AI Models · Paid vs Paid

GPT Audio Paid vs Gemini 3.8 Flash Paid

GPT Audio vs Gemini 3.8 Flash compared — price per token, context window, multimodality, openness and which to choose. Full 2026 breakdown.

Prices & specs refreshed from live data · olud.ai

Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.

GPT AudioPaidOpenAI
$2.5 /M input
$10 /M outputManaged API (no infra to run)
TypeProprietary
Context window128K tokens
MultimodalNo
Self-hostNo
Gemini 3.8 FlashPaidGoogle
$0.75 /M input
$3.75 /M outputManaged API (no infra to run)
TypeProprietary
Context window1M tokens
MultimodalYes
Self-hostNo
Choose Gemini 3.8 Flash for the lower output price ($3.75/M vs $10/M). It also gives you the larger 1M context window.

GPT Audio vs Gemini 3.8 Flash specs

SpecGPT AudioGemini 3.8 FlashWinner
MakerOpenAIGoogle
TypeProprietaryProprietary
Context window128K tokens1M tokensGemini 3.8 Flash
Input price$2.5/M$0.75/MGemini 3.8 Flash
Output price$10/M$3.75/MGemini 3.8 Flash
Vision / multimodalNoYesGemini 3.8 Flash
Tool / function callingYesYes= Tie
Self-hostableNo (API only)No (API only)
LicenseProprietaryProprietary

Price gap & when to choose each

2.7×cheaper per output token

Gemini 3.8 Flash is ~2.7× cheaper than GPT Audio on output tokens ($3.75 vs $10 per M tokens).

Choose GPT Audio if…
  • You want frontier performance through a managed API
  • You value reliability & ecosystem
  • You don't want to manage infrastructure
Choose Gemini 3.8 Flash if…
  • You want frontier performance through a managed API
  • You need the longer 1M context window
  • You want the lower output price
  • You value reliability & ecosystem
  • You don't want to manage infrastructure

Feature comparison

CapabilityGPT AudioGemini 3.8 Flash
Open weights (downloadable)
Self-hostable
Runs fully offline
Vision / multimodal
Tool / function calling
1M+ context window

Benchmarks: GPT Audio vs Gemini 3.8 Flash

Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).

GPT Audio
Gemini 3.8 Flash
Intelligence index
41.2
Coding index
76.3
GPQA
95.3%
Humanity's Last Exam
47.8%
Long Context Reasoning
81.3%
SciCode
56.6%
τ-Bench Banking
44.9%
Terminal-Bench
87.6%
Speed
339 tok/s
Latency
12.31s
Intelligence per $
27.5

Benchmark data by Artificial Analysis.

How GPT Audio and Gemini 3.8 Flash score

🏆 Best value & openness: Gemini 3.8 Flash (3.3 vs 2.6 / 5)
CriterionGPT AudioGemini 3.8 Flash
Cost-efficiency3.54.0
Context window3.55.0
Openness1.51.5
Self-hosting1.01.0
Multimodality3.55.0

Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.

What each model is

GPT Audio Paid

OpenAI · Proprietary

The gpt-audio model is OpenAI's first generally available audio model. The new snapshot features an upgraded decoder for more natural sounding voices and maintains better voice consistency. Audio is priced...

Gemini 3.8 Flash Paid

Google · Proprietary

Gemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.

Other models in these families

These variants are tracked but not compared here — one page per family keeps the comparison readable.

Other variants tracked
Gemini 3.8 Flash (batch)Gemini 3.7 FlashGemini 3.7 Flash (batch)Gemini 3.6 FlashGemini 3.6 Flash (batch)Gemini 3.5 FlashGemini 3.5 Flash (batch)Gemini 3 Flash PreviewGemini 3 Flash Preview (batch)Gemini 2.5 FlashGemini 2.5 Flash (batch)Nano Banana 2 (Gemini 3.1 Flash Image)Nano Banana (Gemini 2.5 Flash Image)

Frequently asked questions

GPT Audio vs Gemini 3.8 Flash — which is cheaper?

Gemini 3.8 Flash is cheaper on output ($3.75/M vs $10/M).

Which has the larger context window?

Gemini 3.8 Flash offers the larger context window (1M tokens).

GPT Audio vs Gemini 3.8 Flash — which should I pick in 2026?

Choose Gemini 3.8 Flash for the lower output price ($3.75/M vs $10/M). It also gives you the larger 1M context window.

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