DeepSeekDeepSeek Coder V2 Lite Instruct
DeepSeek develops the Deepseek Coder V 2 Lite Instruct, a chat model exceling at code-related tasks such as code completion, generation, and review, as well as reasoning. Its Mixture-of-Experts (MoE) architecture and extended context length of 131,072 tokens enable substantial enhancements in coding and mathematical reasoning capabilities.
Input
Output
Context
131K
Max Output
-
Parameters
15.7B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
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Benchmarks
Resources & Links
Estimated GPU requirements for DeepSeek Coder V2 Lite 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.
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Frequently asked questions about DeepSeek Coder V2 Lite Instruct
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
DeepSeek Coder V2 Lite Instruct advertises a context window of 131,072 tokens. The figure is the creator's published maximum; a given provider may serve less, and the gateway routes on what each provider actually serves.
Yes. DeepSeek Coder V2 Lite 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 V2 Lite 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.
DeepSeek Coder V2 Lite Instruct has published results from Artificial Analysis, shown by suite in the benchmarks card above exactly as the publisher reported them. Scores are not combined across suites, and a suite that has not measured DeepSeek Coder V2 Lite Instruct is shown as not available rather than estimated.
Not on the managed pool today; DeepSeek Coder V2 Lite 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 15.9 GB at INT8 for the weights and a default context, from the catalog's 15.7B 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, provider APIs and benchmark publishers, each tagged with its source.
Last updated: Nov 4, 2026
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