Mistral AI vs Groq
Both are alternatives to OpenAI API (ChatGPT). Here's how they stack up — verified facts, no spin.
Also searched as Groq vs Mistral AI — same comparison, one verdict.
Mistral AI is open source (Apache-2.0 (open-weight models); proprietary API) and Groq is not (Proprietary (platform); serves open-weight models) — so the real question is whether you want to own the local & sovereign ai stack or rent it.
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.
Groq
The speed king — open models at 500+ tokens/second on custom LPU chips.
Groq runs open models (Llama and friends) on its custom LPU hardware and is, as of mid-2026, the fastest mainstream inference API available — 500+ tokens per second, at prices mostly under $1 per million tokens (Llama 3.3 70B at $0.59/$0.79). If your product's bottleneck is latency — voice agents, live UX, rapid tool loops — Groq is the honest answer. It's a proprietary hosted platform, but like Together, the models themselves are open, so you're renting speed, not locking in your stack.
Side by side
10 points of comparison, every one read from a verified field. Green marks the side that wins a row outright. A dash means we do not hold that fact — never that it is zero.
| Mistral AI | Groq | |
|---|---|---|
| Sovereignty ScoreOur transparent 0–100 composite for data ownership and exit cost. | 70 | 42 |
| Open source | Yes | No |
| Self-hostable | Yes | No |
| Local-first data | 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 | Most models under $1 per 1M tokens; Llama 3.3 70B $0.59/$0.79; batch −50% |
| RAM to run it wellThe figure that actually matters, not the vendor's minimum. | 24 GB of VRAM for Ministral 3 14B in FP8 (stated on its card). Mistral Small 3.2 (24B) needs ~55 GB in bf16, or fits a single RTX 4090 once quantised per the Small 3.1 card. Small 4 (119B MoE) and Large 3 (675B MoE) are multi-GPU models. | — |
| Realistic running costWhat the box costs each month if you run it yourself. | $0 on an 8 GB gaming GPU you already own for Ministral 3 3B. For the 14B, a 24 GB RTX 4090 rents for $0.34–0.74/hr on RunPod (about $250–540/mo if left on); Mistral Small in bf16 needs an 80 GB A100/H100 at $1.19–3.49/hr (RunPod list prices, read 2026-09-30) | — |
| Setup timeHonest first-install estimate, not the marketing quickstart. | An hour with vLLM in Docker once the GPU drivers work; a day if you are also choosing quantisation and context length | — |
| Ongoing maintenanceThe part nobody budgets for. | New checkpoints arrive every few months with new vLLM and mistral_common minimums (Ministral 3 needs vLLM 0.12.0+), so upgrading the model usually means upgrading the runtime too. Re-read the licence line on each new card before swapping it in. | — |
Mistral AI edges it on the Sovereignty Score, but the right pick depends on the trade-offs below.
What will the GPU cost? Compare every company’s hourly price
Weighing both against staying on OpenAI API (ChatGPT)? Is OpenAI API (ChatGPT) free? What it actually costs →
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
Groq
Strengths
- +Fastest inference on the market (500+ tok/s)
- +Very low prices on open models
- +OpenAI-compatible API — near drop-in
Trade-offs
- −Hosted-only; custom hardware means no self-host path for the speed
- −Model catalog is narrower than Together's
Which one fits you
The trade-offs above, turned into a decision. Find the line that describes your team.
Choose Mistral AI
if you want the source and the option to fork it, and you would rather run it on your own hardware, and open Apache-2.0 weights — you can take the model home.
Choose Groq
if fastest inference on the market (500+ tok/s).
Neither, yet
if both carry a real cost you should weigh first — top-end quality trails the leading US frontier models, and hosted-only; custom hardware means no self-host path for the speed. If either of those is a dealbreaker for your team, the shortlist is wrong rather than the choice.
What it takes to run these yourself
Real requirements and honest running costs, not the vendor quickstart.
Mistral AI vs Groq — common questions
Is Mistral AI a better fit than Groq for local & sovereign ai?
It depends on what you are optimising for, and the honest split is this: Mistral AI scores 70 to Groq's 42 on data ownership and exit cost, so it is the safer choice if you care about being able to leave. Groq earns its place on a different axis — fastest inference on the market (500+ tok/s). Neither is a wrong answer for every team; the table above is the actual comparison.
What happens if we want to switch later?
Neither of these is local-first by default, so plan the exit at the point you adopt rather than later. Export what matters on a schedule instead of trusting you can retrieve it on demand — that is the most common way a local & sovereign ai migration turns into a project instead of an afternoon.
Is Mistral AI free?
Mistral AI: Open weights free to self-host; API from $0.04/1M tokens (Ministral 3B), Large at $2/$6 per 1M. The other side of this comparison, Groq, is priced as Most models under $1 per 1M tokens; Llama 3.3 70B $0.59/$0.79; batch −50%. "Free" here means no licence fee — if you self-host it you still pay for the server, and the running cost row above is our honest estimate of that.
Can I self-host Mistral AI?
Mistral AI can be self-hosted; Groq cannot, so it stays on the vendor's infrastructure whatever you do.
Are Mistral AI and Groq both alternatives to OpenAI API (ChatGPT)?
Yes — both appear in our OpenAI API (ChatGPT) comparison, which is why they are worth putting side by side. People usually arrive here already having decided to move off OpenAI API (ChatGPT) and now choosing between the two replacements, which is a narrower and much easier question.
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Facts verified 2026-07-04. Licenses and pricing change — spotted something out of date? That's a correction we want.