{"id":14582,"date":"2026-11-08T20:31:03","date_gmt":"2026-11-08T18:31:03","guid":{"rendered":"https:\/\/heshamsaad.com\/?p=14582"},"modified":"2026-11-08T20:31:03","modified_gmt":"2026-11-08T18:31:03","slug":"kimi-k3-1-pro-amazon-bedrock","status":"publish","type":"post","link":"https:\/\/heshamsaad.com\/en\/kimi-k3-1-pro-amazon-bedrock\/","title":{"rendered":"Kimi K3.1 Pro on Amazon Bedrock: Highspeed Access, Pricing, Regions and WordPress Limits"},"content":{"rendered":"\n<aside class=\"wp-block-hesham-saad-key-takeaways hs-key-takeaways\">\n<h3 class=\"wp-block-heading hs-key-takeaways__title\">Key takeaways<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>AWS added the Kimi K3.1 Pro Highspeed variant from Moonshot AI to Amazon Bedrock with text and image input support, text output, and a 1-million-token context window.<\/li>\n\n\n\n<li>In-Region inference is not available in any AWS Region, and callers in the UAE or Bahrain Regions must use the Global cross-Region inference profile, which can route data worldwide.<\/li>\n\n\n\n<li>AWS recommends the OpenAI-compatible Chat Completions API on bedrock-runtime and lists Converse limitations for this model: multi-turn requests that include reasoning from earlier turns fail, attached PDF and HTML documents are rejected, and explicit prompt caching is not supported.<\/li>\n\n\n\n<li>Reasoning is enabled by default at the maximum effort level, and every output token consumes ten tokens of account quota on bedrock-runtime.<\/li>\n<\/ul>\n<\/aside>\n\n\n\n<p class=\"wp-block-paragraph\">Running <strong>Kimi K3.1 Pro on Amazon Bedrock<\/strong> gives engineering teams and business owners a managed AWS route to Moonshot AI&#8217;s high-throughput open-weight model without setting up dedicated GPU clusters. AWS announced the availability of Kimi K3.1 Pro (Highspeed) on November 6, 2026, while the Amazon Bedrock User Guide model card lists the official model launch date as November 4, 2026. Instead of opening a separate billing account with a model provider, companies that already run workloads on AWS can call this variant through existing IAM policies, Guardrails, and runtime endpoints.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Before wiring this model into a production application or a WordPress backend, decision-makers in the Middle East and North Africa need to look closely at the technical documentation. The Bedrock deployment has specific rules around cross-Region inference, Middle East data routing, API compatibility, reasoning defaults, and output quota consumption that directly affect both compliance and monthly cloud bills.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What AWS launched with Kimi K3.1 Pro on Amazon Bedrock<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The November 2026 announcement is a cloud availability launch rather than a new base model release. Specifically, AWS introduced the Kimi K3.1 Pro (Highspeed) variant into the managed Bedrock catalog under the active lifecycle state. According to the Bedrock User Guide model card, the end-of-life date is not applicable, and AWS commits to providing at least 45 days of advance notice before any future deprecation. The model card also notes under its licensing terms that accessing the model through Amazon Bedrock counts as access through Certified Inference Partners.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In its release announcement, AWS positioned the deployment of <strong>Kimi K3.1 Pro on Amazon Bedrock<\/strong> as an expansion of its open-weight model portfolio that keeps workloads inside the same security and governance boundary that customers rely on for proprietary models. AWS highlights agentic tasks such as software coding and document processing as primary workloads for this variant. According to AWS, the Highspeed version delivers high output tokens per second (OTPS) for faster, more responsive interactions and supports explicit prompt caching to lower latency and repeated input costs, although AWS does not publish a specific numerical OTPS figure.