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In March, Amazon Internet Providers (AWS) turned the first cloud service supplier to ship DeepSeek-R1 in a serverless manner by launching it as a totally managed, usually out there mannequin in Amazon Bedrock. Since then, clients have used DeepSeek-R1’s capabilities by Amazon Bedrock to construct generative AI purposes, benefiting from the Bedrock’s sturdy guardrails and complete tooling for protected AI deployment.
At the moment, I’m excited to announce DeepSeek-V3.1 is now out there 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 quicker responses.
Based on DeepSeek, the pondering mode of DeepSeek-V3.1 achieves comparable reply high quality with higher outcomes, stronger multi-step reasoning for advanced search duties, and massive positive factors 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 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 may construct world purposes 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 excellent for automated code technology, debugging, and software program engineering workflows. It performs properly on coding benchmarks whereas delivering high-quality outcomes effectively.
- Agentic AI instruments – The mannequin options enhanced software calling by 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 alternative for constructing autonomous AI techniques.
- Enterprise purposes – 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 purposes.
As I discussed in my earlier put up, when implementing publicly out there fashions, give cautious consideration to information privateness necessities when implementing in your manufacturing environments, examine for bias in output, and monitor your outcomes by way of information safety, accountable AI, and mannequin analysis.
You may 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 can even consider and evaluate fashions to determine the optimum mannequin in 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 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 determination.
Define the high-level structure for a scalable URL shortener service like bit.ly. Talk about key elements like API design, database alternative (SQL vs. NoSQL), how the redirect mechanism works, and the way you'll generate distinctive brief codes.
You may 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 can even entry the mannequin utilizing the AWS Command Line Interface (AWS CLI) and AWS SDK. This mannequin helps each the InvokeModel and Converse API. You may take a look at a broad vary of code examples for a number of use circumstances and a wide range of programming languages.
To be taught extra, go to DeepSeek mannequin inference parameters and responses within the AWS documentation.
Now out there
DeepSeek-V3.1 is now out there 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 be taught 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 strive within the Amazon Bedrock console at this time and ship suggestions to AWS re:Submit for Amazon Bedrock or by your standard AWS Assist 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 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.