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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 accessible mannequin in Amazon Bedrock. Since then, prospects have used DeepSeek-R1’s capabilities by Amazon Bedrock to construct generative AI purposes, benefiting from the Bedrock’s strong guardrails and complete tooling for protected AI deployment.
Right this moment, I’m excited to announce DeepSeek-V3.1 is now accessible as a totally managed basis mannequin in Amazon Bedrock. DeepSeek-V3.1 is a hybrid open weight mannequin that switches between considering mode (chain-of-thought reasoning) for detailed step-by-step evaluation and non-thinking mode (direct solutions) for sooner responses.
In response to DeepSeek, the considering mode of DeepSeek-V3.1 achieves comparable reply high quality with higher outcomes, stronger multi-step reasoning for complicated search duties, and large positive aspects in considering 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 instrument utilization and agent duties has considerably improved by 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 international purposes to ship enhanced accuracy and diminished hallucinations in comparison with earlier DeepSeek fashions, whereas sustaining visibility into its decision-making course of.
Listed here are your key use instances utilizing this mannequin:
- Code era – DeepSeek-V3.1 excels in coding duties with enhancements in software program engineering benchmarks and code agent capabilities, making it best for automated code era, debugging, and software program engineering workflows. It performs nicely on coding benchmarks whereas delivering high-quality outcomes effectively.
- Agentic AI instruments – The mannequin options enhanced instrument calling by post-training optimization, making it sturdy in instrument utilization and agentic workflows. It helps structured instrument calling, code brokers, and search brokers, positioning it as a strong selection for constructing autonomous AI programs.
- Enterprise purposes – DeepSeek fashions are built-in into numerous 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 international enterprise purposes.
As I discussed in my earlier put up, when implementing publicly accessible fashions, give cautious consideration to knowledge privateness necessities when implementing in your manufacturing environments, verify for bias in output, and monitor your outcomes by way of knowledge safety, accountable AI, and mannequin analysis.
You possibly can entry the enterprise-grade security measures of Amazon Bedrock and implement safeguards custom-made to your software necessities and accountable AI insurance policies with Amazon Bedrock Guardrails. You may as well consider and evaluate fashions to determine the optimum mannequin on your use instances through the use of 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 below 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 quick codes.
You possibly can flip the considering on and off by toggling Mannequin reasoning mode to generate a response’s chain of thought previous to the ultimate conclusion.
You may as well 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 take a look at a broad vary of code examples for a number of use instances and quite a lot of programming languages.
To study extra, go to DeepSeek mannequin inference parameters and responses within the AWS documentation.
Now accessible
DeepSeek-V3.1 is now accessible within the US West (Oregon), Asia Pacific (Tokyo), Asia Pacific (Mumbai), Europe (London), and Europe (Stockholm) AWS Areas. Verify the full Area listing for future updates. To study extra, take a look at the DeepSeek in Amazon Bedrock product web page and the Amazon Bedrock pricing web page.
Give the DeepSeek-V3.1 mannequin a attempt within the Amazon Bedrock console at present and ship suggestions to AWS re:Put up for Amazon Bedrock or by your common 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 routinely enabling them for each AWS account, eliminating the necessity to manually activate entry by the Bedrock console. The mannequin entry web page will likely be retired in October 8, 2025 Account directors retain full management over mannequin entry by AWS IAM insurance policies and Service Management Insurance policies (SCPs) to limit mannequin entry as wanted.