Coder‑Large is a 32 B‑parameter offspring of Qwen 2.5‑Instruct that has been further trained on permissively‑licensed GitHub, CodeSearchNet and synthetic bug‑fix corpora. It supports a 32k context window, enabling multi‑file refactoring or …
Model details →Arcee AI: Coder Large vs DeepSeek: R1
DeepSeek: R1 wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass. Fully open-source model & [technical report](h…
Model details →Side-by-side comparison
| Capability | Arcee AI: Coder Large | DeepSeek: R1 | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 33K | 64K | 🏆 DeepSeek: R1 |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.50 | $0.70 | 🏆 Arcee AI: Coder Large |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.80 | $2.50 | 🏆 Arcee AI: Coder Large |
| Tool / function calling First-class support for emitting structured tool calls. | — | Yes | 🏆 DeepSeek: R1 |
| Vision input Accepts image inputs alongside text. | — | — | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | — | Yes | 🏆 DeepSeek: R1 |
Frequently asked questions
Is Arcee AI: Coder Large better than DeepSeek: R1?
DeepSeek: R1 wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Arcee AI: Coder Large and DeepSeek: R1?
Input: $0.50 vs $0.70 per 1M tokens. Output: $0.80 vs $2.50 per 1M tokens.
What context windows do Arcee AI: Coder Large and DeepSeek: R1 support?
Arcee AI: Coder Large supports up to 33K tokens. DeepSeek: R1 supports up to 64K tokens.
Do both Arcee AI: Coder Large and DeepSeek: R1 support tool calling?
Arcee AI: Coder Large: not advertised. DeepSeek: R1: yes.