agentspeed.

baseten.co

scanned 7/25/2026, 10:41:08 PM · cached · refresh in 22h · rubric 2026.07.4
Built with Next.js
robots.txt present: passrobots.txt allows AI agents: passContent-Signal directives: failllms.txt present: passSitemap present: passLink response headers: failCanonical URL: passMCP server card: failOAuth authorization metadata: failOAuth resource metadata: failAPI catalog / OpenAPI: failWeb Bot Auth: failMarkdown negotiation: failText-to-markup ratio: failContent without JavaScript: skipHeading hierarchy: warnCookie wall blocks content: passPage title: passMeta description: passJSON-LD present: failStructured data validates: skipSchema type coverage: passPaywall / login wall: passAgent Skills manifest: failWebMCP actions: failPrimary action reachable: passReachability: passTime to first byte: warnFull render time: skipPage weight: pass66/ 100 · D
Needs work

This is how AI agents (not browsers) experience baseten.co. The score weights five categories of machine-readability; the ticks on the arc are the 30 individual checks behind it.

✉ Email me this report + alert me when it changes ↓

Top fixes

Checks tagged “emerging” are 2026 agent-protocol standards most of the web hasn’t adopted yet — adopting early is an edge, not a defect.

failJSON-LD presentStructured data

No JSON-LD blocks found. Add a <script type="application/ld+json"> with a schema.org type for this page.

Fix · Next.js: Emit JSON-LD from a Server Component or the Metadata API: a <script type="application/ld+json"> with Organization / Article / Product for the page.

failLink response headersDiscoverability

No HTTP Link: response headers. Emit canonical/alternate/describedby relations so HEAD-only or stream-rendering agents get them without parsing HTML.

Fix: Emit `Link:` headers for canonical, alternate-language, and describedby relations. Agents that fetch HEAD-only or stream-render rely on these.

failText-to-markup ratioReadability

Visible text is 1.8% of HTML weight (8219/446449 bytes). Low. Markup may be crowding out agent-usable text.

Fix: Heavy ad or navigation markup crowds out agent-usable text. Aim for a text-to-DOM ratio above 15%.

warnTime to first bytePerformance

TTFB 948ms. Acceptable.

Fix: Agents time out aggressively. Use edge caching for anonymous requests to cut TTFB below 800ms.

warnHeading hierarchyReadability

Heading issues: 2 <h1> tags (expected 1).

Fix: Use a single H1 and avoid skipping heading levels (H1 → H3).

failContent-Signal directivesemergingDiscoverability

No Content-Signal directives. Add e.g. `Content-Signal: ai-train=no, ai-summarize=yes` to declare granular AI usage policy beyond binary allow/disallow.

Fix: Add `Content-Signal:` directives to your robots.txt. This is the emerging standard (Cloudflare-driven) for declaring fine-grained AI usage policy beyond a binary allow/disallow.

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Fix it

Generated, ready-to-ship files for the gaps above — copy them or download and drop them into your repo.

Add JSON-LD structured data
Paste inside <head>. Use Article/Product instead of Organization on those page types.
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Inference Platform: Deploy AI models in production | Baseten",
  "url": "https://baseten.co/",
  "description": "Serve and scale open-source and custom AI models on the fastest, most reliable inference platform."
}
</script>