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">A short recap of the Kimi K3.1 Pro model<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">We recently published a complete breakdown of <a href=\"https:\/\/heshamsaad.com\/en\/kimi-k3-1-pro\/\">Kimi K3.1 Pro<\/a> covering its open-weight architecture, direct platform tiers, and core capabilities, so we will keep the base model summary brief here. According to Moonshot AI, Kimi K3.1 Pro is the first release in the K3.1 series and represents its most capable 3-trillion-parameter-class open-weight model to date. Moonshot describes it as a natively multimodal agentic model with a 1-million-token context window, citing gains in coding, 3D creation, financial research, and multi-step agentic workflows, including a vendor-reported score of 65.7 percent on Terminal-Bench 4.0 when tested with the Claude-Code harness.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">On Moonshot&#8217;s own platform documentation, the company offers two distinct API variants: the standard <code>kimi-k3.1-pro<\/code> model and <code>kimi-k3.1-pro-highspeed<\/code>. According to Moonshot AI, the Highspeed variant delivers the same intelligence at roughly two to three times the generation speed of standard K3.1 Pro. On Amazon Bedrock, customers receive this Highspeed variant with a 1-million-token context window, supporting text and image inputs and generating text outputs only. Audio, speech, and video inputs are not supported on Bedrock.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Model IDs and cross-Region inference profiles<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">How you address the model in your AWS code determines where your prompts travel and what you pay per token. The base model identifier in the Bedrock catalog is <code>moonshotai.kimi-k3.1<\/code>. However, the regional availability table in the AWS Bedrock User Guide shows that single-Region (In-Region) inference is not available in any AWS Region for this model. You cannot lock inference to a single data center location; every API call must use cross-Region inference (CRIS) through an inference profile ID.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">AWS provides three system-defined inference profile IDs for routing requests across its infrastructure:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Global profile (<code>global.moonshotai.kimi-k3.1<\/code>):<\/strong> Available as a source across all 32 supported commercial Regions listed on the model card, routing inference requests to any supported commercial AWS Region worldwide.<\/li>\n\n<li><strong>US Geo profile (<code>us.moonshotai.kimi-k3.1<\/code>):<\/strong> Available when calling from US Regions (<code>us-east-1<\/code>, <code>us-east-2<\/code>, <code>us-west-1<\/code>, <code>us-west-2<\/code>) and Canadian Regions (<code>ca-central-1<\/code>, <code>ca-west-1<\/code>), where Canadian source requests route across Canada and US Regions.<\/li>\n\n<li><strong>India Geo profile (<code>in.moonshotai.kimi-k3.1<\/code>):<\/strong> Available when calling from <code>ap-south-1<\/code> (Mumbai) and <code>ap-south-2<\/code> (Hyderabad), keeping cross-Region routing strictly between those two Indian Regions.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Amazon Bedrock also supports application inference profiles for this model, allowing engineering teams to wrap the system profiles in custom ARNs to track token consumption and tag costs by department, client, or environment.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What the regional routing table means for MENA businesses<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">For companies operating in the United Arab Emirates, Saudi Arabia, Egypt, Bahrain, or Qatar, the Bedrock regional routing table contains a critical compliance detail. Both the UAE Region (<code>me-central-1<\/code>) and the Bahrain Region (<code>me-south-1<\/code>) are listed among the 32 source Regions on <code>bedrock-runtime<\/code>, alongside <code>il-central-1<\/code>, <code>af-south-1<\/code>, European Regions, Asia Pacific Regions, and <code>sa-east-1<\/code>. That means an application hosted on EC2, ECS, or Lambda in Dubai or Manama can call the model directly without changing its local AWS SDK Region setting.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">However, there is no Middle East Geo inference profile and no European Union Geo inference profile for Kimi K3.1 Pro Highspeed. Because In-Region inference is not offered anywhere, requests originating from <code>me-central-1<\/code> or <code>me-south-1<\/code> can only use the <code>global.moonshotai.kimi-k3.1<\/code> profile. When you invoke the Global profile from the UAE or Bahrain, Amazon Bedrock can route your prompts and completions to any supported commercial AWS Region worldwide.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Stated plainly, there is no Middle East data residency option for this model on Amazon Bedrock. If your business operates under banking, healthcare, government, or enterprise procurement rules that forbid customer prompts or documents from leaving the GCC or a specific jurisdiction, you cannot use this model on Bedrock for those regulated data sets. On the other hand, if your workload processes public web content, software code, or non-sensitive catalog data where global routing is acceptable, calling the Global profile from UAE or Bahrain gives you the lower of this model&#8217;s two Standard tier rate sets on Bedrock.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Supported APIs, endpoints, and Converse limitations<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">At the endpoint level, Kimi K3.1 Pro Highspeed is supported on <code>bedrock-runtime<\/code>, while the <code>bedrock-mantle<\/code> endpoint is not supported. Within <code>bedrock-runtime<\/code>, AWS lists four supported API surfaces: <code>Responses<\/code>, <code>Chat Completions<\/code>, <code>Converse<\/code>, and <code>Invoke<\/code> (<code>InvokeModel<\/code>). If your developers are starting a new integration, AWS explicitly recommends using the OpenAI-compatible <code>Chat Completions<\/code> API (or the <code>Responses<\/code> API) rather than Bedrock&#8217;s native <code>Converse<\/code> API for this model.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">That recommendation comes down to several launch-specific limitations documented on the AWS model card for <code>Converse<\/code> and multimodal inputs:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Multi-turn reasoning failure on Converse:<\/strong> Including reasoning content from earlier conversation turns inside a multi-turn <code>Converse<\/code> request triggers an <code>InternalServerException<\/code>. AWS says this affects frameworks such as LangChain and Strands Agents in their default configurations, and that to use <code>Converse<\/code> for multi-turn requests you should remove reasoning blocks from prior turns.<\/li>\n\n<li><strong>Document attachments rejected on Converse:<\/strong> The <code>Converse<\/code> API rejects attached document inputs such as PDF and HTML files for this model.<\/li>\n\n<li><strong>No explicit prompt caching on Converse:<\/strong> Explicit prompt caching checkpoints work on <code>Responses<\/code>, <code>Chat Completions<\/code>, and <code>InvokeModel<\/code>, but are not supported on <code>Converse<\/code>.<\/li>\n\n<li><strong>Image ordering and detail controls:<\/strong> AWS notes that placing images before text in a prompt can produce better answers depending on the prompt structure, and the image detail parameter is only honored on <code>Chat Completions<\/code>, whereas <code>Responses<\/code> always processes images at high detail.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Bedrock features supported and not supported at launch<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Because Amazon Bedrock is a shared platform, buyers often assume every model in the catalog works with every managed Bedrock tool. In practice, you have to separate generic Bedrock platform marketing from what the specific model card enables. For Kimi K3.1 Pro Highspeed on <code>bedrock-runtime<\/code>, AWS supports response streaming, implicit prompt caching, explicit prompt caching (minimum 256 tokens per cache checkpoint with a time-to-live of at least 30 minutes), client-side tool calling, structured outputs, model invocation logs, Amazon Bedrock Guardrails, configurable reasoning effort, and application inference profiles.