 |
In March, Amazon Net Providers (AWS) grew to become the first cloud service supplier to ship DeepSeek-R1 in a serverless manner by launching it as a totally managed, typically obtainable mannequin in Amazon Bedrock. Since then, prospects have used DeepSeek-R1’s capabilities via Amazon Bedrock to construct generative AI functions, benefiting from the Bedrock’s strong guardrails and complete tooling for secure AI deployment.
In the present day, I’m excited to announce DeepSeek-V3.1 is now obtainable as a totally managed basis mannequin in Amazon Bedrock. DeepSeek-V3.1 is a hybrid open weight mannequin that switches between pondering mode (chain-of-thought reasoning) for detailed step-by-step evaluation and non-thinking mode (direct solutions) for sooner responses.
In keeping with DeepSeek, the pondering mode of DeepSeek-V3.1 achieves comparable reply high quality with higher outcomes, stronger multi-step reasoning for complicated search duties, and massive good points in pondering effectivity in contrast with DeepSeek-R1-0528.
| Benchmarks | DeepSeek-V3.1 | DeepSeek-R1-0528 |
|---|---|---|
| Browsecomp | 30.0 | 8.9 |
| Browsecomp_zh | 49.2 | 35.7 |
| HLE | 29.8 | 24.8 |
| xbench-DeepSearch | 71.2 | 55.0 |
| Frames | 83.7 | 82.0 |
| SimpleQA | 93.4 | 92.3 |
| Seal0 | 42.6 | 29.7 |
| SWE-bench Verified | 66.0 | 44.6 |
| SWE-bench Multilingual | 54.5 | 30.5 |
| Terminal-Bench | 31.3 | 5.7 |
DeepSeek-V3.1 mannequin efficiency in software utilization and agent duties has considerably improved via post-training optimization in comparison with earlier DeepSeek fashions. DeepSeek-V3.1 additionally helps over 100 languages with near-native proficiency, together with considerably improved functionality in low-resource languages missing massive monolingual or parallel corpora. You possibly can construct world functions to ship enhanced accuracy and lowered hallucinations in comparison with earlier DeepSeek fashions, whereas sustaining visibility into its decision-making course of.
Listed below are your key use circumstances utilizing this mannequin:
- Code technology – DeepSeek-V3.1 excels in coding duties with enhancements in software program engineering benchmarks and code agent capabilities, making it supreme for automated code technology, debugging, and software program engineering workflows. It performs effectively on coding benchmarks whereas delivering high-quality outcomes effectively.
- Agentic AI instruments – The mannequin options enhanced software calling via post-training optimization, making it robust in software utilization and agentic workflows. It helps structured software calling, code brokers, and search brokers, positioning it as a strong selection for constructing autonomous AI programs.
- Enterprise functions – DeepSeek fashions are built-in into varied chat platforms and productiveness instruments, enhancing consumer interactions and supporting customer support workflows. The mannequin’s multilingual capabilities and cultural sensitivity make it appropriate for world enterprise functions.
As I discussed in my earlier put up, when implementing publicly obtainable fashions, give cautious consideration to information privateness necessities when implementing in your manufacturing environments, verify for bias in output, and monitor your outcomes by way of information safety, accountable AI, and mannequin analysis.
You possibly can entry the enterprise-grade safety features of Amazon Bedrock and implement safeguards personalized to your software necessities and accountable AI insurance policies with Amazon Bedrock Guardrails. You too can consider and examine fashions to establish the optimum mannequin on your use circumstances by utilizing Amazon Bedrock mannequin analysis instruments.
Get began with the DeepSeek-V3.1 mannequin in Amazon Bedrock
To check the DeepSeek-V3.1 mannequin in Amazon Bedrock console, select Chat/Textual content underneath Playgrounds within the left menu pane. Then select Choose mannequin within the higher left, and choose DeepSeek because the class and DeepSeek-V3.1 because the mannequin. Then select Apply.
Utilizing the chosen DeepSeek-V3.1 mannequin, I run the next immediate instance about technical structure choice.
Define the high-level structure for a scalable URL shortener service like bit.ly. Talk about key elements like API design, database selection (SQL vs. NoSQL), how the redirect mechanism works, and the way you'd generate distinctive brief codes.
You possibly can flip the pondering on and off by toggling Mannequin reasoning mode to generate a response’s chain of thought previous to the ultimate conclusion.
You too can entry the mannequin utilizing the AWS Command Line Interface (AWS CLI) and AWS SDK. This mannequin helps each the InvokeModel and Converse API. You possibly can try a broad vary of code examples for a number of use circumstances and a wide range of programming languages.
To study extra, go to DeepSeek mannequin inference parameters and responses within the AWS documentation.
Now obtainable
DeepSeek-V3.1 is now obtainable within the US West (Oregon), Asia Pacific (Tokyo), Asia Pacific (Mumbai), Europe (London), and Europe (Stockholm) AWS Areas. Test the full Area listing for future updates. To study extra, try the DeepSeek in Amazon Bedrock product web page and the Amazon Bedrock pricing web page.
Give the DeepSeek-V3.1 mannequin a strive within the Amazon Bedrock console immediately and ship suggestions to AWS re:Publish for Amazon Bedrock or via your normal AWS Help contacts.
— Channy
Up to date on September 19, 2025 — Eliminated the mannequin entry part. Amazon Bedrock will simplify entry to all serverless basis fashions, and any new fashions, by mechanically enabling them for each AWS account, eliminating the necessity to manually activate entry via the Bedrock console. The mannequin entry web page might be retired in October 8, 2025 Account directors retain full management over mannequin entry via AWS IAM insurance policies and Service Management Insurance policies (SCPs) to limit mannequin entry as wanted.
