👁 UC Berkeley
UC Berkeley
Starling LM 7B
Legacy
1.9KDownloads560LikesNov 2023Released8K tokensContextApache 2.0License5 EntryQuality
Starling LM 7B (7B parameters) requires approximately 8.0 GB of VRAM with Q4_K_M quantization. For the best balance of quality and speed, we recommend hardware with at least 10 GB of VRAM.
Get started
— copy & paste to run locallyCopy-paste commands to run Starling LM 7B on your machine.
Run
ollama run starling-lmQuick specs
Parameters7B
Architecturedense
Context8K tokens
Modalitytext
Min RAM2.7 GB
Rec. RAM4.3 GB (Q4_K_M)
LicenseApache 2.0
FamilyStarling
✓ Chat
About this model
- •Developed by:: Banghua Zhu * , Evan Frick * , Tianhao Wu * , Hanlin Zhu and Jiantao Jiao
- •Model type:: Language Model finetuned with RLHF / RLAIF
- •License:: Apache-2.0 license under the condition that the model is not used to compete with OpenAI
- •Finetuned from model:: Openchat 3.5 (based on Mistral-7B-v0.1)
Your hardware
Detecting...
Quick picks
Best hardware
Top picks for Starling LM 7B
Run this model
Quantization options
VRAM estimates by quant level
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | — |
Q3_K_S | 3 | 3.4 GB | Low | — |
NVFP4 | 4 | 3.9 GB | Medium | — |
Q4_K_M | 4 | 4.3 GB | Medium | — |
Q5_K_M | 5 | 5.0 GB | High | — |
Q6_K | 6 | 5.7 GB | High | — |
Q8_0 | 8 | 7.5 GB | Very High | — |
F16 | 16 | 14.3 GB | Maximum | — |
Quality benchmarks
Starling LM 7B benchmark scores
Reasoning
MMLU-Pro24.1%
GPQA Diamond6.3%
MATH-5008.4%
ARC Challenge—
General
Chatbot Arena—
IFEval54.8%
Source: community · 2025-01-01
Hardware compatibility
Fit estimates across all hardware
Computing compatibility...
Memory breakdown
Reference: RTX 2060 6GB
Weights4.3 GB
KV Cache2.0 GB
Runtime1.2 GB
Headroom0.6 GB
Frequently asked questions
FAQ — Starling LM 7B
See also