We Warmed the Model. The Next Question Still Took Four Minutes
Five dated startup observations separated warm generation from worker readiness, while a slow fake provider exposed a different HTTP timeout.
Reviewed by Victor Sineglazov on October 27, 2026.
We warmed a hosted model, opened the product and still waited more than four minutes for the first answer. The worker had already gone idle again. A successful warm-up request did not mean that the next user would reach the same warm process. This case comes from a September 2026 integration spike for our learning RAG. We were checking whether an existing OpenAI-compatible adapter could reach a separately hosted model. We were not choosing a clinically validated model or measuring the quality of its medical reasoning.
Keep the observations in their original order
The recorded cold-start sequence contains five observations:
| Attempt | Time to first event | Recorded context |
|---|---|---|
| 1 | 221 seconds | Initial model listing and first start |
| 2 | 170 seconds | A new worker for a chat stream |
| 3 | About 2 seconds | A FlashBoot hit |
| 4 | 203 seconds | Warm-up through the backend |
| 5 | 242.5 seconds | Browser question after warm-up; worker had already idled |
Once warm, the direct first-token observations were 0.6 to 1.9 seconds, with 1.3 seconds through the streaming backend path. Generation was recorded at 42 to 48 tokens per second. Those numbers describe different phases of that spike; combining them into one response-time claim would mislead a person waiting on a cold worker.
The small sample does not establish cold-start percentiles.
The fast third observation was a cache or process-snapshot hit in the recorded environment, not proof that every future cold request would take two seconds. Hosting prices and present-day vendor tuning recommendations are outside this article.
Headers arrived before the model did
In the observed streaming path, the event-stream headers arrived in about 0.1 seconds, followed by silence while the worker started. An HTTP success at that point established a transport connection, not a model ready to produce an answer.
The registry's then-default first-token and total deadlines were 60 and 120 seconds. Those budgets could not accommodate the slow observations. The spike used 300 and 360 seconds and recorded that all five attempts fit. This was a historical experiment, not a recommendation to give every operation a six-minute timeout.
A product waiting screen also needs the right explanation. During the recorded browser wait, the interface said it was searching documents. Retrieval was not the long-running stage in that case. A model-start state would communicate a different cause and a different decision about whether to keep waiting.
A second timeout was hiding in the application
Testing a slow fake provider exposed an independent problem. It completed successfully at 45 seconds, while the HTTP caller had already received 503 at about 30.5 seconds. The application configuration named a seven-minute async timeout, and a test that compared configuration values passed.
The result is narrower than a root-cause claim. At the time of the spike, the record had not established why that HTTP endpoint ignored the intended budget. It did establish that the runtime behavior disagreed with the configuration, and that the streaming endpoint was not affected in the same way.
configuration budget: seven minutes
fake provider finishes: 45 seconds
HTTP caller receives failure: about 30.5 seconds
result: configuration comparison did not test request lifetimeWarm-up needs an identity and an expiry
The follow-up options included a longer idle interval, an explicit waking state and a deliberately warm worker during a scheduled demo. These were operational choices proposed in the record. Their approval and deployment remain unresolved in this record.
A useful warm-up observation should therefore record which worker it reached, when it completed and how long the worker remains eligible to serve the next request. Without that link, the test can prove that some process was ready earlier while the visitor starts a new one now.
The integration also found reasoning text leaking into the answer and citation extraction. That is a separate adapter-content defect, not evidence about startup latency. Keeping it separate prevented a slow but complete request from being mistaken for a fully correct product response.
The remaining acceptance check
The spike supported the adapter's ability to reach the hosted model and stream an answer. Its broader three-provider acceptance check remained incomplete because another provider hit the HTTP timeout problem. A successful one-provider path could not close the whole acceptance criterion.
These are dated implementation observations, not fresh tests or a current hosting comparison. For a future cold-start investigation, record connection establishment, first model output and completed answer separately, then send a genuinely slow provider through every exposed request path. A passing configuration assertion cannot substitute for that last request.
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Pharos Production has been in business since 2013, with over 13 years of experience in custom software development. During this time, we have delivered over 110 applications for 200+ clients across 28 industries, including FinTech, healthcare, crypto and e-commerce. We are rated 5/5 on Clutch based on 107 verified reviews (2026).
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Pharos Production is headquartered in Las Vegas, Nevada, USA (5348 Vegas Dr, Las Vegas, NV 89108), with an engineering office in Kyiv, Ukraine (44-B Eugene Konovalets Str. Suite 201, Kyiv 01133). We work with clients worldwide and provide remote collaboration across all time zones. Visit our contact page for directions and scheduling options.
