Files
ragflow/conf/models/mistral.json
jay77721 2e2d12d262 feat: add batch_size to all embedding model configs (#17877)
## Summary

Add a `batch_size` field to every embedding model entry in
`conf/models/*.json`. The field represents the maximum number of text
inputs that can be submitted to the embedding API in a single request.

**75 embedding models across 30 config files** now carry a `batch_size`.
Values were verified against each provider's official documentation (see
the verification table at `Desktop/embedding_models_verified.md`).

## Distribution

| batch_size | # models | Provider / Model |
|---|---|---|
| 1 | 2 | AWS Bedrock `amazon.titan-embed-text-v1/v2:0` — Bedrock
`invoke` accepts a single input per call |
| 10 | 3 | Aliyun `text-embedding-v3/v4`, Volcengine
`doubao-embedding-vision-251215` |
| 16 | 5 | BaiChuan `Baichuan-Text-Embedding`, Baidu Qianfan
`embedding-v1`, Mistral `mistral-embed`, Replicate (x2) |
| 32 | 10 | NVIDIA NIM (x3), SILICONFLOW (x2), PPIO (x3), GiteeAI
`bge-m3`, HuaweiCloud `bge-m3` |
| 50 | 4 | Tencent Hunyuan `kinfra` embeddings (x4) — `InputList.N` max
50 |
| 96 | 8 | Cohere embed-v3/v4 (x5), Bedrock Cohere (x3) |
| 100 | 3 | Google Gemini `text-embedding-004`, Upstage (x2) |
| 512 | 5 | Zhipu GLM `embedding-2/3` (x2), Perplexity `pplx-embed`
(x2), Astraflow `text-embedding-3-large` |
| 1000 | 9 | Voyage AI (x9) — API reference max |
| 1024 | 1 | DeepInfra `Qwen/Qwen3-Embedding-4B` |
| 2048 | 15 | OpenAI (x3) + OpenAI-API-compatible proxies (CometAPI,
n1n, Jiekou.AI, GreenPT, TogetherAI, NovitaAI) — OpenAI contract limit |
| 16384 | 10 | Jina (x8), 302.AI, GiteeAI `jina-clip-v2` — no documented
Jina batch limit, safe high cap |

---------

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-08-06 10:47:38 +08:00

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{
"name": "Mistral",
"url": {
"default": "https://api.mistral.ai"
},
"url_suffix": {
"chat": "v1/chat/completions",
"models": "v1/models",
"embedding": "v1/embeddings",
"asr": "v1/audio/transcriptions",
"tts": "v1/audio/speech",
"ocr": "v1/ocr"
},
"class": "mistral",
"models": [
{
"name": "mistral-large-latest",
"content_length": 262144,
"max_output": 262144,
"model_types": [
"chat"
],
"tools": {
"support": true
}
},
{
"name": "voxtral-mini-tts-2603",
"model_types": [
"tts"
]
},
{
"name": "voxtral-mini-transcribe-realtime-2602",
"model_types": [
"asr"
]
},
{
"name": "mistral-medium-latest",
"content_length": 262144,
"max_output": 262144,
"model_types": [
"chat"
],
"tools": {
"support": true
}
},
{
"name": "mistral-small-latest",
"content_length": 262144,
"max_output": 262144,
"model_types": [
"chat"
],
"tools": {
"support": true
}
},
{
"name": "ministral-8b-latest",
"content_length": 262144,
"max_output": 262144,
"model_types": [
"chat"
],
"tools": {
"support": true
}
},
{
"name": "ministral-3b-latest",
"content_length": 262144,
"max_output": 262144,
"model_types": [
"chat"
],
"tools": {
"support": true
}
},
{
"name": "pixtral-large-latest",
"content_length": 131072,
"max_output": 131072,
"model_types": [
"chat",
"vision"
],
"tools": {
"support": true
}
},
{
"name": "codestral-latest",
"content_length": 131072,
"max_output": 131072,
"model_types": [
"chat"
],
"tools": {
"support": true
}
},
{
"name": "open-mistral-nemo",
"content_length": 131072,
"max_output": 131072,
"model_types": [
"chat"
],
"tools": {
"support": true
}
},
{
"name": "open-mistral-7b",
"content_length": 32768,
"max_output": 32768,
"model_types": [
"chat"
],
"tools": {
"support": true
}
},
{
"name": "open-mixtral-8x7b",
"content_length": 32768,
"max_output": 32768,
"model_types": [
"chat"
],
"tools": {
"support": true
}
},
{
"name": "open-mixtral-8x22b",
"content_length": 65536,
"max_output": 65536,
"model_types": [
"chat"
],
"tools": {
"support": true
}
},
{
"name": "magistral-medium-latest",
"content_length": 131072,
"max_output": 131072,
"model_types": [
"chat"
],
"tools": {
"support": true
}
},
{
"name": "magistral-small-latest",
"content_length": 131072,
"max_output": 131072,
"model_types": [
"chat"
],
"tools": {
"support": true
}
},
{
"name": "mistral-embed",
"max_tokens": 8192,
"model_types": [
"embedding"
],
"batch_size": 16
},
{
"name": "mistral-ocr-2512",
"max_tokens": 8192,
"model_types": [
"ocr"
]
}
]
}