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Gemini 3.8 Flash vs GPT 6 Astra

Compare Gemini 3.8 Flash from Google and GPT 6 Astra from OpenAI on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.

GoogleGemini 3.8 FlashOpenAIGPT 6 Astra
Google logo
Gemini 3.8 Flash
Google · text, image, video, audio, pdf → text

Gemini 3.8 Flash is Google's most intelligent Flash-series model, designed for long-running software engineering tasks, autonomous agents, and complex enterprise workflows, while retaining the Flash series' fast responsiveness and cost-effectiveness.

Input$0.75 /M
Output$3.75 /M
Cache read$0.075 /M
OpenAI logo
GPT 6 Astra
OpenAI · text, image → text

GPT-6 Astra is OpenAI's newest and most intelligent model, with industry-leading performance in computer operations, web browsing, software engineering, scientific research, and professional work. It excels at executing multi-step workflows across code, browsers, and various professional software. Astra can achieve better results with significantly fewer output tokens, making its estimated API cost per task lower.

Input$10 /M
Output$50 /M
Cache read$1 /M

Pricing & Specifications

Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.

Gemini 3.8 Flash
GPT 6 Astra
Input /M
$0.75
$10
Output /M
$3.75
$50
Cache read /M
$0.075
$1
Context length
1,048,576
1,050,000
Max output
65,536
128,000
Time to First Token
9.6 s
12.3 s
Throughput
44.3 tok/s
32.2 tok/s
Modalities
textimagevideoaudiopdf
textimage
Supported Parameters
thinkingtoolsfunction callingstructured outputsweblong context
toolsthinkingstructured outputs
API Formats
chat_completions · gemini_api · claude_api
chat_completions · responses
Released
September 2, 2026
September 5, 2026

Promotional prices show the discounted rate; see each model page for promotion windows.

Activity Past 30 Days

Daily traffic served through AIHubMix — how demand for each model is trending.

gemini-3.8-flashgpt-6-astra

Tokens / day

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Requests / day

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Performance Past 3 Days

Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.

gemini-3.8-flashgpt-6-astra

Throughput (tok/s)

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TTFT (s)

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Uptime (%)

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LMArena Benchmarks

LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.

WebDev Arena
gemini-3.8-flashgpt-6-astra
1520162017201820
Overall
15681796
React
15591819
HTML
16081725
Gaming
16151867
Simulations
15911846
Data analytics
15501692

Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.

Cost calculator

Estimate your monthly bill for the same workload on each model.

Gemini 3.8 Flash
$101 /mo
GPT 6 Astra
$1,350 /mo

Monthly = daily × 30. Discounted rates applied where a promotion is active.

FAQ

Which is cheaper: Gemini 3.8 Flash, GPT 6 Astra?

Gemini 3.8 Flash: $3.75/M output tokens; GPT 6 Astra: $50/M. Use the cost calculator above to estimate your own workload.

Which responds faster?

Gemini 3.8 Flash: 9.6s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.

How large is each context window?

Gemini 3.8 Flash accepts 1,048,576 and GPT 6 Astra accepts 1,050,000 input tokens. Maximum output per request is 65,536 tokens on Gemini 3.8 Flash and 128,000 tokens on GPT 6 Astra.

Which one generates tokens faster?

Gemini 3.8 Flash at 44.3 tok/s and GPT 6 Astra at 32.2 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.

What inputs and capabilities does each model support?

Gemini 3.8 Flash accepts text, image, video, audio and PDF input and supports thinking, tool calling, function calling, structured outputs, web search and long context; GPT 6 Astra accepts text and image input and supports tool calling, thinking and structured outputs.

Can I call Gemini 3.8 Flash and GPT 6 Astra with the same API key?

Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.

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