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Reasoning behavior deserves special attention before you push code to production. Reasoning is turned on by default for this model, and the default effort level is set to <code>max<\/code>. Developers can pass the configurable reasoning effort parameter using the values <code>none<\/code>, <code>low<\/code>, <code>medium<\/code>, <code>high<\/code>, <code>xhigh<\/code>, or <code>max<\/code>, where <code>none<\/code> disables reasoning completely; the <code>minimal<\/code> value is not supported. AWS documents the effort setting as <code>reasoning.effort<\/code> on Responses and <code>reasoning_effort<\/code> on Chat Completions and InvokeModel; Converse accepts <code>reasoning_effort<\/code> in <code>additionalModelRequestFields<\/code> but does not validate it for this model. Leaving the setting at its default <code>max<\/code> value means the model may spend more reasoning tokens than a straightforward prompt needs, and those tokens are billed as output.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Just as important are the Bedrock platform features that are not supported for this model: Amazon Bedrock Knowledge Bases, intelligent prompt routing, the count tokens API, and watermarking. Because Bedrock Knowledge Bases are not supported, you cannot select Kimi K3.1 Pro Highspeed as the generator inside a managed Bedrock RAG workflow out of the box. Teams that need retrieval over company documents must either build their own retrieval logic using client-side tool calling and custom vector search or use a different Bedrock model for managed Knowledge Base queries.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Verified Bedrock pricing, caching savings, and quota burndown<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Both the Amazon Bedrock pricing page and the User Guide model card list identical token rates for Kimi K3.1 Pro Highspeed. Pricing depends on whether you route through the Global cross-Region inference profile or one of the two geographic profiles (US or India), as well as the service tier you select. On the Standard tier, verified prices per 1 million tokens are:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Global CRIS (<code>global.moonshotai.kimi-k3.1<\/code>):<\/strong> 4.00 USD for input tokens, 20.00 USD for output tokens, 0.20 USD for cache read tokens, and 5.00 USD for 30-minute cache write tokens.<\/li>\n\n<li><strong>US CRIS (<code>us.moonshotai.kimi-k3.1<\/code>) and India CRIS (<code>in.moonshotai.kimi-k3.1<\/code>):<\/strong> 4.40 USD for input tokens, 22.00 USD for output tokens, 0.22 USD for cache read tokens, and 5.50 USD for 30-minute cache write tokens.<\/li>\n\n<li><strong>Additional service tiers:<\/strong> Priority tier is billed at 1.75 times the Standard tier rate, Flex tier is billed at 0.5 times the Standard tier rate, and a Reserved tier is also listed among the model card tiers.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Three practical cost mechanics stand out from these numbers. First, output tokens cost five times as much as uncached input tokens (20.00 USD versus 4.00 USD per million on Global). Because reasoning defaults to <code>max<\/code>, an unoptimized integration will generate long reasoning chains billed at the output rate unless developers dial the effort down to <code>low<\/code>, <code>medium<\/code>, or <code>none<\/code> for routine tasks. Second, prompt caching reduces input read costs by 95 percent compared to standard input (0.20 USD versus 4.00 USD on Global), making explicit cache checkpoints well worth implementing when sending large system instructions or codebase context repeatedly within a 30-minute window.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Third, the model card specifies a 10x output token quota burndown rate on <code>bedrock-runtime<\/code>. Every single output token generated by the model consumes 10 tokens from your AWS account token quota. Even if your monthly budget easily covers the dollar cost, high-volume agentic tasks or verbose <code>max<\/code> reasoning runs will hit account throttling limits ten times faster on output than on input.