What the agent receives

The agent’s-eye view
Inference Platform: Deploy AI models in production | Baseten GLM-5.2 Fast is now available. Learn more Products Solutions Resources Research Customers Pricing Models Docs Log in Get started Inference is everything The fastest model runtimes, cross-cloud high availability, and seamless developer workflows. Powered by the Baseten Inference Stack. Get started Talk to an engineer Abridge website Clay website Cursor website Decagon website descript website EliseAI case study Gamma case study Harvey website Hubspot website Lovable website Notion website OpenEvidence case study Parallel case study Poolside case study World Labs case study Products The platform for high-performance inference Dedicated inference for high-scale workloads Serve open-source, custom, and fine-tuned AI models on infra purpose-built for high-performance inference at massive scale. Start deploying Learn more Pre-optimized Model APIs Test new workloads, prototype products, or evaluate the latest AI models optimized to be the fastest in production — instantly. Learn more Kimi K2.6 Try It DeepSeek V4 Try It GLM-5.2 Try It Explore the model Library Explore Run Training on Baseten Train your models and easily deploy them in one click on inference-optimized infrastructure for the best possible performance. Learn more Frontier Gateway Deploy an inference API powered by Baseten to monetize your model faster. Learn more The fastest inference takes more than GPUs. Baseten delivers the infrastructure, tooling, and expertise needed to bring the most performant AI products to market—fast. Bleeding-edge performance research Run cutting-edge performance research with custom kernels, the latest decoding techniques, and advanced caching baked into the Baseten Inference Stack. Learn More Learn More Inference-optimized infrastructure Scale workloads across any region and any cloud (in our cloud or yours), with blazing-fast cold starts and 99.99% uptime out of the box. Learn More Learn More DevEx built for rapid iteration Deploy, optimize, and manage your models and compound AI with a delightful developer experience built into Baseten&#x27;s inference platform. Learn More Learn More Forward Deployed Engineers Partner with our forward deployed engineers to build, optimize, and scale your models with hands-on support from prototype to production. Learn More Learn More Scale fast — in our cloud or yours. Learn more Rapidly scale workloads across any cloud provider with global capacity. We offer single-tenant and self-hosted deployments for extra security. Learn more Baseten Cloud Get the fastest time to market with fully-managed, global deployment options and massive horizontal scale. Use single-tenant clusters for additional workload isolation. Learn more Get the fastest time to market with fully-managed, global deployment options and massive horizontal scale. Use single-tenant clusters for additional workload isolation. Learn more Self-hosted Get the low latency, high throughput, and dev experience you expect from a managed service, right in your own VPCs. Optionally, go hybrid with on-demand flex capacity on Baseten Cloud. Learn more Get the low latency, high throughput, and dev experience you expect from a managed service, right in your own VPCs. Optionally, go hybrid with on-demand flex capacity on Baseten Cloud. Learn more Engineered for the most demanding Gen AI apps Custom performance optimizations tailored for Gen AI applications are baked into the Baseten Inference Stack. Rapid image generation Serve custom models or ComfyUI workflows, fine-tune for your use case, and quickly generate high-quality images on our inference platform. Optimized transcription We power the fastest, most accurate, and most cost-efficient transcription and speaker diarization on the market. SOTA text-to-speech We built real-time audio streaming to power AI phone calls, voice agents, translation, and more with the lowest time to first byte (TTFB). Performant LLM runtimes Get the highest throughput and lowest latency in production with models like Qwen, DeepSeek, GLM, and gpt-oss. The fastest embeddings Baseten Embeddings Inference (BEI) has over 2x higher throughput and 10% lower latency than any other solution on the market. Ultra-low-latency compound AI Baseten Chains enables granular hardware and autoscaling for compound AI, powering 6x better GPU usage and cutting latency in half. Dedicated inference for custom models Deploy any custom or proprietary model and get out-of-the-box model performance optimizations and massive horizontal scale with the Baseten Inference Stack. docs What our customers are saying See all I want the best possible experience for our users, but also for our company. Baseten has hands down provided both. We really appreciate the level of commitment and support from your entire team. Nathan Sobo Co-Founder, Zed Industries With Baseten, we gained a lot of control over our entire inference pipeline and worked with Baseten&#x27;s team to optimize each step. Sahaj Garg Co-Founder and CTO, Wispr With Baseten Embeddings Inference, we immediately saw 3x speed improvements. Doctors rely on speed when treating patients, and that improvement has been critical to our product experience. 160 millisecond latency is crazy. Jagath Jai Kumar Full Stack Engineer, OpenEvidence With the launch of Brain MAX we&#x27;ve discovered how addictive speech-to-text is - we use it every day and want it everywhere. But it&#x27;s difficult to get reliable, performant, and scalable inference. Baseten helped us unlock sub-300ms transcription with no unpredictable latency spikes. It&#x27;s been a game-changer for us and our users. Mahendan Karunakaran Head of Mobile Engineering, Clickup Inference for custom-built LLMs could be a major headache. Thanks to Baseten, we&#x27;re getting cost-effective high-performance model serving without any extra burden on our internal engineering teams. Instead, we get to focus our expertise on creating the best possible domain-specific LLMs for our customers. Waseem Alshikh CTO and Co-Founder, Writer With the launch of Brain MAX we&#x27;ve discovered how addictive speech-to-text is - we use it every day and want it everywhere. But it&#x27;s difficult to get reliable, performant, and scalable inference. Baseten helped us unlock sub-300ms transcription with no unpredictable latency spikes. It&#x27;s been a game-changer for us and our users. I want the best possible experience for our users, but also for our company. Baseten has hands down provided both. We really appreciate the level of commitment and support from your entire team. Nathan Sobo Co-Founder, Zed Industries case study Explore Baseten today Start deploying Talk to an engineer Product Dedicated Inference Model APIs Training Frontier Gateway Baseten Inference Platform Model Runtimes Infrastructure Multi-cloud Deployment options Cloud Self-hosted Hybrid Embedded engineering Forward deployed engineers Modalities Transcription Image Generation Text-to-speech Large language models Compound AI Embeddings Industries Enterprise Healthcare Developer Model library Documentation Changelog Resources Research Customers Blog Guides Events Partners Savings calculator Trust Center About us Startups Careers Contact us Legal Terms and Conditions Privacy Policy Service Level Agreement all systems normal © 2026 Baseten Product Dedicated Inference Model APIs Training Frontier Gateway Baseten Inference Platform Model Runtimes Infrastructure Multi-cloud Deployment options Cloud Self-hosted Hybrid Embedded engineering Forward deployed engineers Modalities Transcription Image Generation Text-to-speech Large language models Compound AI Embeddings Industries Enterprise Healthcare Developer Model library Documentation Changelog Resources Research Customers Blog Guides Events Partners Savings calculator Trust Center About us Startups Careers Contact us Legal Terms and Conditions Privacy Policy Service Level Agreement all systems normal © 2026 Baseten Popular mode

