LLM Reference

DeciCoder 1B

Released
2023-08-15
Last refreshed
2026-05-19
Status
Researched 105d ago
Open sourceCommercial use: permitted

DeciCoder 1B is worth evaluating for general LLM work when its provider route and context window match the workload.

Use it for

  • Teams evaluating general LLM work
  • Workloads that can use a 4k context window
  • Buyers comparing 1 tracked provider route

Do not use it for

  • Vision or document-understanding workloads
  • Strict JSON or tool-calling flows
Specifications
Family
DeciCoder
Released
2023-08-15
Context
4k
Parameters
1B
Architecture
Decoder Only
Specialization
general
Openness
Open source
License
Apache 2.0OSI-approvedCommercial use: permitted
Weights
Unknown
Code
Unknown
Training
Fine-tuned
Created by

Automating neural architecture design

Tel Aviv, Israel
Founded 2019
Website
Pricing
Output / 1M
$0.070
Input / 1M
$0.070

Cheapest of 1 route · Microsoft Foundry

About

DeciCoder 1B is a 1 billion-parameter, open-source large language model focused on code generation 12. It excels at efficient and accurate code completion for Python, Java, and JavaScript using a unique Grouped Query Attention architecture with a 2048-token context window 13. Trained on a substantial dataset with a Fill-in-the-Middle objective, it offers impressive throughput, especially when used with Deci's Infery LLM inference engine 79. Although capable of single or multi-line code completion, it may produce suboptimal results as it's not an instruction-following model.

Top use-case fit

No primary decision-task fit is mapped for this model yet.

Capabilities

No model capability flags are currently sourced.

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.