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">How Bedrock compares with Kimi K3, Microsoft Foundry, and the Kimi API<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">When deciding where to host or call Moonshot&#8217;s models, it helps to compare verified official numbers across the same catalog and competing clouds. Within the Amazon Bedrock pricing page itself, the earlier Kimi K3 model is listed at 3.00 USD per 1 million input tokens, 15.00 USD for output, 0.30 USD for cache read, and 3.75 USD for cache write on Global CRIS (and 3.30 USD input, 16.50 USD output, 0.33 USD cache read, and 4.125 USD cache write on US CRIS). Moving up to Kimi K3.1 Pro Highspeed increases standard input, output, and cache write prices by roughly a third, although the Global cache read price drops from 0.30 USD on Kimi K3 to 0.20 USD on K3.1 Pro Highspeed.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Outside AWS, Microsoft announced on November 5, 2026 that Kimi K3.1 Pro is available in the Microsoft Foundry model catalog with text and image understanding and a 1-million-token context window. Microsoft&#8217;s published price table lists 2.30 USD per 1 million input tokens, 0.23 USD for cached input, and 11.50 USD for output. However, Microsoft&#8217;s announcement refers to the standard Kimi K3.1 Pro model and does not mention the Highspeed variant, so those lower per-token figures are not a like-for-like comparison with Bedrock&#8217;s Highspeed deployment. As Microsoft advises in its own post, engineering teams should test on representative tasks and evaluate cost per successful task.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Teams can also call Moonshot&#8217;s direct platform through the Kimi API (which offers both <code>kimi-k3.1-pro<\/code> and <code>kimi-k3.1-pro-highspeed<\/code>, alongside Kimi.ai, Kimi Work, and Kimi Code), where Moonshot states that Zero Data Retention (ZDR) is available for API customers. Choosing between direct vendor APIs and hyperscale clouds is a recurring architectural decision; whether you are comparing Bedrock models such as <a href=\"https:\/\/heshamsaad.com\/en\/gpt-6-1-terra\/\">GPT-6.1 Terra<\/a> or weighing multi-cloud catalogs like <a href=\"https:\/\/heshamsaad.com\/en\/openai-models-google-cloud\/\">OpenAI models on Google Cloud<\/a>, the right pick depends on where your application data already lives and how your team manages IAM and billing.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">What AWS and Moonshot have not published<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">When budgeting for a production integration, knowing what is missing from the official documentation is just as useful as reading the feature list. Based on the AWS announcement, the Bedrock User Guide model card, the Bedrock pricing page, and Moonshot&#8217;s documentation, several details remain unpublished or unsupported:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>No measured Bedrock speed numbers:<\/strong> AWS states that the Highspeed variant delivers high output tokens per second, and Moonshot claims two to three times the speed of standard K3.1 Pro on its own platform, but neither company has published measured OTPS, time-to-first-token latency, or throughput benchmarks specifically on Amazon Bedrock.<\/li>\n\n<li><strong>No Middle East, EU, or In-Region data residency:<\/strong> Neither In-Region inference nor dedicated Middle East or EU Geo profiles are offered in the regional table.<\/li>\n\n<li><strong>No Batch inference or Provisioned Throughput listings:<\/strong> Neither batch inference pricing nor Provisioned Throughput commitment units are listed on the model card for this model.<\/li>\n\n<li><strong>No Knowledge Bases or official WordPress plugin:<\/strong> Bedrock Knowledge Bases are explicitly listed as not supported, and neither AWS nor Moonshot provides an official WordPress plugin.<\/li>\n\n<li><strong>No published Arabic benchmarks or public default quota figures:<\/strong> Neither vendor has published formal evaluations of Arabic language quality for this model, and exact default token rate limits are not listed on the public card because they are assigned per account inside AWS Service Quotas.