vs GPT-4o mini
GPT-OSS 20B is an open-weight chat model you can call on this endpoint; GPT-4o mini is a closed model from OpenAI. Below: what each costs for three realistic workloads, the limits that apply, and when to choose which.
OpenAI figures are public list prices and documented limits, checked 2026-09-16 against the provider page. Inference APIs prices are read live from the price list.
- Cost: GPT-OSS 20B is cheaper in all three workloads, by 69–72%.
- Limits: OpenAI: Rate limits scale with cumulative spend through usage tiers 1–5. Here: no per-minute or per-day caps.
Side by side
| GPT-OSS 20B | GPT-4o mini | |
|---|---|---|
| Served by | Inference APIs | OpenAI |
| Model author | OpenAI | OpenAI |
| Model id | openai/gpt-oss-20b | gpt-4o-mini |
| Input price | $0.04 / 1M tokens | $0.15 / 1M tokens |
| Output price | $0.19 / 1M tokens | $0.60 / 1M tokens |
| Context window | 131K tokens | 128K tokens |
| Capabilities | Chat, Reasoning, Tool calling, JSON mode | Chat, Vision, Tool calling, JSON mode |
| Weights | Open | Closed |
| Status | Available | Available |
| Limits | No per-minute or per-day request or token caps; usage draws on a prepaid balance | Rate limits scale with cumulative spend through usage tiers 1–5. |
What three workloads cost
List prices applied to the same work. The cheaper side of each row is in bold.
| Workload | GPT-OSS 20B | GPT-4o mini | Difference |
|---|---|---|---|
| Chat assistant — 10,000 turns of 800 tokens in, 300 out | $0.89 | $3.00 | 70% |
| Long prompts or RAG — 10,000 requests of 8,000 in, 500 out | $4.15 | $15.00 | 72% |
| Generation-heavy — 10,000 requests of 500 in, 2,000 out | $4.00 | $12.75 | 69% |
GPT-OSS 20B is cheaper in all three workloads, by 69–72%. Reasoning models bill their thinking as output tokens, so real output counts run higher than the visible answer; treat the generation-heavy row as a floor for them.
When to choose which
- Cost is the deciding factor; it is cheaper in every workload above
- You want open weights: the same model can be moved to another host or self-hosted later
- You are replacing llama-3.1-8b-instant on Groq and want the small model Groq itself recommends
- Classification, extraction and short assistant replies where cost per call matters more than depth
- You want open weights, or the option to move the same model to another host
- You need to send images; GPT-OSS 20B is text-only
- You need image input
- You are already on OpenAI and want one bill and one SDK default
Price, context and speed are measurable; answer quality on your task is not something a table can settle. Both take the same request, so the honest test is to run your own prompts through each.
Switching from OpenAI
Both speak the OpenAI wire format. The edit is the base URL, the key and the model id; then re-run your own prompts, because it is a different model.
import os
from openai import OpenAI
# before: OpenAI
# client = OpenAI(base_url="https://api.openai.com/v1", api_key=os.environ["OPENAI_API_KEY"])
# MODEL = "gpt-4o-mini"
# after: Inference APIs
client = OpenAI(base_url="https://api.inferenceapis.com/v1", api_key=os.environ["INFERENCE_API_KEY"])
MODEL = "openai/gpt-oss-20b"
resp = client.chat.completions.create(model=MODEL, messages=[{"role": "user", "content": "Hello"}], max_tokens=500)More detail, including Node, LangChain and LiteLLM: switching OpenAI-compatible providers.
FAQ
Which is cheaper, GPT-OSS 20B or GPT-4o mini?
GPT-OSS 20B is cheaper in all three workloads, by 69–72%. The table above uses list prices: GPT-OSS 20B $0.04 / 1M tokens input, $0.19 / 1M tokens output; GPT-4o mini $0.15 / 1M tokens input, $0.60 / 1M tokens output.
Can I switch from GPT-4o mini to GPT-OSS 20B without rewriting code?
Yes, if you call it through an OpenAI-compatible client. Change the base URL to https://api.inferenceapis.com/v1, swap the API key, and set the model to openai/gpt-oss-20b. Because it is a different model, re-run your prompts and evaluations before moving production traffic.
What limits apply to GPT-4o mini?
Rate limits scale with cumulative spend through usage tiers 1–5. On Inference APIs there are no per-minute or per-day request or token caps; usage draws on a prepaid balance.
Why does GPT-OSS 20B use more output tokens than the visible answer?
It is a reasoning model: it thinks before it answers and the thinking is billed as output tokens. Budget for that in output-heavy workloads, and set max_tokens to a few hundred or more so the answer is not cut off.
Spotted a price or limit that has changed? Tell us and we will re-check the provider page.