Google · Efficient
Gemini 2.5 Flash 0520 Thinking
Deprecated. Mapped to Gemini 2.5 Flash because this model is deprecated
- Reasoning
- Vision
- Input
- Text, Images
- Output
- Text
- Reasoning effort
- low · medium · high
- Discovery tier
- Efficient
Pricing
USD per 1M tokens- Input
- $0.15
- Output
- $3.50
- Cache read
- $0.015
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- 65.5K
Side by side
Gemini 2.5 Flash 0520 Thinking compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Gemini 2.5 Flash 0520 ThinkingGoogleThis model | GPT 5 NanoOpenAIRemove | |
|---|---|---|
| Provider | OpenAI | |
| Discovery tier | Efficient | Efficient |
| Added | May 20, 2025 | Aug 7, 2025 |
| Limits | ||
| Context window | 1.05MBest | 400K |
| Max output | 65.54K | 128KBest |
| Average output | — | 322 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.15 | $0.05Best |
| Output | $3.50 | $0.40Best |
| Cache read | $0.015 | $0.005Best |
| Performance | ||
| Throughput | — | 96.6 tok/s |
| Time to first token | — | 1.8 s |
| Request success (24h) | 99.3% | 99.9%Best |
| Benchmark indexes | ||
| Intelligence Index | 13.1Best | 13.0 |
| Math Index | 73.3 | 83.7Best |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Vision | Yes | Yes |
| Reasoning effort | low, medium, high | minimal, low, medium, high |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Gemini 2.5 Flash 0520 Thinking
- GPT 5 Nano
Intelligence Index
- Gemini 2.5 Flash 0520 Thinking13.1
- GPT 5 Nano13.0
Gemini 2.5 Flash 0520 Thinking: Better than 32% of 326 scored models
Indexes
Math Index
Composite of the math evaluations
- Gemini 2.5 Flash 0520 Thinking: 73.3
- GPT 5 Nano: 83.7Top
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- Gemini 2.5 Flash 0520 Thinking: 65.3%Top
- GPT 5 Nano: 45.0%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Gemini 2.5 Flash 0520 Thinking: 12.1%Top
- GPT 5 Nano: 9.5%
GPQA Diamond
Graduate-level science questions
- Gemini 2.5 Flash 0520 Thinking: 79.0%Top
- GPT 5 Nano: 67.6%
MMLU-Pro
Multi-subject knowledge and reasoning
- Gemini 2.5 Flash 0520 Thinking: 83.2%Top
- GPT 5 Nano: 78.0%
IFBench
Following precise output instructions
- Gemini 2.5 Flash 0520 Thinking: 50.3%
- GPT 5 Nano: 67.6%Top
Coding
LiveCodeBench
Recent competitive programming problems
- Gemini 2.5 Flash 0520 Thinking: 69.5%
- GPT 5 Nano: 78.9%Top
Math
AIME 2025
Competition mathematics, 2025 problems
- Gemini 2.5 Flash 0520 Thinking: 73.3%
- GPT 5 Nano: 83.7%Top
AIME
Competition mathematics
- Gemini 2.5 Flash 0520 Thinking: 82.3%
- GPT 5 Nano: —
MATH-500
Competition math problems
- Gemini 2.5 Flash 0520 Thinking: 98.1%
- GPT 5 Nano: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Gemini 2.5 Flash 0520 Thinking: 13.6%Top
- GPT 5 Nano: 12.1%
τ²-Bench Telecom
Tool use in a customer-support simulation
- Gemini 2.5 Flash 0520 Thinking: 31.6%
- GPT 5 Nano: 36.5%Top
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Gemini 2.5 Flash 0520 Thinking: 65.3%Top
- GPT 5 Nano: 45.0%
Scores from Artificial Analysis, updated Oct 26, 2026. 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.
- Request success (24h)
- 99.3%
- Reliable
- 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": "gemini-2.5-flash-preview-05-20:thinking",
"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="gemini-2.5-flash-preview-05-20:thinking",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Related models
Other Google models, starting with the same family.