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Practical WordPress workflows and when to hire a developer<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">From our perspective building and maintaining custom sites for MENA companies, Kimi K3.1 Pro Highspeed on Amazon Bedrock is best suited for businesses that already use AWS and want a fast, long-context model connected to their back-office workflows. Because there is no official WordPress plugin, a developer has to connect the model through a secure custom plugin, a Laravel or Node middleware service, or an AWS Lambda function that calls the <code>Chat Completions<\/code> API on <code>bedrock-runtime<\/code>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In our view, four practical WordPress and WooCommerce workflows make sense when engineered properly:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Editorial drafting with human review:<\/strong> Generating structured article drafts, bilingual outlines, or SEO metadata inside a private editorial workflow, where staff editors review and verify every paragraph before publishing.<\/li>\n\n<li><strong>Customer support and order triage summaries:<\/strong> Summarizing long customer inquiry threads or WooCommerce order notes for support agents, using lower reasoning effort settings (<code>low<\/code> or <code>medium<\/code>) to keep output costs predictable.<\/li>\n\n<li><strong>WooCommerce catalog and visual document processing:<\/strong> Sending supplier product photos (placed before text prompts on <code>Chat Completions<\/code>) alongside messy specification sheets to return validated JSON attributes using structured outputs, while caching the shared category schema to pay the 0.20 USD cache read rate.<\/li>\n\n<li><strong>Theme and plugin engineering assistance:<\/strong> Using the 1-million-token context window in staging tools to review custom PHP plugins, write automated tests, and inspect Gutenberg block code.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Every one of these workflows requires strict engineering guardrails. AWS access keys and IAM roles must stay entirely on the server and never be exposed in browser JavaScript, reasoning effort should be tuned per endpoint so the 20.00 USD output rate and 10x quota burndown do not cause surprise bills or throttling, and sensitive MENA customer records must be filtered out if your compliance policy forbids Global cross-Region routing. If you want to connect Amazon Bedrock safely to your store or editorial backend, explore our <a href=\"https:\/\/heshamsaad.com\/en\/wordpress-development\/\">WordPress development services<\/a> or book a <a href=\"https:\/\/heshamsaad.com\/en\/free-consultation\/\">free consultation<\/a> so we can review your architecture and build the right integration for your business.<\/p>\n\n\n<h2 class=\"wp-block-heading\">Frequently asked questions<\/h2>\n\n\n\n<div class=\"wp-block-wpseopress-faq-block-v2 is-layout-flow wp-block-wpseopress-faq-block-v2-is-layout-flow\">\n<details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\" id=\"faq-what\"><summary>What version of Kimi K3.1 Pro did AWS launch on Amazon Bedrock?<\/summary>\n<p class=\"wp-block-paragraph\">AWS added the Kimi K3.1 Pro Highspeed variant from Moonshot AI to Amazon Bedrock under the model ID moonshotai.kimi-k3.1. This version supports text and image inputs with text outputs across a 1-million-token context window. It does not support audio, speech, or video inputs on Bedrock, and it runs through the bedrock-runtime endpoint inside the standard Bedrock security boundary.<\/p>\n<\/details>\n\n<details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\" id=\"faq-access\"><summary>Which API should developers use to call Kimi K3.1 Pro on Amazon Bedrock?<\/summary>\n<p class=\"wp-block-paragraph\">AWS recommends using the OpenAI-compatible Chat Completions API or the Responses API on the bedrock-runtime endpoint. While the Converse API is supported, it has known limitations with this model, including an InternalServerException on multi-turn requests that contain earlier reasoning content and a rejection of attached PDF or HTML documents. Explicit prompt caching is also unavailable when calling Converse.<\/p>\n<\/details>\n\n<details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\" id=\"faq-price\"><summary>How much does Kimi K3.1 Pro Highspeed cost on Amazon Bedrock?<\/summary>\n<p class=\"wp-block-paragraph\">On the Standard tier with Global cross-Region inference, Kimi K3.1 Pro Highspeed costs 4.00 USD per 1 million input tokens, 20.00 USD for output, 0.20 USD for cache reads, and 5.00 USD for 30-minute cache writes. US and India Geo profiles cost 4.40 USD for input and 22.00 USD for output. Output tokens also consume account quota at a 10x burndown rate.<\/p>\n<\/details>\n\n<details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\" id=\"faq-mena\"><summary>Does Kimi K3.1 Pro on Amazon Bedrock offer Middle East data residency?<\/summary>\n<p class=\"wp-block-paragraph\">No, Amazon Bedrock does not offer In-Region inference or a Middle East Geo inference profile for Kimi K3.1 Pro Highspeed. Workloads running in the UAE Region me-central-1 or the Bahrain Region me-south-1 must use the global.moonshotai.kimi-k3.1 inference profile. That Global profile can route prompts and completions to any supported commercial AWS Region worldwide, so it does not guarantee local data residency.<\/p>\n<\/details>\n\n<details class=\"wp-block-details is-layout-flow wp-block-details-is-layout-flow\" id=\"faq-wordpress\"><summary>Can I connect Kimi K3.1 Pro on Amazon Bedrock directly to a WordPress site?<\/summary>\n<p class=\"wp-block-paragraph\">There is no official AWS or Moonshot WordPress plugin for Kimi K3.1 Pro Highspeed, so you cannot install it from the plugin directory. A developer must connect your WordPress or WooCommerce site through a custom server-side integration or middleware that calls the Bedrock runtime API. All AWS credentials and IAM permissions must stay on the server and never be exposed in browser code.<\/p>\n<\/details>\n<\/div>\n<script type=\"application\/ld+json\">{\"@context\":\"https:\/\/schema.org\",\"@type\":\"FAQPage\",\"url\":\"https:\/\/heshamsaad.com\/en\/kimi-k3-1-pro-amazon-bedrock\/\",\"@id\":\"https:\/\/heshamsaad.com\/en\/kimi-k3-1-pro-amazon-bedrock\/\",\"mainEntity\":[{\"@type\":\"Question\",\"url\":\"https:\/\/heshamsaad.com\/en\/kimi-k3-1-pro-amazon-bedrock\/#faq-what\",\"name\":\"What version of Kimi K3.1 Pro did AWS launch on Amazon Bedrock?\",\"answerCount\":1,\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"\\u003Cp\\u003EAWS added the Kimi K3.1 Pro Highspeed variant from Moonshot AI to Amazon Bedrock under the model ID moonshotai.kimi-k3.1. This version supports text and image inputs with text outputs across a 1-million-token context window. It does not support audio, speech, or video inputs on Bedrock, and it runs through the bedrock-runtime endpoint inside the standard Bedrock security boundary.\\u003C\/p\\u003E\"}},{\"@type\":\"Question\",\"url\":\"https:\/\/heshamsaad.com\/en\/kimi-k3-1-pro-amazon-bedrock\/#faq-access\",\"name\":\"Which API should developers use to call Kimi K3.1 Pro on Amazon Bedrock?\",\"answerCount\":1,\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"\\u003Cp\\u003EAWS recommends using the OpenAI-compatible Chat Completions API or the Responses API on the bedrock-runtime endpoint. While the Converse API is supported, it has known limitations with this model, including an InternalServerException on multi-turn requests that contain earlier reasoning content and a rejection of attached PDF or HTML documents. Explicit prompt caching is also unavailable when calling Converse.\\u003C\/p\\u003E\"}},{\"@type\":\"Question\",\"url\":\"https:\/\/heshamsaad.com\/en\/kimi-k3-1-pro-amazon-bedrock\/#faq-price\",\"name\":\"How much does Kimi K3.1 Pro Highspeed cost on Amazon Bedrock?\",\"answerCount\":1,\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"\\u003Cp\\u003EOn the Standard tier with Global cross-Region inference, Kimi K3.1 Pro Highspeed costs 4.00 USD per 1 million input tokens, 20.00 USD for output, 0.20 USD for cache reads, and 5.00 USD for 30-minute cache writes. US and India Geo profiles cost 4.40 USD for input and 22.00 USD for output. Output tokens also consume account quota at a 10x burndown rate.\\u003C\/p\\u003E\"}},{\"@type\":\"Question\",\"url\":\"https:\/\/heshamsaad.com\/en\/kimi-k3-1-pro-amazon-bedrock\/#faq-mena\",\"name\":\"Does Kimi K3.1 Pro on Amazon Bedrock offer Middle East data residency?\",\"answerCount\":1,\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"\\u003Cp\\u003ENo, Amazon Bedrock does not offer In-Region inference or a Middle East Geo inference profile for Kimi K3.1 Pro Highspeed. Workloads running in the UAE Region me-central-1 or the Bahrain Region me-south-1 must use the global.moonshotai.kimi-k3.1 inference profile. That Global profile can route prompts and completions to any supported commercial AWS Region worldwide, so it does not guarantee local data residency.\\u003C\/p\\u003E\"}},{\"@type\":\"Question\",\"url\":\"https:\/\/heshamsaad.com\/en\/kimi-k3-1-pro-amazon-bedrock\/#faq-wordpress\",\"name\":\"Can I connect Kimi K3.1 Pro on Amazon Bedrock directly to a WordPress site?\",\"answerCount\":1,\"acceptedAnswer\":{\"@type\":\"Answer\",\"text\":\"\\u003Cp\\u003EThere is no official AWS or Moonshot WordPress plugin for Kimi K3.1 Pro Highspeed, so you cannot install it from the plugin directory. A developer must connect your WordPress or WooCommerce site through a custom server-side integration or middleware that calls the Bedrock runtime API. All AWS credentials and IAM permissions must stay on the server and never be exposed in browser code.\\u003C\/p\\u003E\"}}]}<\/script>\n\n\n<h2 class=\"wp-block-heading\">References<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/aws.amazon.com\/about-aws\/whats-new\/2026\/11\/moonshot-ai-kimi-k3-1-pro-on-amazon-bedrock\" rel=\"noopener\" target=\"_blank\">AWS What&#8217;s New: Kimi K3.1 Pro (Highspeed) now available on Amazon Bedrock<\/a><\/li>\n\n<li><a href=\"https:\/\/docs.aws.amazon.com\/bedrock\/latest\/userguide\/model-card-moonshot-ai-kimi-k3-1-highspeed.html\" rel=\"noopener\" target=\"_blank\">Amazon Bedrock User Guide: Kimi K3.1 Pro Highspeed model card<\/a><\/li>\n\n<li><a href=\"https:\/\/aws.amazon.com\/bedrock\/pricing\/\" rel=\"noopener\" target=\"_blank\">Amazon Bedrock Pricing<\/a><\/li>\n\n<li><a href=\"https:\/\/www.kimi.ai\/blog\/kimi-k3-1-pro\" rel=\"noopener\" target=\"_blank\">Moonshot AI Blog: Introducing Kimi K3.1 Pro<\/a><\/li>\n\n<li><a href=\"https:\/\/platform.kimi.ai\/docs\/models\" rel=\"noopener\" target=\"_blank\">Moonshot AI Platform Documentation: Models<\/a><\/li>\n\n<li><a href=\"https:\/\/techcommunity.microsoft.com\/blog\/azure-ai-foundry-blog\/moonshot-ai%E2%80%99s-kimi-k3-1-pro-comes-to-microsoft-foundry\/4570292\" rel=\"noopener\" target=\"_blank\">Microsoft Foundry Blog: Moonshot AI&#8217;s Kimi K3.1 Pro comes to Microsoft Foundry<\/a><\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>AWS made Kimi K3.1 Pro (Highspeed) available on Amazon Bedrock on November 6, 2026. Model IDs, cross-Region inference, what it means for UAE and Bahrain, API limits, verified token pricing, rivals and WordPress use.<\/p>\n","protected":false},"author":1611,"featured_media":14584,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"iawp_total_views":2,"footnotes":""},"categories":[569],"tags":[604],"class_list":["post-14582","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-news","tag-ai-news"],"acf":[],"_links":{"self":[{"href":"https:\/\/heshamsaad.com\/en\/wp-json\/wp\/v2\/posts\/14582","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/heshamsaad.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/heshamsaad.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/heshamsaad.com\/en\/wp-json\/wp\/v2\/users\/1611"}],"replies":[{"embeddable":true,"href":"https:\/\/heshamsaad.com\/en\/wp-json\/wp\/v2\/comments?post=14582"}],"version-history":[{"count":0,"href":"https:\/\/heshamsaad.com\/en\/wp-json\/wp\/v2\/posts\/14582\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/heshamsaad.com\/en\/wp-json\/wp\/v2\/media\/14584"}],"wp:attachment":[{"href":"https:\/\/heshamsaad.com\/en\/wp-json\/wp\/v2\/media?parent=14582"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/heshamsaad.com\/en\/wp-json\/wp\/v2\/categories?post=14582"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/heshamsaad.com\/en\/wp-json\/wp\/v2\/tags?post=14582"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}