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.
- OlympicCoder 32BOpen R1Remove
- Hy4 previewTencentRemove
- DeepSeek V4.1 FlashDeepSeekRemove
- Qwen3.8 27BAlibabaRemove
4 is the maximum. Remove one to add another.
| Attribute | OlympicCoder 32Bolympiccoder-32b | Hy4 previewhy4-preview | DeepSeek V4.1 Flashdeepseek-v4.1-flash | Qwen3.8 27Bqwen3.8-27b |
|---|---|---|---|---|
| Pricing | ||||
| Input | $0 / 1M | $0.834 / 1M | $0.30 / 1M | $0.45 / 1M |
| Output | $0 / 1M | $2.50 / 1M | $1.20 / 1M | $3.20 / 1M |
| Cache Write (5m) | $0.00 / 1M | $0.834 / 1M | $0.30 / 1M | $0.45 / 1M |
| Cache Write (1h) | $0.00 / 1M | $0.834 / 1M | $0.30 / 1M | $0.45 / 1M |
| Cache Read | $0.00 / 1M | $0.834 / 1M | $0.30 / 1M | $0.45 / 1M |
| Web Search | $0 / 1M | $0 / 1M | $0 / 1M | $0 / 1M |
| Context | ||||
| Max context | 32.8K | 1M | 1M | 262K |
| Max output | N/A | N/A | N/A | N/A |
| Capabilities | ||||
| Vision | No | Yes | Yes | Yes |
| Function Calling | No | Yes | Yes | Yes |
| JSON Mode | No | Yes | Yes | Yes |
| Streaming | No | Yes | Yes | Yes |
| Catalogue | ||||
| Provider | Open R1 | Tencent | DeepSeek | Alibaba |
| Category | chat | chat | chat | chat |
| Charge type | Pay As You Go | Pay As You Go | Pay As You Go | Pay As You Go |
| Released | — | — | — | — |
| Description | ||||
| Summary | — | Tencent Hy4 Preview is a Mixture-of-Experts (MoE) model from Tencent, featuring 770B total parameters with 49B activated per token. It is designed for coding agents, complex tool-driven workflows, and professional productivity tasks that require strong planning and reliable execution. Optimized for context continuity and sustained multi-step work, Hy4 Preview is well suited for long-horizon coding, agentic automation, tool orchestration, and complex real-world workflows. | 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. | 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. |