Thunderbit vs Together
A detailed comparison to help you choose between Thunderbit and Together.
🏆
Verdict: Together wins
Together scores 4.3/5, edging out Thunderbit at 3.3/5. 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.
Thunderbit AI-powered lead scraping in just 2 clicks | Together Ultra-fast scalable AI model development platform | |
|---|---|---|
| Rating | 3.3 (1 review) | 4.3 (1 review) |
| Pricing Model | freemium | usage-based |
| Starting Price | Free tier available | Pricing varies |
| Best For | Non-technical sales, e-commerce and ops teams who need recurring webpage-to-spreadsheet extraction on ordinary public sites and will verify schemas before bulk runs. | 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 | no codeapi accessfree tier | team featuresapi access |
| Visit Thunderbit → | Visit Together → |
Thunderbit
Pros
- + AI Suggest Fields turned a product listing into a clean spreadsheet in two clicks in my test — no selectors, clean Google Sheets export
- + Prebuilt one-click scrapers for Google Maps, Apollo, Zillow and Amazon make lead-list building approachable for non-technical sales staff
- + Coverage beyond visible text — URLs, images, emails, phones, dates and hidden page data are all in scope
- + Schedule and subpage tooling covers the real operational loop: monitor, drill into detail pages, enrich, export
- + Free plan (6 pages/month) is a real trial of the extraction engine rather than a featureless teaser
Cons
- - Credits are charged per output row and consumed even by duplicate or failed rows; large paginated jobs have stopped mid-run and forced paid re-runs
- - Billing complaints are a documented pattern: annual charges presented as monthly, and continued charging after cancellation attempts
- - Struggles against anti-bot protection and page layouts that vary — every schema needs sampled verification before a big job
- - Privacy posture is ambiguous: PII and web history handled per the Chrome listing, conflicting AI-subprocessor statements, unclear retention
- - Support described as slow or unresponsive by multiple reviewers; refunds for wasted credits called cumbersome
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, Thunderbit or Together?▼
Together scores higher at 4.3/5 vs 3.3/5 for Thunderbit, making it the better-rated option in our comparison.
What is the difference between Thunderbit and Together?▼
Thunderbit: AI-powered data scraping tool that enables sales and operations teams to extract leads and other valuable data from websites with just two clicks. Together: Together AI is a cloud for running, fine-tuning and serving open-source models, with dedicated GPU clusters for training.
Is Thunderbit or Together more affordable?▼
Thunderbit starts at €0/mo, Together starts at €0/mo. Check the comparison table above for current pricing.
Stay in the loop
Get weekly updates on the best new AI tools, deals, and comparisons.
No spam. Unsubscribe anytime.