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Arcee AI: Coder Large

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 long diff review in a single call, and understands 30‑plus programming languages with special attention to TypeScript, Go and Terraform. Internal benchmarks show 5–8 pt gains over CodeLlama‑34 B‑Python on HumanEval and competitive BugFix scores thanks to a reinforcement pass that rewards compilable output. The model emits structured explanations alongside code blocks by default, making it suitable for educational tooling as well as production copilot scenarios. Cost‑wise, Together AI prices it well below proprietary incumbents, so teams can scale interactive coding without runaway spend.

Context Window

33K

Input Price

$0.5000/M tokens

Output Price

$0.8000/M tokens

Modality

text->text

Pricing Breakdown
Cost per million tokens for input and output
Input$0.5000/M tokens
Output$0.8000/M tokens

Cost Example: Processing 10,000 input tokens and generating 1,000 output tokens would cost approximately $0.005800

Context Window Size
Maximum tokens the model can process in a single request
Context Window33K tokens
3% of 1M max

~25K

Words Equivalent

~16

Pages of Text

~328

Code Functions

Best Use Cases
What this model excels at
CodingProgrammingDevelopment

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