2026-05-18 17:10:36 -10:00
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{
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"name": "Replicate",
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2026-07-03 18:27:32 +08:00
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"rank": 981,
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2026-05-18 17:10:36 -10:00
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"url": {
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"default": "https://api.replicate.com"
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},
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"url_suffix": {
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"chat": "v1/predictions",
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"models": "v1/models"
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},
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"class": "replicate",
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"models": [
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2026-06-11 15:08:33 +08:00
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{
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"name": "meta/llama-4-maverick-instruct",
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2026-08-05 15:22:57 +08:00
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"content_length": 1048576,
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"max_output": 131072,
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2026-06-11 15:08:33 +08:00
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"model_types": [
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"chat"
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]
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},
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{
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"name": "meta/llama-4-scout-instruct",
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2026-08-05 15:22:57 +08:00
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"content_length": 10485760,
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"max_output": 131072,
|
2026-06-11 15:08:33 +08:00
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"model_types": [
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"chat"
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]
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},
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2026-05-18 17:10:36 -10:00
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{
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"name": "meta/meta-llama-3-70b-instruct",
|
2026-08-05 15:22:57 +08:00
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"content_length": 8000,
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"max_output": 8000,
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2026-05-18 17:10:36 -10:00
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"model_types": [
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"chat"
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]
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},
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{
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"name": "meta/meta-llama-3-8b-instruct",
|
2026-08-05 15:22:57 +08:00
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"content_length": 8000,
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"max_output": 8000,
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2026-05-18 17:10:36 -10:00
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"model_types": [
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"chat"
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]
|
2026-05-21 10:11:56 +03:00
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},
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{
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"name": "replicate/all-mpnet-base-v2:b6b7585c9640cd7a9572c6e129c9549d79c9c31f0d3fdce7baac7c67ca38f305",
|
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"max_tokens": 384,
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"model_types": [
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"embedding"
|
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
|
|
|
],
|
|
|
|
|
"batch_size": 16
|
2026-05-27 09:07:00 +03:00
|
|
|
},
|
|
|
|
|
{
|
2026-06-11 15:08:33 +08:00
|
|
|
"name": "ibm-granite/granite-embedding-278m-multilingual:1f76d42a05f120e12272746d5a2d86b525c13420773f795a4cbef9117d8685f1",
|
|
|
|
|
"max_tokens": 512,
|
2026-05-27 09:07:00 +03:00
|
|
|
"model_types": [
|
2026-06-11 15:08:33 +08:00
|
|
|
"embedding"
|
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
|
|
|
],
|
|
|
|
|
"batch_size": 16
|
2026-05-18 17:10:36 -10:00
|
|
|
}
|
|
|
|
|
]
|
|
|
|
|
}
|