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Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. Gemini 3.1 Flash Lite Image (Google AI Studio)GoogleEnterprise & partner accessRemove
  2. Gemini 3.5 TranscribeGoogleRemove
  3. Qwen3.8 27BAlibabaRemove
gemini-3.1-flash-lite-image-aistudio vs gemini-3.5-transcribe vs qwen3.8-27b
AttributeGemini 3.1 Flash Lite Image (Google AI Studio)gemini-3.1-flash-lite-image-aistudioGemini 3.5 Transcribegemini-3.5-transcribeQwen3.8 27Bqwen3.8-27b
Pricing
Request$0.0336 / request——
BillingPay Per Request——
Cache Write (5m)Not applicableNot applicable$0.45 / 1M
Cache Write (1h)Not applicableNot applicable$0.45 / 1M
Cache ReadNot applicableNot applicable$0.45 / 1M
Input—— Not priced per input token$0.45 / 1M
Output—— Not priced per output token$3.20 / 1M
Web Search—$0 / 1M$0 / 1M
Context
Max contextN/A98.3K262K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingNoYesYes
JSON ModeNoNoYes
StreamingNoNoYes
Catalogue
ProviderGoogleGoogleAlibaba
Categoryimagevoicechat
Charge typePay Per RequestPay As You GoPay As You Go
Released—2026-09-25—
Description
SummaryGemini 3.1 Flash Lite Image served from Google AI Studio. Billed per image at US$0.0336. Call it through /v1/chat/completions with stream set to false; the image is returned in the message content as a base64 data URI. Maximum output resolution is 1K. A request for a larger size returns a 1K image with the same aspect ratio at the same price. When a size is reduced, the response carries an X-Image-Resolution-Capped header with the requested and delivered size.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments.