|
In March, Amazon Internet Providers (AWS) turned the first cloud service supplier to ship DeepSeek-R1 in a serverless method by launching it as a completely managed, typically accessible mannequin in Amazon Bedrock. Since then, clients have used DeepSeek-R1’s capabilities by way of Amazon Bedrock to construct generative AI functions, benefiting from the Bedrock’s strong guardrails and complete tooling for secure AI deployment.
At present, 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 considering 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 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 factors 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 device utilization and agent duties has considerably improved by way of 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 functions to ship enhanced accuracy and diminished hallucinations in comparison with earlier DeepSeek fashions, whereas sustaining visibility into its decision-making course of.
Listed below 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 splendid for automated code era, 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 device calling by way of post-training optimization, making it sturdy in device utilization and agentic workflows. It helps structured device calling, code brokers, and search brokers, positioning it as a strong alternative for constructing autonomous AI techniques.
- Enterprise functions – DeepSeek fashions are built-in into numerous chat platforms and productiveness instruments, enhancing person 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 publish, when implementing publicly accessible 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 may entry the enterprise-grade security measures of Amazon Bedrock and implement safeguards personalized to your software necessities and accountable AI insurance policies with Amazon Bedrock Guardrails. It’s also possible to consider and evaluate fashions to determine the optimum mannequin in your use instances 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 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 choice.
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 considering on and off by toggling Mannequin reasoning mode to generate a response’s chain of thought previous to the ultimate conclusion.
It’s also possible to 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 instances and a wide range of programming languages.
To be taught 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 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 attempt within the Amazon Bedrock console immediately and ship suggestions to AWS re:Put up for Amazon Bedrock or by way of your ordinary 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 robotically enabling them for each AWS account, eliminating the necessity to manually activate entry by way of the Bedrock console. The mannequin entry web page will probably be retired in October 8, 2025 Account directors retain full management over mannequin entry by way of AWS IAM insurance policies and Service Management Insurance policies (SCPs) to limit mannequin entry as wanted.