Google · Efficient
Gemini 3.8 Flash
Google's fast multimodal model for agentic workloads, including coding, tool use, image understanding, PDF and document extraction, audio, and video. Its capabilities, limits, reasoning behavior, and pricing currently mirror Gemini 3.7 Flash.
- Reasoning
- Tools
- Vision
- Structured output
- PDF input
- Audio input
- Video input
- Input
- Text, Images, Video, Audio
- Output
- Text
- Reasoning effort
- minimal · low · medium · high
- Discovery tier
- Efficient
Pricing
USD per 1M tokens- Input
- $0.75
- Output
- $3.75
- Cache read
- $0.075
- Cache write
- $0.0417
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- 65.5K
- Average output (7 days)
- 1.2K tokens
- Longer than 79% of 465 models
Side by side
Gemini 3.8 Flash compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Gemini 3.8 FlashGoogleThis model | Gemini 3 Flash (Preview)GoogleRemove | |
|---|---|---|
| Provider | ||
| Discovery tier | Efficient | Efficient |
| Added | Sep 2, 2026 | Dec 17, 2025 |
| Limits | ||
| Context window | 1.05M | 1.05M |
| Max output | 65.54K | 65.54K |
| Average output | 1.2K tokens | 592 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.75 | $0.50Best |
| Output | $3.75 | $3.00Best |
| Cache read | $0.075 | $0.05Best |
| Cache write | $0.0417 | — |
| Performance | ||
| Throughput | 164.7 tok/s | 211.2 tok/sBest |
| Time to first token | 5.9 s | 1.3 sBest |
| Request success (24h) | 99.8% | 99.8% |
| Benchmark indexes | ||
| Intelligence Index | 39.8Best | 17.9 |
| Coding Index | 74.1 | — |
| Math Index | — | 55.7 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | Yes |
| Structured output | Yes | Yes |
| PDF input | Yes | No |
| Audio input | Yes | Yes |
| Video input | Yes | Yes |
| Reasoning effort | minimal, 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 3.8 Flash
- Gemini 3 Flash (Preview)
Intelligence Index
- Gemini 3.8 Flash39.8
- Gemini 3 Flash (Preview)17.9
Gemini 3.8 Flash tested at medium reasoning effort
Gemini 3.8 Flash: Better than 84% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- Gemini 3.8 Flash: 74.1
- Gemini 3 Flash (Preview): —
Math Index
Composite of the math evaluations
- Gemini 3.8 Flash: —
- Gemini 3 Flash (Preview): 55.7
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Gemini 3.8 Flash: 60.9%
- Gemini 3 Flash (Preview): —
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Gemini 3.8 Flash: 31.1%
- Gemini 3 Flash (Preview): —
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Gemini 3.8 Flash: 1,181 Elo
- Gemini 3 Flash (Preview): —
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Gemini 3.8 Flash: 1,423 Elo
- Gemini 3 Flash (Preview): —
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Gemini 3.8 Flash: 22.8%
- Gemini 3 Flash (Preview): —
AA-LCRv1.1
Reasoning across long documents
- Gemini 3.8 Flash: 84.0%Top
- Gemini 3 Flash (Preview): 55.3%
MLCR-AA
Long-context reasoning over medical records
- Gemini 3.8 Flash: 12.8%
- Gemini 3 Flash (Preview): —
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Gemini 3.8 Flash: 42.1%Top
- Gemini 3 Flash (Preview): 15.0%
GPQA Diamond
Graduate-level science questions
- Gemini 3.8 Flash: 93.5%Top
- Gemini 3 Flash (Preview): 81.2%
MMLU-Pro
Multi-subject knowledge and reasoning
- Gemini 3.8 Flash: —
- Gemini 3 Flash (Preview): 88.2%
IFBench
Following precise output instructions
- Gemini 3.8 Flash: —
- Gemini 3 Flash (Preview): 55.1%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Gemini 3.8 Flash: 19.7%
- Gemini 3 Flash (Preview): —
SciCode
Scientific computing in Python
- Gemini 3.8 Flash: 55.1%
- Gemini 3 Flash (Preview): —
LiveCodeBench
Recent competitive programming problems
- Gemini 3.8 Flash: —
- Gemini 3 Flash (Preview): 79.7%
Math
AIME 2025
Competition mathematics, 2025 problems
- Gemini 3.8 Flash: —
- Gemini 3 Flash (Preview): 55.7%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Gemini 3.8 Flash: —
- Gemini 3 Flash (Preview): 31.8%
τ²-Bench Telecom
Tool use in a customer-support simulation
- Gemini 3.8 Flash: —
- Gemini 3 Flash (Preview): 43.3%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Gemini 3.8 Flash: 84.0%Top
- Gemini 3 Flash (Preview): 55.3%
Scores from Artificial Analysis, updated Oct 26, 2026. Gemini 3.8 Flash was tested at medium reasoning effort; compare scores measured at the same effort.Artificial Analysis
- Gemini 3.8 Flash
- Gemini 3 Flash (Preview)
| Leaderboard | Gemini 3.8 Flash | Gemini 3 Flash (Preview) |
|---|---|---|
| Combined | #16 · 9.3% | Not in top 20 |
Ranks among Noumen catalog models on Combined leaderboards. Only top-20 placements are listed.
- Gemini 3.8 Flash
- Gemini 3 Flash (Preview)
| Leaderboard | Gemini 3.8 Flash | Gemini 3 Flash (Preview) |
|---|---|---|
| Creative writing | #19 · 15.2% | Not in top 20 |
| Math | #3 · 41.9% | Not in top 20 |
Ranks among Noumen catalog models on Use cases leaderboards. Only top-20 placements are listed.
- Gemini 3.8 Flash
- Gemini 3 Flash (Preview)
| Leaderboard | Gemini 3.8 Flash | Gemini 3 Flash (Preview) |
|---|---|---|
| Overall | #8 · 1495.7 | Not in top 20 |
| Math | #3 · 1525.9 | Not in top 20 |
| Longer Query | #7 · 1509.9 | Not in top 20 |
| Creative Writing | #9 · 1485.1 | Not in top 20 |
| Instruction Following | #11 · 1490.2 | Not in top 20 |
| Hard Prompts | #8 · 1517.3 | Not in top 20 |
| Chinese | #12 · 1538.3 | Not in top 20 |
| English | #9 · 1498.0 | Not in top 20 |
| Exclude Ties | #9 · 1513.6 | Not in top 20 |
| Expert | #12 · 1527.5 | Not in top 20 |
| German | #8 · 1501.8 | #10 · 1499.1 |
| Hard Prompts English | #11 · 1514.0 | Not in top 20 |
| Industry Entertainment And Sports And Media | #9 · 1477.4 | Not in top 20 |
| Industry Life And Physical And Social Science | #9 · 1519.3 | Not in top 20 |
| Industry Mathematical | #10 · 1513.9 | Not in top 20 |
| Industry Medicine And Healthcare | #10 · 1507.7 | Not in top 20 |
| Industry Software And It Services | #18 · 1517.5 | Not in top 20 |
| Industry Writing And Literature And Language | #9 · 1490.5 | Not in top 20 |
| Japanese | #7 · 1508.3 | #13 · 1488.7 |
| Korean | #13 · 1459.7 | Not in top 20 |
| Multi Turn | #7 · 1504.4 | Not in top 20 |
| Non English | #8 · 1486.3 | Not in top 20 |
| Polish | #13 · 1492.9 | #10 · 1496.6 |
| Russian | #5 · 1515.1 | Not in top 20 |
| Spanish | #18 · 1478.0 | #17 · 1478.0 |
| Vision Style Control Overall | #8 · 1291.0 | Not in top 20 |
| Vision Style Control · Chinese | #1 · 1383.7 | Not in top 20 |
| Vision Style Control · Creative Writing Vision | #16 · 1275.7 | #6 · 1296.1 |
| Vision Style Control · Diagram | #2 · 1333.3 | Not in top 20 |
| Vision Style Control · English | #4 · 1291.5 | Not in top 20 |
| Vision Style Control · Homework | #5 · 1338.4 | Not in top 20 |
| Vision Style Control · Humor | #3 · 1297.9 | #14 · 1268.8 |
| Vision Style Control · Ocr | #2 · 1316.0 | Not in top 20 |
| WebDev · Image To Webdev | #15 · 1592.7 | Not in top 20 |
| Vision Style Control · Creative Writing | Not in top 20 | #2 · 1289.1 |
| Vision Style Control · Captioning | Not in top 20 | #6 · 1233.8 |
| Vision Style Control · Entity Recognition | Not in top 20 | #1 · 1290.0 |
Ranks among Noumen catalog models on LMArena leaderboards. Only top-20 placements are listed.LMArena
- Gemini 3.8 Flash
- Gemini 3 Flash (Preview)
| Leaderboard | Gemini 3.8 Flash | Gemini 3 Flash (Preview) |
|---|---|---|
| Epoch Capabilities Index | #19 · 157.4 | Not in top 20 |
| FrontierMath v2 (Tiers 1–3) | Not in top 20 | #11 · 51.2% |
| SWE-bench Verified | Not in top 20 | #7 · 75.4% |
Ranks among Noumen catalog models on Epoch AI leaderboards. Only top-20 placements are listed.Epoch AI
- Gemini 3.8 Flash
- Gemini 3 Flash (Preview)
| Leaderboard | Gemini 3.8 Flash | Gemini 3 Flash (Preview) |
|---|---|---|
| ARC-AGI-1 | #3 · 98.5% | Not in top 20 |
| ARC-AGI-2 | #10 · 89.2% | Not in top 20 |
| ARC-AGI-3 (Default harness) | #6 · 10.4% | Not in top 20 |
Ranks among Noumen catalog models on ARC Prize leaderboards. Only top-20 placements are listed.ARC Prize
- Gemini 3.8 Flash
- Gemini 3 Flash (Preview)
| Leaderboard | Gemini 3.8 Flash | Gemini 3 Flash (Preview) |
|---|---|---|
| Game Development | #19 · 1305 | Not in top 20 |
| Website | #19 · 1300 | Not in top 20 |
| UI Component | #14 · 1313 | Not in top 20 |
| SVG | #11 · 1292 | Not in top 20 |
| 3D | #20 · 1292 | Not in top 20 |
| ASCII Art | #12 · 1266 | Not in top 20 |
| Web Apps | #12 · 1239 | Not in top 20 |
| Full Stack | #10 · 1244 | Not in top 20 |
| Mobile Apps | #9 · 1235 | Not in top 20 |
Ranks among Noumen catalog models on Design Arena leaderboards. Only top-20 placements are listed.Design Arena
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.
- Throughput
- 164.7 tok/s
- Faster than 80% of 250 models
- Time to first token
- 5.9 s
- Quicker than 27% of 250 models
- Prompt cache hits
- 9.6%
- About $0.69 per 1M input tokens with caching
- Request success (24h)
- 99.8%
- 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": "google/gemini-3.8-flash",
"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="google/gemini-3.8-flash",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)Related models
Other Google models, starting with the same family.