OpenAI · Efficient
GPT 5 Mini
A lightweight version of GPT-5 for cost-sensitive applications. Balances advanced capabilities with efficient resource usage.
- Reasoning
- Vision
- Input
- Text, Images
- Output
- Text
- Reasoning effort
- minimal · low · medium · high
- Discovery tier
- Efficient
Pricing
USD per 1M tokens- Input
- $0.25
- Output
- $2.00
- Cache read
- $0.025
Reference prices as published by the model provider. API example
Specifications
- Context window
- 400K
- Max output
- 128K
- Average output (7 days)
- 891 tokens
- Longer than 67% of 465 models
Side by side
GPT 5 Mini compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| GPT 5 MiniOpenAIThis model | Step 3.5 Flash 2603stepfunRemove | |
|---|---|---|
| Provider | OpenAI | stepfun |
| Discovery tier | Efficient | Open weights |
| Added | Aug 7, 2025 | Apr 14, 2026 |
| Limits | ||
| Context window | 400KBest | 262.14K |
| Max output | 128KBest | 65.54K |
| Average output | 891 tokens | 3K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.25 | $0.10Best |
| Output | $2.00 | $0.30Best |
| Cache read | $0.025 | — |
| Performance | ||
| Request success (24h) | 100.0% | 100.0% |
| Benchmark indexes | ||
| Intelligence Index | 16.8 | 17.0Best |
| Coding Index | 15.6 | — |
| Math Index | 90.7 | — |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Vision | Yes | No |
| Reasoning effort | minimal, low, medium, high | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- GPT 5 Mini
- Step 3.5 Flash 2603
Intelligence Index
- GPT 5 Mini16.8
- Step 3.5 Flash 260317.0
GPT 5 Mini tested at high reasoning effort
GPT 5 Mini: Better than 45% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- GPT 5 Mini: 15.6
- Step 3.5 Flash 2603: —
Math Index
Composite of the math evaluations
- GPT 5 Mini: 90.7
- Step 3.5 Flash 2603: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- GPT 5 Mini: 6.5%
- Step 3.5 Flash 2603: —
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- GPT 5 Mini: 0.9%
- Step 3.5 Flash 2603: —
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- GPT 5 Mini: 428 Elo
- Step 3.5 Flash 2603: —
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- GPT 5 Mini: 766 Elo
- Step 3.5 Flash 2603: —
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- GPT 5 Mini: 8.4%
- Step 3.5 Flash 2603: —
AA-LCRv1.1
Reasoning across long documents
- GPT 5 Mini: 72.3%Top
- Step 3.5 Flash 2603: 63.0%
MLCR-AA
Long-context reasoning over medical records
- GPT 5 Mini: 8.9%
- Step 3.5 Flash 2603: —
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- GPT 5 Mini: 21.5%
- Step 3.5 Flash 2603: 24.5%Top
GPQA Diamond
Graduate-level science questions
- GPT 5 Mini: 82.8%Top
- Step 3.5 Flash 2603: 82.6%
MMLU-Pro
Multi-subject knowledge and reasoning
- GPT 5 Mini: 83.7%
- Step 3.5 Flash 2603: —
IFBench
Following precise output instructions
- GPT 5 Mini: 75.4%Top
- Step 3.5 Flash 2603: 66.5%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- GPT 5 Mini: 0.0%
- Step 3.5 Flash 2603: —
SciCode
Scientific computing in Python
- GPT 5 Mini: 39.0%
- Step 3.5 Flash 2603: —
LiveCodeBench
Recent competitive programming problems
- GPT 5 Mini: 83.8%
- Step 3.5 Flash 2603: —
Math
AIME 2025
Competition mathematics, 2025 problems
- GPT 5 Mini: 90.7%
- Step 3.5 Flash 2603: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- GPT 5 Mini: 33.3%Top
- Step 3.5 Flash 2603: 32.6%
τ²-Bench Telecom
Tool use in a customer-support simulation
- GPT 5 Mini: 68.4%
- Step 3.5 Flash 2603: 87.4%Top
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- GPT 5 Mini: 72.3%Top
- Step 3.5 Flash 2603: 63.0%
Scores from Artificial Analysis, updated Oct 26, 2026. GPT 5 Mini was tested at high reasoning effort; compare scores measured at the same effort.Artificial Analysis
Live routing data
Performance and reliability
Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.
- Prompt cache hits
- 22.1%
- About $0.20 per 1M input tokens with caching
- Request success (24h)
- 100.0%
- Reliable
Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.
- Healthy (98% or more)
- Degraded (90–98%)
- Down (under 90%)
- No requests
Developers
Use it through the API
Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "openai/gpt-5-mini",
"reasoning_effort": "medium",
"messages": [{ "role": "user", "content": "Explain this stack trace." }]
}'import os
from openai import OpenAI
client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
model="openai/gpt-5-mini",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)OpenAI
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