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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. Kimi K3.1 ProMoonShot AIRemove
  2. Transcribe 1 ProFish AudioRemove
  3. Qwen3.8 2.4T A95BAlibabaRemove
kimi-k3.1-pro vs transcribe-1-pro vs qwen3.8-2.4t-a95b
AttributeKimi K3.1 Prokimi-k3.1-proTranscribe 1 Protranscribe-1-proQwen3.8 2.4T A95Bqwen3.8-2.4t-a95b
Pricing
Input$2.00 / 1M— Not priced per input token$1.80 / 1M
Output$10.00 / 1M— Not priced per output token$5.40 / 1M
Cache Write (5m)$2.00 / 1MNot applicable$1.80 / 1M
Cache Write (1h)$2.00 / 1MNot applicable$1.80 / 1M
Cache Read$2.00 / 1MNot applicable$1.80 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max context1MN/A262K
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderMoonShot AIFish AudioAlibaba
Categorychatvoicechat
Charge typePay As You GoPay As You GoPay As You Go
Released—2026-09-24—
Description
SummaryKimi 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.Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio.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.