Model
Model explorer

Galactica 120B

OPEN
Meta · Galactica family · released Nov 15, 2022

Science LLM trained on papers/code; public demo pulled after about three days over hallucination concerns.

ReasoningCodingVisionFunction callingTool useAgentic
85.9
Elo · rank #388
Parameters
120B
Active params
120B (dense)
Context
2.048K tokens
Architecture
Dense decoder-only Transformer trained on scientific papers, code, and reference material
License
CC-BY-NC 4.0
Languages
API price (in/out)
No hosted API
Modalities
text
Benchmark results
Bar shows position within the tracked field; marker = field best
ARC-ChallengeReasoning67.9%#58
best: Llama 3.1 405B · 96.9%
ARC-EasyReasoning83.8%#16
best: Phi-3-medium (14B) · 97.7%
BIG-benchReasoning48.7%#4
best: Chinchilla · 65.1%
MATH-500Math20.4%#181
best: GPT-5 · 99.4%
MMLU: AnatomyKnowledge58.5%#2
best: Palmyra Med 70B · 83.7%
MMLU: Clinical KnowledgeKnowledge59.2%#2
best: Palmyra Med 70B · 90.9%
MMLU: Medical GeneticsKnowledge68.0%#2
best: Palmyra Med 70B · 94.0%
MMLUKnowledge41.3%#256
best: OpenAI o3 · 92.9%
PubMedQAKnowledge77.6%#3
best: Palmyra Med 70B · 79.6%
TruthfulQAKnowledge26.0%#107
best: Phi-3.5-MoE (16x3.8B, 6.6B active) · 77.5%
Run it locally
VRAM @ Q4
64 GB
VRAM @ FP16
240 GB
Fits on (Q4)
M3 Max 128GBM3 Ultra 512GBA100 80GBH100 80GBH200 141GBB200 192GB
llama.cpp does not support the Galactica architecture; only bitsandbytes INT8/FP16 loading is documented, and even that exceeds a single RTX 4090's VRAM.
Quantizations
bitsandbytes INT8
Galactica family
Elo progression across releases
API price weights · each benchmark row carries its own source badge (see methodology)