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AgentSpeed score for baseten.co
<a href="https://agentspeed.com/scan/baseten.co"><img src="https://agentspeed.com/badge/baseten.co" alt="AgentSpeed agent-readiness score" height="56"></a>

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Full breakdown

13 pass2 warn12 fail3 skip
Discoverability
pass
robots.txt present
A robots.txt is reachable at the site root.
100/100
pass
robots.txt allows AI agents
All 8 answer-time access agents allowed.
100/100
fail
Content-Signal directivesemerging
No Content-Signal directives. Add e.g. `Content-Signal: ai-train=no, ai-summarize=yes` to declare granular AI usage policy beyond binary allow/disallow.
0/100
pass
llms.txt present
Found /llms.txt (25605 bytes), H1 + at least one link present.
100/100
pass
Sitemap present
sitemap.xml reachable and referenced from robots.txt.
100/100
fail
Link response headers
No HTTP Link: response headers. Emit canonical/alternate/describedby relations so HEAD-only or stream-rendering agents get them without parsing HTML.
0/100
pass
Canonical URL
Canonical points to self: https://www.baseten.co/.
100/100
fail
MCP server cardemerging
No valid MCP Server Card at /.well-known/mcp/server-card.json. Publish one so agents can discover your tools without HTML scraping.
0/100
fail
OAuth authorization metadataemerging
No RFC 8414 metadata at /.well-known/oauth-authorization-server. Agents that act on behalf of users need this to discover your authorization endpoints.
0/100
fail
OAuth resource metadataemerging
No RFC 9728 metadata at /.well-known/oauth-protected-resource. Publish it so agents can discover required scopes without hand-coded credentials.
0/100
fail
API catalog / OpenAPIemerging
No /.well-known/api-catalog (RFC 9727) and no /openapi.json|yaml. Publish one so agents that integrate with APIs can discover your endpoints.
0/100
fail
Web Bot Authemerging
No Web Bot Auth JWKS at /.well-known/http-message-signatures-directory.json. Publish one to allow trusted agents while keeping a default-deny posture for the rest.
0/100
Readability
fail
Markdown negotiationemerging
Accept: text/markdown returns HTML, not markdown. Serve a markdown variant of primary content when requested; agents summarize and cite it more reliably.
0/100
fail
Text-to-markup ratio
Visible text is 1.8% of HTML weight (8219/446449 bytes). Low. Markup may be crowding out agent-usable text.
14/100
skip
Content without JavaScript
Browser pass unavailable; cannot measure JS dependency.
warn
Heading hierarchy
Heading issues: 2 <h1> tags (expected 1).
75/100
pass
Cookie wall blocks content
No common consent-modal markers detected.
100/100
pass
Page title
A concise <title> is present (60 chars).
100/100
pass
Meta description
A well-sized meta description is present (98 chars).
100/100
Structured data
fail
JSON-LD present
No JSON-LD blocks found. Add a <script type="application/ld+json"> with a schema.org type for this page.
0/100
skip
Structured data validates
No JSON-LD blocks present; nothing to validate (covered by structured_data.jsonld_present).
pass
Schema type coverage
Page intent unclear; no specific schema.org type expected.
100/100
Actionability
pass
Paywall / login wall
No paywall or login-wall detected on the landing URL.
100/100
fail
Agent Skills manifestemerging
No Agent Skills manifest at /.well-known/agent-skills.json. Enumerate the tasks agents can perform (search, add-to-cart, contact-support) so they pick the right one without scraping.
0/100
fail
WebMCP actionsemerging
No WebMCP detected. On pages with first-class actions (cart, support, account), embed a WebMCP server so on-page agents invoke tools directly.
0/100
pass
Primary action reachable
Primary offering identified ("AI model inference platform") with price/CTA ("Get started").
100/100
pass
Reachability
HTTP 200 after 1 redirect.
100/100
Performance
warn
Time to first byte
TTFB 948ms. Acceptable.
60/100
skip
Full render time
Full-render time unavailable (browser pass skipped or failed).
pass
Page weight
Initial document is a lean 436 KB.
100/100
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