Slite vs Together
A detailed comparison to help you choose between Slite and Together.
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Verdict: Together wins
Together scores 4.3/5, edging out Slite at 3.7/5. 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.
Slite AI-powered team knowledge base | Together Ultra-fast scalable AI model development platform | |
|---|---|---|
| Rating | 3.7 (1 review) | 4.3 (1 review) |
| Pricing Model | freemium | usage-based |
| Starting Price | Free tier available | Pricing varies |
| Best For | Teams of roughly 10–200 whose core problem is keeping written knowledge verified, current, and answerable — not teams wanting an all-in-one workspace. | 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 | free tierteam features | team featuresapi access |
| Visit Slite → | Visit Together → |
Slite
Pros
- + The maintenance loop works: stale unverified docs were flagged in the Knowledge Management Panel within a week in my test workspace, and re-verification is one click with recorded state
- + Ask declined to invent an answer when my workspace had no source for the question and logged the gap in AI answers insights — the gap report is the feature I'd demo first
- + Clean, fast editor with real export paths (PDF, Markdown, HTML) — onboarding and support docs imported and rendered without cleanup in my testing
- + MCP and API access are included from the $10/user Basic tier, which is earlier than most knowledge-base competitors expose programmatic access
- + Slite Agent on Pro ($20/user/mo billed yearly) answers across connected tools and runs fact-checking with suggested fixes, not just keyword search
Cons
- - No free plan at time of writing — the 14-day trial is the only unpaid access, and cached/older listings still advertise a free tier that no longer exists
- - Basic's 30 AI questions per seat per month burned quickly during my testing; heavy Ask users will hit the ceiling monthly
- - No relational databases, formulas, or project views — teams leaving Notion or Coda lose operational tracking entirely
- - Storage is tight (5GB/user Basic, 10GB/user Pro, 200MB upload cap on Basic) for anything media-heavy
- - Small vendor (11–50 employees): SCIM, audit logs, SLA, and dedicated support are Enterprise-tier and custom-priced
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, Slite or Together?▼
Together scores higher at 4.3/5 vs 3.7/5 for Slite, making it the better-rated option in our comparison.
What is the difference between Slite and Together?▼
Slite: Slite is a team knowledge base that keeps documents verified and current, and answers questions from them across connected tools. Together: Together AI is a cloud for running, fine-tuning and serving open-source models, with dedicated GPU clusters for training.
Is Slite or Together more affordable?▼
Slite starts at €0/mo, Together starts at €0/mo. Check the comparison table above for current pricing.
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