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In March, Amazon Internet Companies (AWS) grew to become the first cloud service supplier to ship DeepSeek-R1 in a serverless approach by launching it as a completely managed, typically accessible mannequin in Amazon Bedrock. Since then, clients have used DeepSeek-R1’s capabilities via Amazon Bedrock to construct generative AI functions, benefiting from the Bedrock’s sturdy guardrails and complete tooling for secure AI deployment.
At the moment, I’m excited to announce DeepSeek-V3.1 is now accessible as a completely 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.
In response to 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 features 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 device 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’ll be able to construct world functions to ship enhanced accuracy and decreased 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 technology – DeepSeek-V3.1 excels in coding duties with enhancements in software program engineering benchmarks and code agent capabilities, making it splendid 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 device calling via post-training optimization, making it robust in device utilization and agentic workflows. It helps structured device 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 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 world enterprise functions.
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, examine for bias in output, and monitor your outcomes when it comes to knowledge safety, accountable AI, and mannequin analysis.
You’ll be able to 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 examine 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 beneath 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 resolution.
Define the high-level structure for a scalable URL shortener service like bit.ly. Talk about key parts like API design, database selection (SQL vs. NoSQL), how the redirect mechanism works, and the way you'll generate distinctive quick codes.
You’ll be able to 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’ll be able to 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. Examine the full Area record 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 this time and ship suggestions to AWS re:Publish for Amazon Bedrock or via 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 via the Bedrock console. The mannequin entry web page will probably 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.
