FitMyLLM
NousResearch/Mixture of Experts

NousResearchNous-Hermes-2-Mixtral-8x7B-DPO

Nous Hermes 2 Mixtral — community fine-tune of Mixtral with improved helpfulness.

chat
46.7B
Parameters (13B active)
32K
Context length
7
Benchmarks
14
Quantizations
9K
HF downloads
Architecture
MoE
Released
2024-01-11
Layers
32
KV Heads
8
Head Dim
128
Family
mistral

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
IQ3_XXS3.25
20.0 GB
19.5 + 0.5 KV
low
IQ3_XS3.5
21.4 GB
20.9 + 0.5 KV
low
Q3_K_S3.64
22.2 GB
21.7 + 0.5 KV
low
IQ3_M3.76
22.9 GB
22.4 + 0.5 KV
low
Q3_K_M4
24.3 GB
23.8 + 0.5 KV
low
Q3_K_L4.3
26.1 GB
25.6 + 0.5 KV
moderate
IQ4_XS4.46
27.0 GB
26.5 + 0.5 KV
moderate
Q4_K_S4.67
28.2 GB
27.7 + 0.5 KV
moderate
Q4_K_M4.89
29.5 GB
29.0 + 0.5 KV
good
Q5_K_S5.57
33.5 GB
33.0 + 0.5 KV
good
Q5_K_M5.7
34.3 GB
33.8 + 0.5 KV
good
Q6_K6.56
39.3 GB
38.8 + 0.5 KV
excellent
Q8_08.5
50.6 GB
50.1 + 0.5 KV
lossless
FP1616
94.4 GB
93.9 + 0.5 KV
lossless

Select your GPU above to see speed estimates and compatibility for each quantization.

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READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN NOUS-HERMES-2-MIXTRAL-8X7B-DPO NOW

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Community Ratings

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Benchmarks (7)

Arena Elo1099
IFEval59.0
BBH37.1
MMLU-PRO29.6
MUSR16.7
MATH12.2
GPQA9.5

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run nous-hermes2-mixtral:8x7b-dpo-q4_K_M

Downloads and runs automatically. Add --verbose for speed stats.

▸ SETUP GUIDE
>_

Auto-setup with fitmyllm CLI

Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.

pip install fitmyllmthen run fitmyllmLearn more
Auto-detect GPULive tok/s in chatSpeed benchmarks9 inference engines

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

Apple M1 Max (32GB)
32 GB VRAM • 400 GB/s
APPLE
$1499
Apple M2 Max (32GB)
32 GB VRAM • 400 GB/s
APPLE
$1799
NVIDIA V100 SXM2 32GB
32 GB VRAM • 900 GB/s
NVIDIA
$3500
Apple M2 Pro (32GB)
32 GB VRAM • 200 GB/s
APPLE
$1499
Apple M4 (32GB)
32 GB VRAM • 120 GB/s
APPLE
$1199
NVIDIA Tesla V100 DGXS 32 GB
32 GB VRAM • 897 GB/s
NVIDIA
NVIDIA Tesla V100 PCIe 32 GB
32 GB VRAM • 897 GB/s
NVIDIA
NVIDIA Tesla V100 SXM2 32 GB
32 GB VRAM • 898 GB/s
NVIDIA
NVIDIA Tesla V100 SXM3 32 GB
32 GB VRAM • 981 GB/s
NVIDIA
AMD Radeon Instinct MI60
32 GB VRAM • 1020 GB/s
AMD
NVIDIA Tesla V100S PCIe 32 GB
32 GB VRAM • 1130 GB/s
NVIDIA
AMD Radeon Instinct MI100
32 GB VRAM • 1230 GB/s
AMD
$5000
NVIDIA Tesla PG500-216
32 GB VRAM • 1130 GB/s
NVIDIA
NVIDIA Tesla PG503-216
32 GB VRAM • 1130 GB/s
NVIDIA

Find the best GPU for Nous-Hermes-2-Mixtral-8x7B-DPO

Build Hardware for Nous-Hermes-2-Mixtral-8x7B-DPO

Nous Hermes 2 Mixtral — community fine-tune of Mixtral with improved helpfulness.

▸ SPEC SHEET

Nous-Hermes-2-Mixtral-8x7B-DPO46.7B MoE.

▸ SPECIFICATIONS
PARAMETERS
46.7B (13B active)
ARCHITECTURE
Mixture of Experts
CONTEXT LENGTH
32K tokens
CAPABILITIES
chat
RELEASE DATE
2024-01-11
PROVIDER
NousResearch
FAMILY
mistral
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
IQ3_XXS3.2519.5 GB82%
IQ3_XS3.520.9 GB84%
Q3_K_S3.6421.7 GB85%
IQ3_M3.7622.4 GB86%
Q3_K_M423.8 GB88%
Q3_K_L4.325.6 GB90%
IQ4_XS4.4626.5 GB92%
Q4_K_S4.6727.7 GB93%
Q4_K_M4.8929.0 GB94%
Q5_K_S5.5733.0 GB96%
Q5_K_M5.733.8 GB96%
Q6_K6.5638.8 GB97%
Q8_08.550.1 GB100%
FP161693.9 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO29.6
MATH12.2
IFEval59.0
BBH37.1
GPQA9.5
MUSR16.7
Arena Elo1099.0
§ 02RUN COMMAND

Run Nous-Hermes-2-Mixtral-8x7B-DPO locally with Ollama — needs 29.0 GB VRAM at Q4_K_M:

$ollama run nous-hermes2-mixtral:8x7b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M