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.
| Attribute | GLM 5.3glm-5.3 | Mixtral 8x7B Instructmixtral-8x7b-instruct | Qwen3.8 27Bqwen3.8-27b |
|---|---|---|---|
| Pricing | |||
| Input | $1.40 / 1M | $60.00 / 1M | $0.45 / 1M |
| Output | $4.40 / 1M | $60.00 / 1M | $3.20 / 1M |
| Cache Write (5m) | $1.40 / 1M | $60.00 / 1M | $0.45 / 1M |
| Cache Write (1h) | $1.40 / 1M | $60.00 / 1M | $0.45 / 1M |
| Cache Read | $1.40 / 1M | $60.00 / 1M | $0.45 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 1M | 32.8K | 262K |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | No | No | Yes |
| Function Calling | Yes | No | Yes |
| JSON Mode | Yes | No | Yes |
| Streaming | Yes | No | Yes |
| Catalogue | |||
| Provider | Z.AI | Mistral AI | Alibaba |
| Category | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | GLM-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. | — | 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. |