DxGPT Alternative — Free, Anonymous, Patient-Focused
A data-led comparison of DxGPT and Dr.Khan AI across audience, response latency, interface design, and privacy. Both services are free; the differentiation is who each is built for. DxGPT is clinician-first decision support; Dr.Khan AI is patient-first triage and education.
Underlying model performance
Standardized medical question accuracy on MedQA-USMLE for the publicly benchmarked models. Source: Open Medical LLM Leaderboard; Nori et al., Microsoft Research, 2023. GPT-5 mini scores are recent and not yet stably documented in peer-reviewed benchmarks.
Speed and access compared
Two operational dimensions where the services diverge most measurably.
When medical questions become training data
Medical AI services that route queries through closed-model APIs from large model providers (OpenAI, Anthropic, Google) inherit the data-handling policies of those providers in addition to whatever the medical service itself promises. This is not a critique of any specific service; it is a structural feature of the architecture. When a medical AI service is built on top of GPT, Claude, or Gemini, conversations transit through provider infrastructure with provider retention rules applied.
OpenAI’s default API policy as of March 2024 retains conversations for up to 30 days for abuse monitoring and does not use them to train models — but only when explicitly opted out via the appropriate API parameters or enterprise contract. Default consumer ChatGPT, by contrast, uses conversations for training unless the user actively opts out in settings. The granularity of these distinctions matters because it determines whether a sensitive medical question becomes part of a future model’s training corpus.
Carlini et al., “Extracting Training Data from Large Language Models” (2021), demonstrated that LLMs memorize and can be induced to regurgitate portions of their training data verbatim, including personal identifiers. Follow-up work in 2023 showed that even simple extraction attacks recover meaningful training content from production models. For sensitive medical conversations, this means the “your data may be used for training” clause in a privacy policy is not abstract — it is a measurable downstream leakage risk.
The architectural alternative is locally-served open-weights inference. Llama 3.3 70B is an open-weights model — its weights are public, and inference can be performed by any provider (including Groq, where Dr.Khan AI runs). Conversations never transit through a closed-model provider’s training pipeline, because there is no closed-model provider in the path. Whatever data-handling policy the service applies is the only policy that applies; there is no upstream policy layered on top.
For DxGPT’s primary clinical decision support use case — particularly rare-disease differential generation by clinicians evaluating complex cases — the GPT-5 mini reasoning is genuinely strong and the use case is identified clinical work where the conversation already exists in a clinical record. The training-data concern is muted in that context. For the consumer use case where a patient asks anonymous symptom questions, the architectural difference becomes more consequential: open-weights local inference categorically eliminates the upstream-training-leakage risk, while closed-model API services manage it through policy commitments that may or may not be sufficient for a given user’s threat model.
Feature-by-feature comparison
Twelve dimensions evaluated. Color indicates which service holds the advantage on each.
| Dimension | DxGPT | Dr.Khan AI | Advantage |
|---|---|---|---|
| Target audience | Doctors and patients (clinical decision support) | Patients (consumer triage and education) | Comparable |
| Cost | Free for doctors and patients | Free, no upsell | Comparable |
| Underlying model | GPT-5 mini (per public statement) | Llama 3.3 70B + Llama 4 Scout vision | Comparable |
| Account / signup | Required for full diagnostic features | No — fully anonymous | Dr.Khan AI |
| Conversation interface | Diagnostic decision support form | Conversational chat with clarifying questions | Dr.Khan AI |
| Response latency | Standard cloud inference (5–15s on GPT-5 mini) | Sub-second via Groq LPU | Dr.Khan AI |
| Lab image interpretation | Limited | Llama 4 Scout vision model | Dr.Khan AI |
| Multiple workflow flows | Single diagnostic decision flow | Chat / consultation / instant triage | Dr.Khan AI |
| Privacy posture | Standard healthcare-software privacy | Anonymous by architecture, no data stored | Dr.Khan AI |
| Backed by | Foundation 29 (Spanish nonprofit) | Independent product | Comparable |
| Specialty focus | Rare-disease and complex differential strength | General-purpose primary-care triage | Comparable |
| Benchmark transparency | GPT-5 mini known model | MedQA-USMLE cited, primary sources linked | Dr.Khan AI |
- The user is a patient, not a clinician
- Anonymity matters — no account requirement
- Sub-second responses are required
- The query is consumer triage or education
- Lab images need direct interpretation
- The user is a clinician evaluating a complex case
- Rare-disease differential is in the workup
- GPT-5 mini reasoning specifically is required
- Foundation 29 nonprofit backing matters
Frequently asked questions
- What is the best alternative to DxGPT for patients?
- For patient-facing symptom triage and education without an account requirement, Dr.Khan AI is the closer functional fit. DxGPT is excellent for clinical decision support — particularly rare-disease differential generation — but its primary audience is clinicians, and the patient-facing flow is account-gated. Dr.Khan AI is purpose-built for direct consumer triage with no signup and a conversational interface optimized for how patients actually describe symptoms.
- Is Dr.Khan AI based on GPT-5 like DxGPT?
- No. DxGPT runs on GPT-5 mini per their public disclosure. Dr.Khan AI runs on Llama 3.3 70B (open-weights from Meta) served via Groq's LPU infrastructure. Both deliver strong medical reasoning — Llama 3.3 70B scores within ~2 percentage points of GPT-4 on MedQA-USMLE, and GPT-5 mini exceeds GPT-4. The architectural difference matters for cost economics and speed: Llama 3.3 70B on Groq runs roughly 8x cheaper than equivalent inference on OpenAI, and at ~500 tok/sec versus standard cloud inference rates.
- Is DxGPT really free for both doctors and patients?
- Yes — DxGPT is free, supported by Foundation 29, a Spanish nonprofit focused on rare diseases. The free pricing reflects nonprofit sponsorship rather than the underlying inference economics. Dr.Khan AI is also free, but for a different reason: the cost economics of running Llama 3.3 70B on Groq make a sustainable free tier viable without nonprofit subsidy or ad-based monetization.
- How is Dr.Khan AI different from DxGPT?
- Three measurable differences. (1) Audience — DxGPT primarily targets clinicians using AI for diagnostic decision support; Dr.Khan AI targets consumers seeking triage and education. (2) Interface — DxGPT uses a structured diagnostic decision form; Dr.Khan AI uses a conversational chat that asks clinician-style clarifying questions. (3) Architecture — Dr.Khan AI offers three differentiated flows (chat, consultation, instant triage); DxGPT offers a single diagnostic flow. The two services are complementary more than competitive.
- Should I use DxGPT or Dr.Khan AI for symptom checking?
- For first-pass consumer symptom triage — "is this serious enough to see someone, what should I do" — Dr.Khan AI is purpose-built. For complex diagnostic differentials, particularly when rare diseases are in the differential or you are a clinician evaluating a complex case, DxGPT's clinical decision support is genuinely strong. The two services do not directly substitute. Most users will benefit from Dr.Khan AI; complex multi-system cases benefit from DxGPT followed by a clinician.
- Is DxGPT FDA-approved?
- DxGPT positions itself as diagnostic decision support, not a regulated medical device. Standard medical AI products in this category typically operate as decision support rather than seeking FDA medical-device clearance. Dr.Khan AI takes the same posture: triage and education only, not a regulated medical device, not a substitute for licensed clinician assessment. Always discuss any AI-generated medical output with a licensed clinician before acting on it.
Evaluate Dr.Khan AI as your DxGPT alternative
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