Google · Efficient
Gemini 2.5 Flash Lite Preview
Ultra-lightweight and fast variant of Gemini 2.5 Flash. Preview release optimized for speed and efficiency.
- Reasoning
- Vision
- Audio input
- Input
- Text, Images, Audio
- Output
- Text
- Reasoning effort
- low · medium · high
- Discovery tier
- Efficient
Pricing
USD per 1M tokens- Input
- $0.15
- Output
- $0.60
- 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 Lite Preview compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Gemini 2.5 Flash Lite PreviewGoogleThis model | Mistral Small 3 24B (2501)MistralRemove | |
|---|---|---|
| Provider | Mistral | |
| Discovery tier | Efficient | Open weights |
| Added | Jun 17, 2025 | Sep 10, 2026 |
| Limits | ||
| Context window | 1.05MBest | 32.77K |
| Max output | 65.54KBest | 8.19K |
| Average output | — | 403 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.15 | $0.12Best |
| Output | $0.60 | $0.35Best |
| Cache read | $0.015 | — |
| Performance | ||
| Request success (24h) | 99.5% | — |
| Benchmark indexes | ||
| Intelligence Index | 6.7 | 6.7 |
| Math Index | 35.3Best | 4.3 |
| Capabilities | ||
| Reasoning | Yes | No |
| Tools | No | Yes |
| Vision | 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
- Mistral Small 3 24B (2501)
Intelligence Index
- Gemini 2.5 Flash Lite Preview6.7
- Mistral Small 3 24B (2501)6.7
Gemini 2.5 Flash Lite Preview: Better than 6% of 326 scored models
Indexes
Math Index
Composite of the math evaluations
- Gemini 2.5 Flash Lite Preview: 35.3Top
- Mistral Small 3 24B (2501): 4.3
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- Gemini 2.5 Flash Lite Preview: 32.0%Top
- Mistral Small 3 24B (2501): 0.0%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Gemini 2.5 Flash Lite Preview: 3.7%
- Mistral Small 3 24B (2501): 3.8%Top
GPQA Diamond
Graduate-level science questions
- Gemini 2.5 Flash Lite Preview: 47.4%Top
- Mistral Small 3 24B (2501): 46.2%
MMLU-Pro
Multi-subject knowledge and reasoning
- Gemini 2.5 Flash Lite Preview: 72.4%Top
- Mistral Small 3 24B (2501): 65.2%
IFBench
Following precise output instructions
- Gemini 2.5 Flash Lite Preview: 31.5%Top
- Mistral Small 3 24B (2501): 26.4%
Coding
LiveCodeBench
Recent competitive programming problems
- Gemini 2.5 Flash Lite Preview: 40.0%Top
- Mistral Small 3 24B (2501): 25.2%
Math
AIME 2025
Competition mathematics, 2025 problems
- Gemini 2.5 Flash Lite Preview: 35.3%Top
- Mistral Small 3 24B (2501): 4.3%
AIME
Competition mathematics
- Gemini 2.5 Flash Lite Preview: 50.0%Top
- Mistral Small 3 24B (2501): 8.0%
MATH-500
Competition math problems
- Gemini 2.5 Flash Lite Preview: 92.6%Top
- Mistral Small 3 24B (2501): 71.5%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Gemini 2.5 Flash Lite Preview: 2.3%
- Mistral Small 3 24B (2501): —
τ²-Bench Telecom
Tool use in a customer-support simulation
- Gemini 2.5 Flash Lite Preview: 19.0%
- Mistral Small 3 24B (2501): 19.6%Top
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Gemini 2.5 Flash Lite Preview: 32.0%Top
- Mistral Small 3 24B (2501): 0.0%
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 $0.15 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-06-17",
"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-06-17",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Related models
Other Google models, starting with the same family.