Google · Efficient
Gemini 2.5 Flash Preview (09/2025) – Thinking
Same checkpoint with thinking enabled by default for deeper reasoning and stepwise analysis on complex tasks. Routed to Gemini 2.5 Flash Thinking (stable).
- Reasoning
- Tools
- Vision
- Structured output
- PDF input
- Audio input
- Input
- Text, Images, Audio
- Output
- Text
- Reasoning effort
- low · medium · high
- Discovery tier
- Efficient
Pricing
USD per 1M tokens- Input
- $0.30
- Output
- $2.50
- Cache read
- $0.03
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 Preview (09/2025) – Thinking compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Gemini 2.5 Flash Preview (09/2025) – ThinkingGoogleThis model | Gemini 3.5 Flash ThinkingGoogleRemove | |
|---|---|---|
| Provider | ||
| Discovery tier | Efficient | Efficient |
| Added | Sep 25, 2025 | May 19, 2026 |
| Limits | ||
| Context window | 1.05M | 1.05M |
| Max output | 65.54K | 65.54K |
| Average output | — | 1.7K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.30Best | $1.50 |
| Output | $2.50Best | $9.00 |
| Cache read | $0.03Best | $0.15 |
| Cache write | — | $0.0833 |
| Performance | ||
| Throughput | — | 255.7 tok/s |
| Time to first token | — | 10.3 s |
| Request success (24h) | 99.3%Best | 89.1% |
| Benchmark indexes | ||
| Intelligence Index | 15.5 | 32.6Best |
| Coding Index | — | 70.1 |
| Math Index | 78.3 | — |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | No |
| Vision | Yes | Yes |
| Structured output | Yes | No |
| PDF input | Yes | No |
| Audio input | Yes | Yes |
| Video input | No | 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 Preview (09/2025) – Thinking
- Gemini 3.5 Flash Thinking
Intelligence Index
- Gemini 2.5 Flash Preview (09/2025) – Thinking15.5
- Gemini 3.5 Flash Thinking32.6
Gemini 2.5 Flash Preview (09/2025) – Thinking: Better than 39% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Gemini 2.5 Flash Preview (09/2025) – Thinking: —
- Gemini 3.5 Flash Thinking: 70.1
Math Index
Composite of the math evaluations
- Gemini 2.5 Flash Preview (09/2025) – Thinking: 78.3
- Gemini 3.5 Flash Thinking: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Gemini 2.5 Flash Preview (09/2025) – Thinking: —
- Gemini 3.5 Flash Thinking: 42.1%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Gemini 2.5 Flash Preview (09/2025) – Thinking: —
- Gemini 3.5 Flash Thinking: 13.5%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Gemini 2.5 Flash Preview (09/2025) – Thinking: —
- Gemini 3.5 Flash Thinking: 874 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Gemini 2.5 Flash Preview (09/2025) – Thinking: —
- Gemini 3.5 Flash Thinking: 1,202 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Gemini 2.5 Flash Preview (09/2025) – Thinking: —
- Gemini 3.5 Flash Thinking: 19.8%
AA-LCRv1.1
Reasoning across long documents
- Gemini 2.5 Flash Preview (09/2025) – Thinking: 71.0%
- Gemini 3.5 Flash Thinking: 73.3%Top
MLCR-AA
Long-context reasoning over medical records
- Gemini 2.5 Flash Preview (09/2025) – Thinking: —
- Gemini 3.5 Flash Thinking: 10.0%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Gemini 2.5 Flash Preview (09/2025) – Thinking: 13.8%
- Gemini 3.5 Flash Thinking: 42.7%Top
GPQA Diamond
Graduate-level science questions
- Gemini 2.5 Flash Preview (09/2025) – Thinking: 79.3%
- Gemini 3.5 Flash Thinking: 92.2%Top
MMLU-Pro
Multi-subject knowledge and reasoning
- Gemini 2.5 Flash Preview (09/2025) – Thinking: 84.2%
- Gemini 3.5 Flash Thinking: —
IFBench
Following precise output instructions
- Gemini 2.5 Flash Preview (09/2025) – Thinking: 52.3%
- Gemini 3.5 Flash Thinking: 76.3%Top
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Gemini 2.5 Flash Preview (09/2025) – Thinking: —
- Gemini 3.5 Flash Thinking: 6.6%
SciCode
Scientific computing in Python
- Gemini 2.5 Flash Preview (09/2025) – Thinking: —
- Gemini 3.5 Flash Thinking: 53.9%
LiveCodeBench
Recent competitive programming problems
- Gemini 2.5 Flash Preview (09/2025) – Thinking: 71.3%
- Gemini 3.5 Flash Thinking: —
Math
AIME 2025
Competition mathematics, 2025 problems
- Gemini 2.5 Flash Preview (09/2025) – Thinking: 78.3%
- Gemini 3.5 Flash Thinking: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Gemini 2.5 Flash Preview (09/2025) – Thinking: 16.7%
- Gemini 3.5 Flash Thinking: 40.9%Top
τ²-Bench Telecom
Tool use in a customer-support simulation
- Gemini 2.5 Flash Preview (09/2025) – Thinking: 45.6%
- Gemini 3.5 Flash Thinking: 95.3%Top
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Gemini 2.5 Flash Preview (09/2025) – Thinking: 71.0%
- Gemini 3.5 Flash Thinking: 73.3%Top
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-09-2025-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-09-2025-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.