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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. Qwen3.8 27BAlibabaRemove
  2. Gemini 3.5 TranscribeGoogleRemove
  3. DeepSeek V4.1 FlashDeepSeekRemove
qwen3.8-27b vs gemini-3.5-transcribe vs deepseek-v4.1-flash
AttributeQwen3.8 27Bqwen3.8-27bGemini 3.5 Transcribegemini-3.5-transcribeDeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input$0.45 / 1M— Not priced per input token$0.30 / 1M
Output$3.20 / 1M— Not priced per output token$1.20 / 1M
Cache Write (5m)$0.45 / 1MNot applicable$0.30 / 1M
Cache Write (1h)$0.45 / 1MNot applicable$0.30 / 1M
Cache Read$0.45 / 1MNot applicable$0.30 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context262K98.3K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderAlibabaGoogleDeepSeek
Categorychatvoicechat
Charge typePay As You GoPay As You GoPay As You Go
Released—2026-09-25—
Description
SummaryQwen3.8 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.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion.