01.AI · Yi 1.5

Yi 1.5 9B Chat

Yi 1.5 9B Chat is a 9B chat and text-generation model available through supported Badgr execution routes.

Last validated or meaningfully updated: 2026-07-27

ChatLong contextFine-tunable

Availability

✓ Badgr AI API

Available through Badgr

Not yet Dedicated endpoint

Not currently validated

Not yet Custom GPU deployment

Not currently validated

Deployment profile

Architecture
LlamaForCausalLM
Licence
Apache-2.0
Minimum VRAM
~22GB
Context
32K tokens

Recommended: RTX 4090 24GB. VRAM is an estimate and increases with context, cache, concurrency, and runtime overhead.

Model identity

Updated
2 years ago
HuggingFace revision
1a0fc698cf

Popularity and trust

Downloads (last month)

17.8K

Likes

149

Spaces using this model

77

Files and formats

Weight formats

Safetensors

Repository files

15

Tokenizer

SentencePiece

Chat template

Available

GPU deployment scenarios

Estimated from parameter count and quantisation. Will switch to “Verified by Badgr” once a real run backs a tier.

Testing

RTX 4090 24GB

Short context, low concurrency

Small production

L40S 48GB

8K context, 1-4 concurrent requests

Higher throughput

A100 80GB

32K context, continuous batching

Large production

RTX 4090 24GB

Higher concurrency

Estimated — multimodal inputs, long context, and concurrency all increase real VRAM use beyond this estimate.

Also runs well on L40S 48GB, A100 40GB. Available in United States, Europe.

Serving compatibility

RuntimeStatusNotes
vLLMEstimatedUsed for Badgr dedicated endpoints
TransformersDeclared by sourceBasic fallback
llama.cppRequires GGUF conversionNo GGUF weights found in repo
SGLangUnknownNot evaluated
OllamaUnknownNot evaluated
DiffusersUnknownNot evaluated
PyTorchUnknownNot evaluated
TensorRT-LLMUnknownConversion may be required
TGIUnknownNot evaluated

Call this model through Badgr

curl https://aibadgr.com/v1/chat/completions \
  -H "Authorization: Bearer $BADGR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"01-ai/Yi-1.5-9B-Chat","messages":[{"role":"user","content":"Hello"}]}'

Estimated pricing

Provider estimate: cold start

2–5 min

Provider estimate: endpoint cost

$0.18 – $0.45/hr

Idle cost

$0 when stopped

Per-token throughput cost is not shown here: Badgr has not benchmarked this model yet, and this page does not display figures it cannot back with real data.

Recommended Badgr routes

RTX 4090 24GB · United States

Available

from $0.18/hr

24GB VRAM/GPU16GB RAM1440.9GB storage0.02Gbps networkCUDA 13.2

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · United States

Available

from $0.39/hr

48GB VRAM/GPU48 vCPU31.2GB RAM1625GB storage0.65Gbps networkCUDA 13.2

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · United States

Available

from $0.42/hr

2x GPU24GB VRAM/GPUSame host32 vCPU62.7GB RAM785GB storage0.01Gbps networkCUDA 13.0

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · United States

Available

from $0.43/hr

2x GPU24GB VRAM/GPUSame host8 vCPU31.3GB RAM704GB storage0.81Gbps networkCUDA 13.2

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · United States

Available

from $0.44/hr

24GB VRAM/GPU

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · United States

Available

from $0.45/hr

2x GPU24GB VRAM/GPUSame host20 vCPU62.6GB RAM1360GB storage0.08Gbps networkCUDA 12.2

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

Known limitations

  • Memory use increases with context length and concurrency.

Related troubleshooting