Replit Code
replit-code
Last refreshed 2026-04-15. Next refresh: weekly.
Replit Code is worth evaluating for general LLM work when its provider route and context window match the workload.
Decision context: Coding task fit, 1 tracked provider route, and research from 2026-01-01.
Use it for
- Teams evaluating general LLM work
- Buyers comparing 1 tracked provider route
Do not use it for
- Vision or document-understanding workloads
- Strict JSON or tool-calling flows
Cheapest output
-
Replicate API per 1M tokens
Provider routes
1
Tracked API hosts
Quality / dollar
Unknown
No task benchmark coverage yet
Freshness
2026-01-01
Researched 137d ago
Top use-case fit
No primary decision-task fit is mapped for this model yet.
Provider price ladder
| Provider | Input / 1M | Output / 1M | Route |
|---|---|---|---|
| Replicate API | - | - | ServerlessPartial |
Benchmark peer barsfor Coding
No task-mapped benchmark peers are available for this model yet.
Migration checks
No linked migration route is available for this model yet.
About
Replit Code is a series of large language models (LLMs) focused on code completion and generation, such as Replit Code v1.3B and v1.5 3B. These models are trained on extensive datasets featuring various programming languages, including Python, JavaScript, and Java 56. They utilize advancements like Flash Attention and AliBi positional embeddings to enhance training and inference efficiency 56. Capabilities encompass code completion, generation from natural language prompts, and support for multiple languages 5. These models are integrated into Replit's platform for code suggestions and explanation tools, initially offered through paid services but now with basic AI features available for free 12. They are also accessible on Hugging Face, inviting community participation and development 10. Performance varies by model version and language used 78.
Capabilities
No model capability flags are currently sourced.
Specifications
Created by
Online coding platform with AI-assisted features.