Toast vs Together
A detailed comparison to help you choose between Toast and Together.
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Verdict: Together wins
Together scores 4.3/5, edging out Toast at 4.2/5. 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.
Toast Restaurant-POS | Together Ultra-fast scalable AI model development platform | |
|---|---|---|
| Rating | 4.2 (1 review) | 4.3 (1 review) |
| Pricing Model | paid | usage-based |
| Starting Price | Pricing varies | Pricing varies |
| Best For | US restaurants — from single locations to regional groups — that want one deeply integrated platform for POS, kitchen, ordering, payroll and cost control and can negotiate their processing rate. | 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 | — | team featuresapi access |
| Visit Together → |
Toast
Pros
- + Functional depth covers the whole restaurant: in my walkthrough the KDS routing, table management, online ordering and xtraCHEF cost analytics formed one system rather than a bundle of integrations.
- + Restaurant-grade proprietary hardware built for kitchen conditions, with 24/7/365 support and installation/network configuration included (source: Toast pricing comparison chart).
- + Plan entry is flexible: $0/month Starter Kit with no upfront hardware cost for low-volume sites, $69/month Point of Sale with better processing (source: pos.toasttab.com/pricing, at time of writing).
- + Payroll bundle at $69/month + $9/employee/month (promotional, at time of writing) connects scheduling, tips and pay in one system.
- + Offline mode keeps orders moving when the internet drops — a real operational requirement that Toast builds for.
Cons
- - Processing dominates the bill: 2.49% + 15¢ in-person on the POS plan, 3.09%–3.69% + 15¢ on Starter Kit — on $50k/month that is roughly $1,400+/month versus $69 software (POSUSA, October 2026).
- - Real all-in cost for a typical single location is $1,500–$2,500+/month and $3,000–$5,000+/month for full-service or multi-location, per POSUSA's research — well beyond headline pricing.
- - Proprietary hardware: terminals, handhelds and KDS screens must be Toast's, and replacement cost over three years is a real line item.
- - Add-on sprawl (Digital Storefront, Marketing, Payroll, xtraCHEF, Restaurant Management, Retail) each priced separately; the stack you want always costs more than the quote you saw first.
- - Quote-based pricing with sales-rep negotiation and common multi-year contracts — the effective rate you get is the one you negotiate.
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, Toast or Together?▼
Together scores higher at 4.3/5 vs 4.2/5 for Toast, making it the better-rated option in our comparison.
What is the difference between Toast and Together?▼
Toast: Toast is a restaurant point-of-sale and management platform covering orders, payments, online ordering, kitchen display and payroll. Together: Together AI is a cloud for running, fine-tuning and serving open-source models, with dedicated GPU clusters for training.
Is Toast or Together more affordable?▼
Toast starts at €0/mo, Together starts at €0/mo. Check the comparison table above for current pricing.
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