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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. Claude Fable 5.2AnthropicRemove
  2. Qwen3 Next 80B A3B ThinkingAlibabaRemove
claude-fable-5.2 vs qwen3-next-80b-a3b-thinking
AttributeClaude Fable 5.2claude-fable-5.2Qwen3 Next 80B A3B Thinkingqwen3-next-80b-a3b-thinking
Pricing
Input$8.00 / 1M$0.10 / 1M
Output$40.00 / 1M$0.40 / 1M
Cache Write (5m)$10.00 / 1M$0.10 / 1M
Cache Write (1h)$16.00 / 1M$0.10 / 1M
Cache Read$0.20 / 1M$0.10 / 1M
Web Search$0 / 1M$0 / 1M
Context
Max context1M262.1K
Max outputN/AN/A
Capabilities
VisionYesNo
Function CallingYesYes
JSON ModeYesYes
StreamingYesYes
Catalogue
ProviderAnthropicAlibaba
Categorychatchat
Charge typePay As You GoPay As You Go
Released——
Description
SummaryClaude 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.Qwen3-Next-80B-A3B-Thinking is a reasoning-first chat model designed for difficult multi-step tasks such as math proofs, code synthesis and debugging, logical reasoning, and agentic planning. It outputs structured thinking traces by default, emphasizing stability over long chains of thought, efficient inference scaling, and strong instruction following. Suited for agent frameworks, tool use, retrieval-heavy workflows, and benchmarks requiring step-by-step solutions, it supports long detailed outputs and faster generation via throughput-optimized techniques, operating exclusively in thinking mode.