Deepseek Coder 1.3B Instruct
DeepSeek builds the Deepseek Coder 1.3B Instruct, a chat model exceling at code completion, generation, and review tasks, thanks to its pre-training on a large project-level code corpus with a 16,384 token context window. This model is notable for its massive training data of 2T tokens, comprising 87% code and 13% natural language in both English and Chinese.
Input
Output
Context
16K
Max Output
1K
Parameters
1.3B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
Loading capabilities…
Resources & Links
Estimated GPU requirements for Deepseek Coder 1.3B Instruct
Estimates based on INT8 quantization at up to 32K context. A count above one assumes tensor parallelism across the cards. Actual requirements vary by framework and configuration.
More models by DeepSeek
The creator's other models in the catalog, with their context, size and license where published.
Compare it, or keep browsing
Put this model beside its alternatives on the same evidence, or go back to the full catalog.
Frequently asked questions about Deepseek Coder 1.3B Instruct
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Deepseek Coder 1.3B Instruct advertises a context window of 16,384 tokens, with a maximum output of 512 tokens in a single response. The figure is the creator's published maximum; a given host may serve less, and the gateway routes on what each host actually serves.
Yes. Deepseek Coder 1.3B Instruct is an open-weight model released under the Other license, so the weights can be downloaded and self-hosted within that license's terms.
Deepseek Coder 1.3B Instruct accepts Text and produces Text. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
No published benchmark result for Deepseek Coder 1.3B Instruct is in the catalog yet, so the model is shown as unmeasured. It is not ranked or estimated; the router treats it as unknown for every task until a suite measures it.
Not on the managed pool today; Deepseek Coder 1.3B Instruct is listed for reference and comparison. Connect your own provider key or endpoint that serves it and the gateway runs it on your account, with routing decisions recorded the same way.
About 1.8 GB at INT8 for the weights and a default context, from the catalog's 1.3B parameter count; FP16 needs roughly twice that, and long contexts or many concurrent requests add KV cache on top. The GPU section on this page lists cards that hold it, and the capacity planner sizes it for your context length and traffic.
Fields collected from public registries, host APIs and benchmark publishers, each tagged with its source.
Last updated: Aug 28, 2026
Put intelligence in the middle.
One gateway in front of every model, with your policies applied and every decision on record. Start with $5 of credit and 5,000 routing decisions a month, no card required.