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Pharos Production has a team of 90+ engineers, including software developers, blockchain specialists, QA engineers, DevOps experts, UI/UX designers, project managers and solution architects. Our founder, Dr. Dmytro Nasyrov, holds a PhD in Artificial Intelligence and leads the technical direction of all projects.
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We serve a wide range of clients, from startups and product companies to mid-sized enterprises and large institutions. Our clients include crypto exchanges, FinTech providers (like Pleenk), healthcare organizations, sportsbook operators (like Pro Gambling), e-commerce platforms and SaaS companies. Pharos Production has worked with 200+ clients across 28 industries since 2013, adapting engagement models to match each client's stage, whether it is MVP validation for a startup or enterprise-scale development for an established business.
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A custom software development company like Pharos Production assigns one dedicated engineering team that owns your product across multiple release cycles, instead of handing it off once a contract ends. Agencies more often rotate staff between clients and optimize for fast delivery over long-term product ownership.
Pharos Production keeps the same team on your codebase through 2-week sprints, so there is no re-onboarding cost each time you request a new feature.
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Custom software development costs vary based on project scope and complexity. At Pharos Production, typical project ranges are: MVP development ($10,000-$25,000), suitable for startups validating a product idea; full-fledged production ($25,000-$50,000), for established businesses scaling a proven concept; and full-cycle development ($50,000-$80,000+), for complex enterprise-grade systems. These ranges include architecture design, development, QA testing and deployment. Hourly rates range from $50 to $99 depending on role and seniority. Final pricing depends on technology stack, number of integrations and engagement model (staff augmentation, dedicated team or project outsourcing).
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How long does it take to develop a custom software application?
Development timelines depend on scope and complexity. At Pharos Production, a typical MVP takes 2-4 months, a production-ready application takes 4-8 months and a complex enterprise system can take 8-12+ months. We use an agile methodology with 2-week sprints, delivering working increments after each sprint. Every sprint includes a retrospective, progress report and planning session for the next iteration. This approach ensures transparency and allows businesses to launch faster by prioritizing high-impact features first. Get a timeline estimate for your project.
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Hiring a software development company offers faster time-to-market, lower upfront costs and access to specialized expertise without long-term employment commitments. According to Deloitte's 2024 Global Outsourcing Survey, 57% of companies outsource software development to access skills they cannot hire internally.
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What projects does Pharos Production not take on?
Pharos Production focuses on mid-to-large custom software projects with budgets starting at $10,000. We do not take on template-based websites, WordPress theme customization or short-term contracts under one month. We also do not provide non-technical staffing (marketing, sales or design-only roles). Our strongest fit is blockchain, FinTech and healthcare projects where security, compliance and high-load architecture are critical. For smaller projects or MVPs under $10,000, we recommend exploring freelance platforms or no-code tools as a more cost-effective starting point.
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Why does Pharos Production use agile methodology?
We use agile with 2-week sprints because it reduces the risk of building features that miss the mark. Each sprint ends with a working demo, a retrospective and a plan for the next iteration.
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When should you NOT hire a custom software development company?
Custom development is not the right choice in every situation. You should not hire a custom software company if: your problem is fully solved by an existing SaaS product (e.g. Shopify for e-commerce, Salesforce for CRM); your budget is under $10,000 and timeline is under 4 weeks; you need a simple landing page or marketing website (WordPress or Webflow is faster and cheaper); or you are still validating the idea and have not spoken to potential users yet.
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What kind of projects has Pharos Production delivered?
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FinTech startup - payment platform (MVP)
Scope: mobile app + backend API with bank-grade encryption. Team: 4 engineers, 1 QA. Timeline: 10 weeks. Budget: $38,000. Result: launched on schedule, processed $2M+ in transactions within the first quarter.Healthcare provider - patient portal (Full product)
Scope: HIPAA-aligned web platform with EHR integration, appointment scheduling and telemedicine. Team: 6 engineers, 1 DevOps, 2 QA. Timeline: 6 months. Budget: $120,000. Result: 15,000+ active patients, zero compliance violations in two annual audits.Crypto exchange - trading engine (Complex)
Scope: high-load matching engine handling 50,000+ orders per second, multi-chain wallet infrastructure on Ethereum and Solana. Team: 8 engineers, 2 QA, 1 security auditor. Timeline: 11 months. Budget: $340,000. Result: 99.97% uptime, passed three independent security audits.See more projects: NoMoreBets, Pulse, Sagas, Gambit Stream and Pleenk. For the full portfolio, visit our case studies. Learn more about the technology behind these projects in our guide to stablecoins and crypto infrastructure.
Dmytro Ihnatov is the Lead Backend Developer at Pharos Production. He documents backend architecture and research experiments from the team's work on a professional learning platform for aesthetic medicine.
