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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. Qwen3 30B A3BAlibabaRemove
  2. Muse WonderMetaRemove
  3. Gemini 4 ArgonGoogleRemove
  4. Kimi K3.1 ProMoonShot AIRemove

4 is the maximum. Remove one to add another.

qwen3-30b-a3b vs muse-wonder vs gemini-4-argon vs kimi-k3.1-pro
AttributeQwen3 30B A3Bqwen3-30b-a3bMuse Wondermuse-wonderGemini 4 Argongemini-4-argonKimi K3.1 Prokimi-k3.1-pro
Pricing
Input$0.05 / 1M$4.00 / 1M$2.00 / 1M$2.00 / 1M
Output$0.15 / 1M$20.00 / 1M$10.00 / 1M$10.00 / 1M
Cache Write (5m)$0.05 / 1M$4.00 / 1M$2.00 / 1M$2.00 / 1M
Cache Write (1h)$0.05 / 1M$4.00 / 1M$2.00 / 1M$2.00 / 1M
Cache Read$0.05 / 1M$4.00 / 1M$2.00 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context41.0K1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesYesYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderAlibabaMetaGoogleMoonShot AI
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released————
Description
SummaryQwen3 is the latest generation in the Qwen large language model series, featuring both dense and Mixture-of-Experts (MoE) architectures designed to excel in reasoning, multilingual understanding, and advanced agentic tasks. A defining capability of Qwen3 is its ability to seamlessly switch between a thinking mode for complex, multi-step reasoning and a non-thinking mode for efficient, high-quality dialogue—delivering strong versatility across use cases. Compared with earlier models such as QwQ and Qwen2.5, Qwen3 demonstrates substantial performance gains in mathematics, coding, commonsense reasoning, creative writing, and interactive conversation. The Qwen3-30B-A3B variant comprises 30.5B total parameters with 3.3B activated, 48 layers, and 128 experts (with 8 activated per task). With support for up to 131K token context lengths via YaRN, it sets a new benchmark for open-source MoE models in both capability and efficiency.Muse Wonder is Meta’s frontier multimodal reasoning model, designed for complex personal and professional agentic workflows. It supports text, image, video, audio, and PDF inputs with text output and features a 1M-token context window for sustained reasoning across long-running tasks. Optimized for autonomous execution and multi-agent orchestration, Muse Wonder can plan, delegate to subagents, coordinate parallel tool use, recover from errors, and operate browsers and applications across desktop and mobile environments. With cross-conversation context retrieval and its Active Focus training approach, it is well suited for complex software engineering, multi-file refactoring, computer use, and end-to-end workflows requiring persistence, adaptability, and minimal supervision.Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across long, multi-step tasks and to turn long documents mixing text, tables, charts and images into a single grounded output. It leads the Vals Index across finance, legal, coding and tax work, and supports long decode of up to 1M output tokens in a single response.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.