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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. Gemma 3 1BGoogleRemove
  2. Qwen3.8 27BAlibabaRemove
  3. DeepSeek V4.1 FlashDeepSeekRemove
gemma-3-1b-it vs qwen3.8-27b vs deepseek-v4.1-flash
AttributeGemma 3 1Bgemma-3-1b-itQwen3.8 27Bqwen3.8-27bDeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input$0 / 1M$0.45 / 1M$0.30 / 1M
Output$0 / 1M$3.20 / 1M$1.20 / 1M
Cache Write (5m)$0.00 / 1M$0.45 / 1M$0.30 / 1M
Cache Write (1h)$0.00 / 1M$0.45 / 1M$0.30 / 1M
Cache Read$0.00 / 1M$0.45 / 1M$0.30 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context32.8K262K1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderGoogleAlibabaDeepSeek
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
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.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.