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Gemini 3.8 Flash (Low Reasoning)
Low reasoning effort variant of Gemini 3.8 Flash optimized for sub-150ms TTFT and maximum throughput.
Intelligence
62.0 #318
Top 41% tier
Output Speed
340 t/s
TTFT 140 ms · ITL 2.9 ms/tok
Blended price (3:1)
$1.5 /1M
In $0.75/M · Out $3.75/M
Context
1M
≈ 2,500 A4 pages · max out 32,768
Quality Domain Radar
6-Axis Frontier Evaluation vs Category Average & Flagship
Gemini 3.8 Flash (Low Reasoning)
Claude Mythos Preview (#1)
Average (68)
Radar axes are approximated from category scores where direct benchmark measurements are missing — see Methodology.
Strengths & Trade-offs
Where it wins
- 1M context — swallows whole repos, codebases or corpora in one pass
- Up to 65,536 output tokens per response
- 302 tok/s output — fast enough for real-time agents
- Sub-200ms time-to-first-token
Trade-offs to watch
- Architecture and weights undisclosed — API access only
Killer Use Cases
SWE-bench agents
Issue-to-PR resolution across multi-file repos — refactor, test and verify autonomously.
Math & proof work
Step-verified reasoning for olympiad math, theorem proving and formal verification.
Real-time agents
Low-latency loops for voice, gaming and interactive copilots.
Developer Quickstart & API
Set
GEMINI_API_KEY first — get an API keycurl "https://generativelanguage.googleapis.com/v1beta/models/gemini-3-8-flash-low:generateContent" \
-H "x-goog-api-key: $GEMINI_API_KEY" \
-H "content-type: application/json" \
-d '{
"contents": [{"parts": [{"text": "Refactor this function for O(n) time and explain the change."}]}]
}'from google import genai
client = genai.Client() # reads GEMINI_API_KEY
resp = client.models.generate_content(
model="gemini-3-8-flash-low",
contents="Refactor this function for O(n) time and explain the change.",
)
print(resp.text)const res = await fetch(
`https://generativelanguage.googleapis.com/v1beta/models/gemini-3-8-flash-low:generateContent`,
{
method: "POST",
headers: {
"x-goog-api-key": process.env.GEMINI_API_KEY,
"content-type": "application/json",
},
body: JSON.stringify({ contents: [{ parts: [{ text: "Refactor this function for O(n) time and explain the change." }] }] }),
}
);
console.log((await res.json()).candidates[0].content.parts[0].text);Official Resources & Links
API deployment
Compare hosts & latency
Throughput, TTFT and cache pricing across Groq, Cerebras, Together, DeepInfra, Fireworks, Bedrock and Azure.
GroqCerebrasTogether AIDeepInfraFireworks AIAWS BedrockAzure AI
Scores by Source
Category Scores
Benchmark Results
Live Specs & Architecture
Under the hood
- Switchable reasoning effort — trading latency and tokens for accuracy on hard problems.
- Prompt caching supported — cached input reads at $0.075/1M tokens.
- Native multimodality: text, image, audio, video in a single model.
Release date
Sep 1, 2026
Parameters
Not disclosed
License
Proprietary
Context Window
1,000,000 tokens
Max Output
32,768 tokens
Modalities
text + image + audio + video
Cache Pricing
read $0.075 · write $0.9375 /1M
Reasoning
Effort levels
Input Price
$0.75/M
Output Price
$3.75/M
Output Speed
340 t/s
Time to First Token
140 ms
Data Updated
Sep 2, 2026
Estimated monthly bill
Estimated monthly spend
$0.00
Calculating savings vs GPT-4o...
Cite & embed
GitHub Markdown badge
Loading badge markdown...BibTeX
@misc{llmpodium2026gemini38flashlow,
title = {Benchmark Analysis and Intelligence Evaluation of Gemini 3.8 Flash (Low Reasoning)},
author = {LLMPodium Research},
year = {2026},
url = {https://llmpodium.com/models/gemini-3-8-flash-low}
}Embed Score Badge
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