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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. DeepSeek V3.2 (Thinking)DeepSeekRemove
  2. DeepSeek V4.1 FlashDeepSeekRemove
  3. Claude Fable 5.1AnthropicRemove
deepseek-v3.2-thinking vs deepseek-v4.1-flash vs claude-fable-5.1
AttributeDeepSeek V3.2 (Thinking)deepseek-v3.2-thinkingDeepSeek V4.1 Flashdeepseek-v4.1-flashClaude Fable 5.1claude-fable-5.1
Pricing
Input$0.19 / 1M$0.30 / 1M$10.00 / 1M
Output$0.275 / 1M$1.20 / 1M$50.00 / 1M
Cache Write (5m)$0.19 / 1M$0.30 / 1M$12.50 / 1M
Cache Write (1h)$0.19 / 1M$0.30 / 1M$20.00 / 1M
Cache Read$0.19 / 1M$0.30 / 1M$1.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context163.8K1M1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderDeepSeekDeepSeekAnthropic
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryDeepSeek-V3.2 is an efficiency-focused large model that combines strong reasoning with reliable tool use. It introduces DeepSeek Sparse Attention to lower compute costs for long contexts while preserving quality, and uses large-scale reinforcement learning to reach GPT-5-class reasoning (including top IMO/IOI results). An agentic task-synthesis pipeline improves how it reasons with tools in interactive settings — and developers can toggle reasoning on or off as needed.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.Claude Fable 5.1 is an upgraded version of Fable 5, delivering broad improvements with particularly strong gains in agentic coding, long-running workflows, and professional knowledge work. It excels at large code refactors, front-end and visual code generation, financial analysis, and complex analytical tasks. Compared with Fable 5, it also produces more concise plans and summaries while maintaining strong performance across extended tasks, making it a natural upgrade for existing Fable workflows and a strong option alongside Opus 5 for reasoning-intensive applications.