Model
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Nous Hermes 2 Mixtral 8x7B DPO

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Nous Research · Hermes family · released Jan 15, 2024

Flagship MoE fine-tune of Mixtral 8x7B, SFT+DPO on 1M+ mostly GPT-4-generated samples; first community model to beat Mixtral Instruct broadly.

ReasoningCodingVisionFunction callingTool useAgentic
474.1
Elo · rank #314
Parameters
46.7B
Active params
12.9B (MoE)
Context
32K tokens
Architecture
Sparse Mixture-of-Experts transformer (8 experts, top-2 routing, Mixtral architecture)
License
Apache-2.0
Languages
API price (in/out)
No hosted API
Modalities
text
Benchmark results
Bar shows position within the tracked field; marker = field best
AGIEvalReasoning46.0%#24
best: OLMo 3-Think 32B · 88.2%
ARC-ChallengeReasoning64.3%#68
best: Llama 3.1 405B · 96.9%
ARC-EasyReasoning86.4%#11
best: Phi-3-medium (14B) · 97.7%
BIG-benchReasoning49.7%#3
best: Chinchilla · 65.1%
GSM8KMath71.7%#98
best: Llama 3.1 405B · 96.8%
HellaSwagReasoning84.9%#43
best: Claude 3 Opus · 95.4%
MMLUKnowledge72.2%#135
best: OpenAI o3 · 92.9%
OpenBookQAReasoning46.6%#33
best: Claude 1 · 90.8%
PIQAReasoning83.8%#13
best: GPT-4o mini · 93.1%
TruthfulQAKnowledge54.8%#37
best: Phi-3.5-MoE (16x3.8B, 6.6B active) · 77.5%
WinoGrandeReasoning76.2%#56
best: PaLM 2 · 90.9%
Run it locally
VRAM @ Q4
30 GB
VRAM @ FP16
93 GB
Fits on (Q4)
M4 Pro 48GBM3 Max 128GBM3 Ultra 512GBA100 80GBH100 80GBH200 141GBB200 192GB
Throughput data unavailable.
Quantizations
GGUF Q4_K_M · GPTQ · AWQ
API price weights · each benchmark row carries its own source badge (see methodology)