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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. GPT-4o Mini TranscribeOpenAIRemove
  2. Claude Fable 5.1AnthropicRemove
  3. DeepSeek V4.1 FlashDeepSeekRemove
gpt-4o-mini-transcribe vs claude-fable-5.1 vs deepseek-v4.1-flash
AttributeGPT-4o Mini Transcribegpt-4o-mini-transcribeClaude Fable 5.1claude-fable-5.1DeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input$0.625 / 1M$10.00 / 1M$0.30 / 1M
Output$0.625 / 1M$50.00 / 1M$1.20 / 1M
Cache Write (5m)Not applicable$12.50 / 1M$0.30 / 1M
Cache Write (1h)Not applicable$20.00 / 1M$0.30 / 1M
Cache ReadNot applicable$1.00 / 1M$0.30 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context128K1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesYes
JSON ModeYesYesYes
StreamingNoYesYes
Catalogue
ProviderOpenAIAnthropicDeepSeek
Categoryvoicechatchat
Charge typePay As You GoPay As You GoPay As You Go
Released
Description
SummaryGPT-4o Mini Transcribe is a smaller, cost-efficient speech-to-text model built on GPT-4o Mini's audio capabilities. It is designed for high-volume transcription workloads, delivering reliable performance with lower cost and latency. Priced per token (input and output), it provides transparent, fine-grained billing, making it well suited for scalable transcription pipelines, real-time applications, and cost-sensitive deployments.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.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.