Arya.ai vs Together
A detailed comparison to help you choose between Arya.ai and Together.
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Verdict: Together wins
Together scores 4.3/5, edging out Arya.ai 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.
Arya.ai AI-powered banking and insurance transformation platform | Together Ultra-fast scalable AI model development platform | |
|---|---|---|
| Rating | 3.7 (1 review) | 4.3 (1 review) |
| Pricing Model | paid | usage-based |
| Starting Price | From $5000/mo | Pricing varies |
| Best For | Banks, insurers and lenders — particularly in India and Southeast Asia — that need pre-trained, auditable AI models for KYC, document processing and risk workflows with on-premise or hybrid deployment. | 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 featuressso | team featuresapi access |
| Visit Arya.ai → | Visit Together → |
Arya.ai
Pros
- + Genuinely vertical model library — bank statement analysis, salary-slip extraction, document tampering detection, KYC parsing — not generic wrappers (Apex catalog, 100+ APIs)
- + Evaluation is de-risked: 50 free trial calls per API, 500 free calls across five modules with a corporate email, no sales call required to start
- + Deployment flexibility (cloud, on-premise, hybrid, private cloud) with data-sovereignty positioning matches what regulated buyers actually need
- + Institutional stability: 67% acquired by listed Aurionpro Solutions in April 2024 (~$16.5M), profitable at acquisition, 100+ BFSI clients named publicly
- + Infinity OS's audit trail, human-in-the-loop checkpoints and model-agnostic routing address the explainability demands financial regulators actually impose
Cons
- - No public pricing beyond Apex pay-as-you-go credits — Nexus, Infinity OS and platform deals are all quote-only, blocking cost comparison
- - Performance claims (95%+ accuracy, 99% API success rate, 300M+ annual calls) are vendor figures with no published methodology or benchmarks
- - Prism is 'coming soon' and Infinity OS maturity signals are thin — parts of the flagship roadmap are not yet shipped
- - Per-API credit pools fragment billing across multi-API workflows, and the developer portal shows no SDKs, sandboxes or community support
- - Document formats and compliance packs are India/Southeast Asia-centric first; other markets are secondary
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, Arya.ai or Together?▼
Together scores higher at 4.3/5 vs 3.7/5 for Arya.ai, making it the better-rated option in our comparison.
What is the difference between Arya.ai and Together?▼
Arya.ai: Enterprise AI platform that revolutionizes banking and insurance operations with intelligent automation, risk assessment, and customer service solutions. Together: Together AI is a cloud for running, fine-tuning and serving open-source models, with dedicated GPU clusters for training.
Is Arya.ai or Together more affordable?▼
Arya.ai starts at €5000/mo, Together starts at €0/mo. Check the comparison table above for current pricing.
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