Using DeepSeek Math 7B on Replicate API
Implementation guide · DeepSeek Math · DeepSeek
Replicate API exposes DeepSeek Math 7B through model ID deepseek-math-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-math-7b— see the documentation for request format. - 3
Code Examples
pip install replicateREPLICATE_API_TOKENdeepseek-math-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-math-7b format: "owner/model-name" (latest version) or "owner/model-name:version-hash"
output = replicate.run(
"deepseek-math-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
No model capability flags are currently sourced.
About DeepSeek Math 7B
DeepSeek Math 7B is a powerful family of large language models by DeepSeek AI, crafted for advanced mathematical reasoning. The base model begins as DeepSeek-Coder-v1.5 7B, further pre-trained with 500 billion tokens, encompassing math-focused and general data sources. This model attains a 51.7% score on the MATH benchmark, demonstrating competitive prowess without external aids. Enhanced by instruction tuning, DeepSeekMath-Instruct 7B boosts its mathematical expertise. The DeepSeekMath-RL 7B model, further refined by a novel Group Relative Policy Optimization algorithm, capitalizes on reinforcement learning for superior performance.