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 | Claude Opus 4.6claude-opus-4-6 | DeepSeek V4.1 Flashdeepseek-v4.1-flash | GLM 5.3 Flashglm-5.3-flash |
|---|---|---|---|
| Pricing | |||
| Input | $4.00 / 1M | $0.30 / 1M | $0.075 / 1M |
| Output | $20.00 / 1M | $1.20 / 1M | $0.25 / 1M |
| Cache Write (5m) | $5.00 / 1M | $0.30 / 1M | $0.075 / 1M |
| Cache Write (1h) | $8.00 / 1M | $0.30 / 1M | $0.075 / 1M |
| Cache Read | $0.40 / 1M | $0.30 / 1M | $0.075 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | |||
| Max context | 1M | 1M | 1M |
| Max output | N/A | N/A | N/A |
| Capabilities | |||
| Vision | Yes | Yes | Yes |
| Function Calling | Yes | Yes | Yes |
| JSON Mode | Yes | Yes | Yes |
| Streaming | Yes | Yes | Yes |
| Catalogue | |||
| Provider | Anthropic | DeepSeek | Z.AI |
| Category | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — |
| Description | |||
| Summary | Opus 4.6 is Anthropic's most capable model for coding and long-running professional workflows, designed for agents that operate across entire workflows rather than single prompts. It demonstrates strong performance on large codebases, complex refactoring, and multi-step debugging, with improved contextual understanding, deeper problem decomposition, and higher reliability on challenging engineering tasks compared to earlier generations. Beyond software development, Opus 4.6 excels at sustained knowledge work, producing near production-ready documents, technical plans, and analyses in a single pass while maintaining coherence across long outputs and extended sessions. Its strength in persistence, judgment, and structured execution makes it well suited for technical design, migration planning, and end-to-end project execution. | DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion. | GLM-5.3-Flash is Z.AI's efficient native multimodal model, designed for coding and long-horizon agentic workflows. It combines strong multimodal capabilities with an architecture optimized for responsive, cost-efficient task execution. Built on a hybrid sparse and linear attention architecture, GLM-5.3-Flash maintains accurate long-context behavior while reducing computational overhead, making it well suited for coding agents, extended multi-step tasks, and scalable production workloads. |