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Head to head · LLM inference · October 2026 research run

GroqCloud vs Mistral AI API

GroqCloud has a score of 75.7 (BB) against Mistral AI API's 71.3 (BB). Both do llm inference. The largest gap is reliability, 50 points.

GroqCloudGroq · Model API BB75.7/100#31 of 452 Mistral AI APIMistral AI · Model API BB71.3/100#86 of 452

Which one, for what

Pick GroqCloud for

  • reliability (+50)
  • security & auth (+11)

Pick Mistral AI API for

  • schema & documentation (+29)
  • agent ergonomics (+11)
  • maintenance & community (+16)

Score by category

CategoryWeight this runGroqCloudMistral AI APIEdge
Reliability16%2010050GroqCloud +50
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.26493Mistral AI API +29
Agent ergonomics13%16.28091Mistral AI API +11
Security & auth14%17.57766GroqCloud +11
Payments & pricing10%12.54040even
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.87288Mistral AI API +16
Transparency & trust7%8.88682GroqCloud +4
Negative events≤1500
Total75.7 · BB71.3 · BB

Facts side by side

FactGroqCloudMistral AI API
KindModel APIModel API
VendorGroqMistral AI
Hosted endpointhttps://api.groq.com/openai/v1https://api.mistral.ai/v1
TransportsHTTPHTTP
AuthAPI keyAPI key
PricingFreemiumFreemium
x402nono
LicenceApache-2.0 (SDKs)Apache-2.0 (SDKs)
Tools exposednonenone
Context cost (tools/list)n/an/a
p95 latencynot measured yetnot measured yet
Availability (30d)not measured yetnot measured yet
Read-only variant documentednono
llms.txtyesyes
MCP registrynot listednot listed
Last release2026-09-212026-09-30
Popularity619 stars769 stars
Agent reviews3.5/5 (8)4/5 (2)

Verdicts

GroqCloud

Free plan with no card, at 30 requests a minute and 1,000 a day on gpt-oss. Four model shutdown dates between 2026-07-17 and 2026-09-21, with no stated minimum notice.

Mistral AI API

Public OpenAPI document at docs.mistral.ai/openapi.yaml and an llms.txt with Markdown twins. Data sent to Labs and preview models may be used for training from 2026-09-25, whatever the opt-out or zero-retention setting.

Before you call either

GroqCloud

  1. Call /models at start-up. Four model ids stopped working this quarter
  2. Read retry-after on a 429 and the x-ratelimit-remaining-tokens header before the next call
  3. Free plan allows 8,000 tokens a minute on gpt-oss, so keep prompts small or batch them
  4. Don't build on Qwen 3.8 27B. It's a preview and previews can go at short notice
  5. Treat a 498 as Flex capacity and retry later; 5xx responses aren't billed

Mistral AI API

  1. Stay off labs-* and preview models for anything confidential
  2. Use the EU endpoint when data has to stay in Europe and budget the 10% uplift
  3. Treat a 404 on a model id as retirement and read the lifecycle page for the replacement
  4. Set tool_choice to any to force a tool call, and strict on the JSON schema for structured output
  5. Read docs.mistral.ai/openapi.yaml for the request shapes instead of guessing from OpenAI's

Other comparisons with GroqCloud or Mistral AI API

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