Swapp vs Together
A detailed comparison to help you choose between Swapp and Together.
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Verdict: Together wins
Together scores 4.3/5, edging out Swapp at 4.1/5. 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.
Swapp AI-powered architectural documentation automation platform | Together Ultra-fast scalable AI model development platform | |
|---|---|---|
| Rating | 4.1 (1 review) | 4.3 (1 review) |
| Pricing Model | paid | usage-based |
| Starting Price | From $99/mo | Pricing varies |
| Best For | Mid-to-large architecture firms with heavy Revit or ArchiCAD production volume who want CD documentation and modeling automation trained on their own standards. | 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 Swapp → | Visit Together → |
Swapp
Pros
- + Executes real CD work inside Revit and ArchiCAD — in my walkthrough, the annotation run included a legibility pass that detected and re-placed overlapping tags, so cleanup isn't left to the user
- + Trains on the firm's own standards and production history rather than generic rules; the resulting intelligence stays firm-owned (stated no-training on general models)
- + Frank's approve-then-execute agentic loop keeps a human in control of model changes instead of firing off unattended edits
- + Concrete enterprise trust posture: ISO/IEC 27001:2022 certified (cert #1125599), tenant isolation, native BIM files never sent to third-party LLM providers
- + Named production customers (Page, VLK Architects, SNHA, MOREgroup) with renewals quoted publicly — not a pilot graveyard
Cons
- - Main pricing page is custom-quote credit pricing while pricing-v2 shows $45/user/mo Pro and $95/user/mo Team tiers — both waitlist/early-access gated at time of writing
- - Credit costs per task type are not published in units a buyer can model before signing
- - Not triable by a solo or small studio: the value depends on having firm standards and production volume to train against
- - Vendor statistics (80% automation, 35M+ sq ft, 104,300+ hours saved) are self-reported and not independently audited
- - Output still needs firm QA on critical sheets — documentation errors propagate to construction
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, Swapp or Together?▼
Together scores higher at 4.3/5 vs 4.1/5 for Swapp, making it the better-rated option in our comparison.
What is the difference between Swapp and Together?▼
Swapp: Swapp revolutionizes architectural workflows with AI-powered automation for documentation, design optimization, and seamless project integration. Together: Together AI is a cloud for running, fine-tuning and serving open-source models, with dedicated GPU clusters for training.
Is Swapp or Together more affordable?▼
Swapp starts at €99/mo, Together starts at €0/mo. Check the comparison table above for current pricing.
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