Model
Model explorer
Guanaco 33B
OPENUniversity of Washington (Dettmers et al.) · Guanaco family · released May 23, 2023
QLoRA 4-bit finetune of LLaMA-33B on OASST1 that reached 97.8% of ChatGPT's Vicuna-benchmark quality (second-best in the paper, after the 65B model's 99.3%) after roughly 12 hours on a single 24GB consumer GPU.
ReasoningCodingVisionFunction callingTool useAgentic
280.6
Elo · rank #350
Parameters
33B
Active params
33B (dense)
Context
2K tokens
Architecture
Dense decoder-only transformer (LLaMA-33B base) with 4-bit QLoRA adapter finetune
License
Apache-2.0 (LoRA adapter); base LLaMA-33B weights under Meta's non-commercial research license
Languages
—
API price (in/out)
No hosted API
Modalities
text
Benchmark results
Bar shows position within the tracked field; marker = field best
best: Llama 3.1 405B · 96.9%
best: Claude Fable 5 · 1505
best: Claude 3 Opus · 95.4%
best: OpenAI o3 · 92.9%
best: Hunyuan-Large (A52B) · 9.4
best: GPT-4 · 1294
best: Phi-3.5-MoE (16x3.8B, 6.6B active) · 77.5%
best: GPT-4 · 1176
Run it locally
VRAM @ Q4
21 GB
VRAM @ FP16
66 GB
Fits on (Q4)
RTX 3090 24GBRTX 4090 24GBRTX 5090 32GBM4 Pro 48GBM3 Max 128GBM3 Ultra 512GBA100 80GBH100 80GBH200 141GBB200 192GB
Throughput data unavailable.
Quantizations
GGUF Q4 · GPTQ · AWQ
API price weights · each benchmark row carries its own source badge (see methodology)