Google · Efficient
Gemini 2.5 Flash Lite Preview (09/2025)
Deprecated compatibility alias. Requests route to the stable Gemini 2.5 Flash Lite model.
- 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
- $0.10
- Output
- $0.40
- Cache read
- $0.01
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 Lite Preview (09/2025) compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Gemini 2.5 Flash Lite Preview (09/2025)GoogleThis model | Qwen3 Coder NextQwenRemove | |
|---|---|---|
| Provider | Qwen | |
| Discovery tier | Efficient | Open weights |
| Added | Sep 25, 2025 | Dec 8, 2025 |
| Limits | ||
| Context window | 1.05MBest | 262.14K |
| Max output | 65.54K | 65.54K |
| Average output | — | 182 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.10Best | $0.25 |
| Output | $0.40Best | $0.80 |
| Cache read | $0.01Best | $0.0798 |
| Performance | ||
| Throughput | — | 123.1 tok/s |
| Time to first token | — | 1.7 s |
| Request success (24h) | 99.5%Best | 92.3% |
| Benchmark indexes | ||
| Intelligence Index | 9.3Best | 9.2 |
| Coding Index | — | 36.2 |
| Math Index | 46.7 | — |
| Capabilities | ||
| Reasoning | Yes | No |
| Tools | Yes | Yes |
| Vision | Yes | No |
| Structured output | Yes | Yes |
| PDF input | Yes | No |
| Audio input | Yes | No |
| Reasoning effort | 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 Lite Preview (09/2025)
- Qwen3 Coder Next
Intelligence Index
- Gemini 2.5 Flash Lite Preview (09/2025)9.3
- Qwen3 Coder Next9.2
Gemini 2.5 Flash Lite Preview (09/2025): Better than 18% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Gemini 2.5 Flash Lite Preview (09/2025): —
- Qwen3 Coder Next: 36.2
Math Index
Composite of the math evaluations
- Gemini 2.5 Flash Lite Preview (09/2025): 46.7
- Qwen3 Coder Next: —
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Gemini 2.5 Flash Lite Preview (09/2025): —
- Qwen3 Coder Next: 1.1%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Gemini 2.5 Flash Lite Preview (09/2025): —
- Qwen3 Coder Next: 0.0%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Gemini 2.5 Flash Lite Preview (09/2025): —
- Qwen3 Coder Next: 404 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Gemini 2.5 Flash Lite Preview (09/2025): —
- Qwen3 Coder Next: 513 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Gemini 2.5 Flash Lite Preview (09/2025): —
- Qwen3 Coder Next: 2.6%
AA-LCRv1.1
Reasoning across long documents
- Gemini 2.5 Flash Lite Preview (09/2025): 49.7%Top
- Qwen3 Coder Next: 47.0%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Gemini 2.5 Flash Lite Preview (09/2025): 5.1%
- Qwen3 Coder Next: 10.1%Top
GPQA Diamond
Graduate-level science questions
- Gemini 2.5 Flash Lite Preview (09/2025): 65.1%
- Qwen3 Coder Next: 73.7%Top
MMLU-Pro
Multi-subject knowledge and reasoning
- Gemini 2.5 Flash Lite Preview (09/2025): 79.6%
- Qwen3 Coder Next: —
IFBench
Following precise output instructions
- Gemini 2.5 Flash Lite Preview (09/2025): 41.8%Top
- Qwen3 Coder Next: 35.2%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Gemini 2.5 Flash Lite Preview (09/2025): —
- Qwen3 Coder Next: 0.0%
SciCode
Scientific computing in Python
- Gemini 2.5 Flash Lite Preview (09/2025): —
- Qwen3 Coder Next: 36.2%
LiveCodeBench
Recent competitive programming problems
- Gemini 2.5 Flash Lite Preview (09/2025): 64.1%
- Qwen3 Coder Next: —
Math
AIME 2025
Competition mathematics, 2025 problems
- Gemini 2.5 Flash Lite Preview (09/2025): 46.7%
- Qwen3 Coder Next: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Gemini 2.5 Flash Lite Preview (09/2025): 7.6%
- Qwen3 Coder Next: 18.2%Top
τ²-Bench Telecom
Tool use in a customer-support simulation
- Gemini 2.5 Flash Lite Preview (09/2025): 30.4%
- Qwen3 Coder Next: 79.5%Top
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Gemini 2.5 Flash Lite Preview (09/2025): 49.7%Top
- Qwen3 Coder Next: 47.0%
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.
- Prompt cache hits
- 0.0%
- About $0.10 per 1M input tokens with caching
- Request success (24h)
- 99.5%
- 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": "gemini-2.5-flash-lite-preview-09-2025",
"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-lite-preview-09-2025",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Related models
Other Google models, starting with the same family.