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## 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>
161 lines
2.9 KiB
JSON
161 lines
2.9 KiB
JSON
{
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"name": "CometAPI",
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"url": {
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"default": "https://api.cometapi.com"
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},
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"url_suffix": {
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"chat": "v1/chat/completions",
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"models": "api/models",
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"embedding": "v1/embeddings",
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"balance": "https://query.cometapi.com/user/quota",
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"tts": "v1/audio/speech",
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"asr": "v1/audio/transcriptions"
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},
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"class": "cometapi",
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"models": [
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{
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"name": "gpt-5.5",
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"content_length": 1050000,
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"max_output": 128000,
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"model_types": [
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"chat",
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"vision"
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],
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"thinking": {
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"default_value": true,
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"clear_thinking": true
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},
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"tools": {
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"support": true
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}
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},
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{
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"name": "gpt-5.4-mini",
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"content_length": 400000,
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"max_output": 128000,
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"model_types": [
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"chat",
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"vision"
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],
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"thinking": {
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"default_value": true,
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"clear_thinking": true
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},
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"tools": {
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"support": true
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}
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},
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{
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"name": "gpt-5",
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"content_length": 400000,
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"max_output": 128000,
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"model_types": [
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"chat",
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"vision"
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],
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"thinking": {
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"default_value": true,
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"clear_thinking": true
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},
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"tools": {
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"support": true
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}
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},
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{
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"name": "gpt-4o",
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"content_length": 128000,
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"max_output": 16384,
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"model_types": [
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"chat",
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"vision"
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],
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"tools": {
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"support": true
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}
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},
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{
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"name": "claude-sonnet-4-6",
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"content_length": 1000000,
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"max_output": 128000,
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"model_types": [
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"chat",
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"vision"
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],
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"tools": {
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"support": true
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}
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},
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{
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"name": "gemini-3-pro-preview",
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"content_length": 1048576,
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"max_output": 65536,
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"model_types": [
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"chat",
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"vision"
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],
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"tools": {
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"support": true
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}
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},
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{
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"name": "deepseek-v3.2",
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"content_length": 131072,
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"max_output": 8192,
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"model_types": [
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"chat"
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],
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"tools": {
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"support": true
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}
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},
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{
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"name": "qwen3-235b-a22b",
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"content_length": 131072,
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"max_output": 32768,
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"model_types": [
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"chat"
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],
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"tools": {
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"support": true
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}
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},
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{
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"name": "text-embedding-3-small",
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"max_tokens": 8191,
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"model_types": [
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"embedding"
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],
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"batch_size": 2048
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},
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{
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"name": "text-embedding-3-large",
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"max_tokens": 8191,
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"model_types": [
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"embedding"
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],
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"batch_size": 2048
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},
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{
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"name": "text-embedding-ada-002",
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"max_tokens": 8191,
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"model_types": [
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"embedding"
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],
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"batch_size": 2048
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},
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{
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"name": "whisper-1",
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"model_types": [
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"asr"
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]
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},
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{
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"name": "tts-1",
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"max_tokens": 8192,
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"model_types": [
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"tts"
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]
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}
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]
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}
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