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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. Mistral Small 4Mistral AIRemove
  2. Claude Fable 5.2AnthropicRemove
mistral-small-2603 vs claude-fable-5.2
AttributeMistral Small 4mistral-small-2603Claude Fable 5.2claude-fable-5.2
Pricing
Input$0.15 / 1M$8.00 / 1M
Output$0.60 / 1M$40.00 / 1M
Cache Write (5m)$0.15 / 1M$10.00 / 1M
Cache Write (1h)$0.15 / 1M$16.00 / 1M
Cache Read$0.15 / 1M$0.20 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context262.1K1M
Max outputN/AN/A
Capabilities
VisionYesYes
Function CallingYesYes
JSON ModeYesYes
StreamingYesYes
Catalogue
ProviderMistral AIAnthropic
Categorychatchat
Charge typePay As You GoPay As You Go
Released——
Description
SummaryMistral Small 4 is the latest release in the Mistral Small family, unifying capabilities from multiple flagship models into a single system. It integrates strong reasoning (Magistral), multimodal understanding (Pixtral), and agentic coding capabilities (Devstral), enabling a versatile, all-in-one model. Designed to handle complex analysis, software development, and visual tasks within the same workflow, Mistral Small 4 is well suited for integrated agentic applications and end-to-end problem solving across domains.Claude Fable 5.2 is Anthropic's most capable model for advanced technical work and open-ended problem solving, delivering significant improvements in coding, reasoning, and vision over Fable 5.1. It excels at exceptionally complex tasks, including large-scale software migrations, electronic system design, and advanced scientific and mathematical research. With up to 30% faster output generation, clearer communication, and always-on adaptive extended thinking, Fable 5.2 supports configurable reasoning effort from low to max (default high), with thinking preserved across turns. Designed for frontier engineering, scientific discovery, and ambitious long-horizon agentic workflows, it complements Opus 5.5 as a specialized option for the most demanding technical challenges.