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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 Sonnet 5.5AnthropicRemove
  2. Kimi K3.1 ProMoonShot AIRemove
  3. Qwen3.8 2.4T A95BAlibabaRemove
claude-sonnet-5.5 vs kimi-k3.1-pro vs qwen3.8-2.4t-a95b
AttributeClaude Sonnet 5.5claude-sonnet-5.5Kimi K3.1 Prokimi-k3.1-proQwen3.8 2.4T A95Bqwen3.8-2.4t-a95b
Pricing
Input$2.00 / 1M$2.00 / 1M$1.80 / 1M
Output$10.00 / 1M$10.00 / 1M$5.40 / 1M
Cache Write (5m)$2.50 / 1M$2.00 / 1M$1.80 / 1M
Cache Write (1h)$4.00 / 1M$2.00 / 1M$1.80 / 1M
Cache Read$0.10 / 1M$2.00 / 1M$1.80 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M1M262K
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeYesYesYes
StreamingYesYesYes
Catalogue
ProviderAnthropicMoonShot AIAlibaba
Categorychatchatchat
Charge typePay As You GoPay As You GoPay As You Go
Released———
Description
SummaryClaude Sonnet 5.5 is Anthropic's Sonnet-class model for well-scoped everyday work, serving as a direct upgrade to Sonnet 5. It excels at feature development, bug fixing, and creating polished documents, presentations, and spreadsheets, while offering clearer writing and communication than its predecessor.Kimi K3.1 Pro is Moonshot AI's flagship open-weight multimodal reasoning model, building on Kimi K3 with enhanced post-training for advanced reasoning and autonomous task execution. It features a 1M-token context window and native image and video understanding, enabling complex, long-context multimodal workflows. Optimized for long-horizon coding, 3D creation, financial research, and end-to-end agentic knowledge work, Kimi K3.1 Pro is well suited for autonomous software engineering, multimodal analysis, and complex professional workflows that require sustained reasoning and reliable execution.Qwen3.8 2.4T A95B is Qwen's open-weight sparse Mixture-of-Experts (MoE) model and the open-weight counterpart to Qwen3.8 Max. It features 2.4T total parameters with 95B activated per token, combining frontier-scale capacity with efficient sparse inference. Designed for coding, research, complex reasoning, and agentic workflows, the model is well suited for demanding long-horizon tasks and advanced autonomous systems while providing the flexibility and customization benefits of open weights.