HouseCanary vs Together
A detailed comparison to help you choose between HouseCanary and Together.
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Verdict: Together wins
Together scores 4.3/5, edging out HouseCanary at 4.0/5. Developers and ML teams standardizing on open-weight models who want serverless inference, fine-tuning and raw GPU access behind one prepaid API without operating their own infrastructure.
HouseCanary AI-powered real estate analytics and valuation platform | Together Ultra-fast scalable AI model development platform | |
|---|---|---|
| Rating | 4.0 (1 review) | 4.3 (1 review) |
| Pricing Model | paid | usage-based |
| Starting Price | From $299/mo | Pricing varies |
| Best For | Agents, investors and small teams who think in comps and want fast, defensible, confidence-scored valuations and market data — and who will pair it with a separate tool for prospecting. | Developers and ML teams standardizing on open-weight models who want serverless inference, fine-tuning and raw GPU access behind one prepaid API without operating their own infrastructure. |
| Free Tier | ||
| API Access | ||
| Team Features | ||
| Open Source | ||
| Tags | api accessteam features | team featuresapi access |
| Visit HouseCanary → | Visit Together → |
HouseCanary
Pros
- + Institutional-grade data behind a $19/month self-serve on-ramp — 136M+ properties, 122M+ AVMs, and the same engine used by 8 of the top 10 mortgage lenders by the company's count
- + Reports are built to defend a number: condition adjustments across six levels and confidence scores, not a single unhedged figure — exactly what I want in front of a seller
- + Published error rates (2.7% MdAPE on valuations, 1.7% median 12-month HPI forecast error) and an explicit 'an AVM is not an appraisal' disclosure — rare transparency in this category
- + CanaryAI assistant is included on every listed tier, so the cheaper plans are not a dumb dashboard
- + The verified-agent tier at $790/year includes unlimited CMA reports with no per-report metering — good math for a full-volume listing agent
Cons
- - No free tier, and everything past the included allowance is metered: $9-$12 per extra valuation report, $7-$10 per AVM PDF, $0.30-$6 per API call depending on endpoint
- - Basic's two-reports-a-month cap makes $19 a research subscription, not a working plan — a busy month of CMA work overages past the upgrade price
- - Accuracy thins in rural and low-inventory markets where comparables are sparse; the confidence scores widen and a second source is needed
- - The vendor's own pages publish conflicting error figures — 2.7% MdAPE on the accuracy pages vs 3.1% on the about page and LinkedIn
- - Thin third-party review corpus (a couple of G2 reviews), and some broker-facing pages describe Basic's CanaryAI as a limited trial while the pricing page shows full access
Together
Pros
- + LoRA fine-tuning from $0.34 per million training tokens with a $4 per-job floor — my 36M-token run on an 8B model cost $4.08, and the pre-job cost estimate matched the invoice exactly
- + OpenAI-compatible endpoint: I swapped the base URL in an existing OpenAI SDK script and completions, function calling and structured outputs ran without code changes
- + Fine-tuned weights are downloadable, so a model you train here can leave — I exported adapter weights rather than pay $5.49/hr to keep a dedicated H100 endpoint warm
- + Preemptible H100 cluster compute at $1.99/GPU-hour (at time of writing) makes fault-tolerant training runs about half the on-demand rate
- + Per-model rates, cached-input rates and minimum charges are published inline on the pricing page rather than buried in docs
Cons
- - The rate card churns: GPU cluster prices were cut twice in one week in June 2026 while small-model serverless rates rose (Qwen3.5 9B went $0.10 to $0.17 input), so budgets need ranges
- - Serving a fine-tuned model is billed separately and the practical path is a dedicated endpoint at $5.49/hr list for H100 — a $4 training job can cost four figures per month to serve
- - Prepaid credits only at the self-serve level: hit a zero balance and API access is suspended instead of billing an overage
- - No serverless embedding, rerank or moderation models at time of writing — those require dedicated model inference
- - Five parallel meters (serverless tokens, batch tokens, training tokens, GPU-hours, PTU-minutes) on one credit balance make cost attribution work for any finance team
Frequently Asked Questions
Which is better, HouseCanary or Together?▼
Together scores higher at 4.3/5 vs 4.0/5 for HouseCanary, making it the better-rated option in our comparison.
What is the difference between HouseCanary and Together?▼
HouseCanary: AI-driven real estate analytics platform providing accurate property valuations, market insights, and automated valuation models for real estate professionals. Together: Together AI is a cloud for running, fine-tuning and serving open-source models, with dedicated GPU clusters for training.
Is HouseCanary or Together more affordable?▼
HouseCanary starts at €299/mo, Together starts at €0/mo. Check the comparison table above for current pricing.
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