Mistral AI vs Together AI
Both are free/open-source alternatives to OpenAI API (ChatGPT). Here's how they stack up — verified facts, no spin.
Mistral AI
Open-weight Apache-2.0 models with an EU-hosted API — the exit ramp stays open.
Mistral is the middle path between a closed API and full self-hosting: many of its models (Ministral 3B/8B/14B, Small, Devstral, Magistral Small and others) ship as open weights under Apache-2.0, so anything you build on La Plateforme's API can later move onto your own hardware — the exit ramp is built in. The API is EU-hosted (a real advantage for GDPR-sensitive workloads) and aggressively priced, from $0.04 per million tokens for Ministral 3B up to $2/$6 for Mistral Large.
Together AI
One API for the whole open-model universe — Llama, DeepSeek, Qwen and more.
Together AI is a hosted inference cloud for open models: one OpenAI-compatible API serving Llama, DeepSeek, Qwen, Mistral and dozens more, priced from about $0.05 to $9 per million tokens (Llama 3.3 70B around $0.88). The platform itself is commercial, but everything it serves is open-weight — so unlike a closed lab API, your exit is real: the same model you call today can run on your own GPUs tomorrow. A strong bridge for teams not ready to operate vLLM themselves.
Side by side
| Mistral AI | Together AI | |
|---|---|---|
| Sovereignty Score | 70 | 46 |
| Open source | Yes | No |
| Self-hostable | Yes | No |
| Local-first | No | No |
| License | Apache-2.0 (open-weight models); proprietary API | Proprietary (platform); serves open-weight models |
| Pricing | Open weights free to self-host; API from $0.04/1M tokens (Ministral 3B), Large at $2/$6 per 1M | Usage-based, ~$0.05–$9 per 1M tokens by model; intro credits for new accounts |
Mistral AI edges it on the Sovereignty Score, but the right pick depends on the trade-offs below.
Mistral AI
Strengths
- +Open Apache-2.0 weights — you can take the model home
- +EU data residency (GDPR-friendly by default)
- +Very competitive pricing across the range
- +Codestral for code, Ministral for edge/cheap workloads
Trade-offs
- −Top-end quality trails the leading US frontier models
- −Which models are open vs API-only varies — check per model
Together AI
Strengths
- +Huge open-model catalog behind one OpenAI-compatible API
- +The models are open — migrating to self-hosting later is realistic
- +Often far cheaper than closed frontier APIs for comparable tasks
Trade-offs
- −A hosted US cloud — your prompts transit their infrastructure
- −Quality/cost varies widely across the catalog; you do the picking
More OpenAI API (ChatGPT) head-to-heads
Facts verified 2026-07-04. Licenses and pricing change — spotted something out of date? That's a correction we want.