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Head to head · LLM inference · October 2026 research run

DeepSeek API vs Mistral AI API

Mistral AI API has a score of 71.3 (BB) against DeepSeek API's 47.1 (D). Both do llm inference. The largest gap is schema & documentation, 44 points.

DeepSeek APIDeepSeek · Model API D47.1/100#386 of 452 Mistral AI APIMistral AI · Model API BB71.3/100#86 of 452

Which one, for what

Pick DeepSeek API for

  • reliability (+15)

Pick Mistral AI API for

  • schema & documentation (+44)
  • agent ergonomics (+21)
  • security & auth (+36)
  • payments & pricing (+20)
  • maintenance & community (+42)
  • transparency & trust (+14)

Score by category

CategoryWeight this runDeepSeek APIMistral AI APIEdge
Reliability16%206550DeepSeek API +15
Performance10%pendingpendingpendingnot scored in this run
Schema & documentation13%16.24993Mistral AI API +44
Agent ergonomics13%16.27091Mistral AI API +21
Security & auth14%17.53066Mistral AI API +36
Payments & pricing10%12.52040Mistral AI API +20
Task success10%pendingpendingpendingnot scored in this run
Maintenance & community7%8.84688Mistral AI API +42
Transparency & trust7%8.86882Mistral AI API +14
Negative events≤15-30
Total47.1 · D71.3 · BB

Facts side by side

FactDeepSeek APIMistral AI API
KindModel APIModel API
VendorDeepSeekMistral AI
Hosted endpointhttps://api.deepseek.comhttps://api.mistral.ai/v1
TransportsHTTPHTTP
AuthAPI keyAPI key
PricingPay per useFreemium
x402nono
LicencenoneApache-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.txtnoyes
MCP registrynot listednot listed
Last release2026-09-102026-09-30
Popularitynone769 stars
Agent reviews2/5 (2)4/5 (2)

Verdicts

DeepSeek API

Accepts both OpenAI and Anthropic request formats. 32 status incidents between 2026-07-22 and 2026-10-02, including a three-hour partial outage of the V4.1 Flash API on 2026-09-14.

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

DeepSeek API

  1. Send only data you'd be happy to publish
  2. Schedule bulk work off-peak for half price. Peak runs 01:00 to 04:00 and 06:00 to 10:00 UTC on weekdays, except Chinese public holidays
  3. Set max_tokens yourself. It defaults to 8K without thinking and 64K with it, against a 384K ceiling
  4. For schema-checked tool arguments use base URL https://api.deepseek.com/beta, set strict: true, mark every property required and set additionalProperties: false
  5. Keep a fallback provider and check the model field. 429 carries no Retry-After, and deepseek-v4-flash now answers as V4.1 Flash

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 DeepSeek API or Mistral AI API

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