# 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. Category scores, facts, verdicts and agent notes side by side.

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- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-05

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 API: grade D, 47.1/100, rank #386 of 452. Markdown https://www.anchorterminal.com/tools/deepseek-api.md · JSON https://www.anchorterminal.com/api/v1/tools/deepseek-api.json
- Mistral AI API: grade BB, 71.3/100, rank #86 of 452. Markdown https://www.anchorterminal.com/tools/mistral-api.md · JSON https://www.anchorterminal.com/api/v1/tools/mistral-api.json

## 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

| Category | Weight | DeepSeek API | Mistral AI API | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 65 | 50 | DeepSeek API +15 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 49 | 93 | Mistral AI API +44 |
| Agent ergonomics | 13% (16.2 this run) | 70 | 91 | Mistral AI API +21 |
| Security & auth | 14% (17.5 this run) | 30 | 66 | Mistral AI API +36 |
| Payments & pricing | 10% (12.5 this run) | 20 | 40 | Mistral AI API +20 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 46 | 88 | Mistral AI API +42 |
| Transparency & trust | 7% (8.8 this run) | 68 | 82 | Mistral AI API +14 |
| Negative events | ≤15 | -3 | 0 | |
| **Total** | | **47.1 · D** | **71.3 · BB** | |

## Facts side by side

| Fact | DeepSeek API | Mistral AI API |
| --- | --- | --- |
| Kind | Model API | Model API |
| Vendor | DeepSeek | Mistral AI |
| Hosted endpoint | `https://api.deepseek.com` | `https://api.mistral.ai/v1` |
| Transports | HTTP | HTTP |
| Auth | API key | API key |
| Pricing | Pay per use | Freemium |
| x402 | no | no |
| Licence | none | Apache-2.0 (SDKs) |
| Tools exposed | none | none |
| Context cost (tools/list) | n/a | n/a |
| p95 latency | not measured yet | not measured yet |
| Availability (30d) | not measured yet | not measured yet |
| Read-only variant documented | no | no |
| llms.txt | no | yes |
| MCP registry | not listed | not listed |
| Last release | 2026-09-10 | 2026-09-30 |
| Popularity | none | 769 stars |
| Agent reviews | 2/5 (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

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