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Compare models

Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. Gemma 3 1BGoogleRemove
  2. GLM 5.3Z.AIRemove
  3. Muse Spark 1.3MetaRemove
  4. Qwen3.8 27BAlibabaRemove

4 is the maximum. Remove one to add another.

gemma-3-1b-it vs glm-5.3 vs muse-spark-1.3 vs qwen3.8-27b
AttributeGemma 3 1Bgemma-3-1b-itGLM 5.3glm-5.3Muse Spark 1.3muse-spark-1.3Qwen3.8 27Bqwen3.8-27b
Pricing
Input$0 / 1M$1.40 / 1M$1.25 / 1M$0.45 / 1M
Output$0 / 1M$4.40 / 1M$4.25 / 1M$3.20 / 1M
Cache Write (5m)$0.00 / 1M$1.40 / 1M$1.25 / 1M$0.45 / 1M
Cache Write (1h)$0.00 / 1M$1.40 / 1M$1.25 / 1M$0.45 / 1M
Cache Read$0.00 / 1M$1.40 / 1M$1.25 / 1M$0.45 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context32.8K1M1M262K
Max outputN/AN/AN/AN/A
Capabilities
VisionNoNoYesYes
Function CallingNoYesYesYes
JSON ModeNoYesYesYes
StreamingNoYesYesYes
Catalogue
ProviderGoogleZ.AIMetaAlibaba
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
SummaryGLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.Muse Spark 1.3 is Meta's multimodal reasoning model designed for long-running agentic, multi-agent, and coding workflows. It maintains context and information across extended tasks, enabling reliable execution in complex, multi-step environments. The model is optimized to resolve conflicting information, seek clarification or confirmation when necessary, and execute concisely, making it well suited for autonomous agents, collaborative multi-agent systems, and long-horizon software engineering workflows.Qwen3.8 27B is an open-weight dense vision-language model from Qwen, designed for coding, professional knowledge work, research, and multimodal interaction. It combines strong text and visual understanding with capabilities optimized for sustained, real-world agentic tasks. The model supports flexible thinking modes that can be enabled for deeper reasoning or disabled for faster execution, making it well suited for long-running agents, multimodal workflows, coding assistants, and cost-conscious self-hosted deployments.