Using DeepSeek VL 7B on Replicate API
Implementation guide · DeepSeek VL · DeepSeek
Replicate API exposes DeepSeek VL 7B through model ID deepseek-vl-7b. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-09-18. Next refresh: weekly.
Quick Start
- 1
- 2Use the Replicate API SDK or REST API to call
deepseek-vl-7b— see the documentation for request format. - 3
Code Examples
pip install replicateREPLICATE_API_TOKENdeepseek-vl-7bReplicate uses "owner/model-name" format (e.g. "meta/meta-llama-3-8b-instruct") for the latest version, or "owner/model-name:version-sha" to pin to a specific version. The REST endpoint splits owner and model-name into the path: /v1/models/{owner}/{model-name}/predictions.
import replicate
# reads REPLICATE_API_TOKEN from env
# deepseek-vl-7b format: "owner/model-name" (latest version) or "owner/model-name:version-hash"
output = replicate.run(
"deepseek-vl-7b",
input={"prompt": "Hello"}
)
# Output is a list or generator depending on the model
print("".join(output))Pricing on Replicate API
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.05 |
| Output tokens | $0.25 |
Capabilities
About DeepSeek VL 7B
DeepSeek-VL 7B is an open-source vision-language model engineered for robust real-world applications. With its general multimodal understanding capabilities, it can process logical diagrams, web pages, formulas, scientific literature, natural images, and complex scenarios involving embodied intelligence. The model features a hybrid vision encoder that integrates SigLIP-L and SAM-B, allowing it to handle high-resolution (1024 x 1024) image inputs. Built on the DeepSeek-LLM-7b-base foundation, it is pre-trained on roughly 2 trillion text tokens and further trained on approximately 400 billion vision-language tokens.