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Nous ResearchDense

Hermes 4 70B RAM Calculator

For Hermes 4 70B, plan about 64GB system RAM at Q4_K_M / 8K context for this 70B dense large model (131K-token window). Hermes 4 70B weights are available for local runtimes (llama.cpp / Ollama / vLLM class stacks) β€” buy kits you can fill with dual-channel DDR5 (or ECC RDIMM on true workstations).

Hermes 4 70B is a hybrid reasoning model from Nous Research, built on Meta-Llama-3.1-70B. It introduces the same hybrid mode as the larger 405B release, allowing the model to either...

Standard Recommendation

64GB RAM

Calculated for 4-bit (Q4_K_M) @ 8K Context

1. Workload

Inference sizes run-time memory. Training adds optimizer/activation headroom and steers toward ECC.

2. Hardware path

CPU + RAM offload path: full model weights reside in system RAM (llama.cpp / similar). Dual-channel DDR5 bandwidth is the speed bottleneck.

3. Quantization

GGUF-style bit widths for planning. Native FP4/FP8 trainer footprints can differ.

4. Context length

Grows KV cache (inference) or activation scratch (training ballpark).

8,192 tokens

Inference bandwidth snapshot

DDR4 ~45 GB/s

1.1 t/s

DDR5 ~96 GB/s

2.4 t/s

Unified ~300 GB/s

7.6 t/s

VRAM ~1008 GB/s

25.6 t/s

Host RAM target

64GB

Inference Β· CPU offload Β· Q4 K_M

Model weights:39.4 GB
KV cache:0.17 GB
OS / runtime:6 GB
Host total:45.6 GB

Kit picks (64GB)

Disclosure: As an Amazon Associate I earn from qualifying purchases. Rankings use price and spec data only β€” not paid placement. How we rank products

A-Tech 64GB (2x32GB) DDR4 2666 MHz UDIMM PC4-21300 (PC4-2666V) CL19 DIMM 2Rx8 Non-ECC Desktop RAM Memory Modules

UDIMMECC2-stick kit
$426.78$6.67/GBIn stock

Best match for dual-channel desktop boards (populate the recommended slots).

CORSAIR DOMINATOR PLATINUM RGB DDR5 RAM 64GB (2x32GB) 5600MHz CL40 Intel XMP iCUE Compatible Computer Memory - White (CMT64GX5M2B5600C40W)

UDIMM2-stick kit
$969.99$15.16/GBIn stock

Best match for dual-channel desktop boards (populate the recommended slots).

CORSAIR Dominator Platinum RGB DDR5 RAM 64GB (2x32GB) 5600MHz CL40 Intel XMP iCUE Compatible Computer Memory - Black (CMT64GX5M2X5600C40)

UDIMM2-stick kit
$1098.97$17.17/GBIn stock

Best match for dual-channel desktop boards (populate the recommended slots).

G.SKILL Trident Z5 Neo RGB Series DDR5 RAM (AMD EXPO) 64GB (2x32GB) 6000MT/s CL30-40-40-96 1.40V Desktop Computer Memory U-DIMM - Matte Black (F5-6000J3040G32GX2-TZ5NR)

UDIMM2-stick kit
$999.99$15.62/GBIn stock

Best match for dual-channel desktop boards (populate the recommended slots).

A-Tech 64GB (4x16GB) DDR4 2400 MHz UDIMM PC4-19200 (PC4-2400T) CL17 DIMM 2Rx8 Non-ECC Desktop RAM Memory Modules

UDIMMECC4-stick kit
$384.16$6.00/GBIn stock

Four sticks can stress the memory controller and lower stable XMP speeds on many consumer boards.

Confirm motherboard QVL / max capacity per slot before buying.

G.SKILL Ripjaws DDR5 SO-DIMM Series DDR5 RAM 64GB (2x32GB) 5600MT/s CL40-40-40-89 1.10V Unbuffered Non-ECC Notebook/Laptop Memory SO-DIMM (F5-5600S4040A32GX2-RS)

SO-DIMMECC2-stick kit
$1049.99$16.41/GBIn stock

Laptop / mini-PC form factor β€” will not fit desktop DIMM slots.

A-Tech 64GB Kit (2x32GB) DDR5 5600MHz PC5-44800 CL46 SODIMM 2Rx8 Dual Rank 1.1V Non-ECC Unbuffered SO-DIMM 262-Pin Laptop Computer RAM Memory Upgrade Modules

SO-DIMMECC2-stick kit
$876.91$13.70/GBIn stock

Laptop / mini-PC form factor β€” will not fit desktop DIMM slots.

Why Hermes 4 70B pressures system RAM

Hermes 4 70B is a dense 70B network β€” every weight participates each token, so quantization choice dominates. Q4_K_M lands near ~39.4GB weights, plus ~0.17GB KV at 8K and ~6GB overhead (~45.6GB β†’ 64GB kit). The 131K-token context ceiling is the sleeper cost: long-doc or agent traces inflate KV while the 70B slab stays fixed. Prefer dual-channel DDR5 bandwidth when CPU offload or mmap is involved.

What RAM kit to buy

Buy a matched dual-channel DDR5 kit at 64GB for Hermes 4 70B (EXPO/XMP only if stable). Avoid single-stick installs β€” local inference is bandwidth-sensitive when layers spill to host memory. Pair with 2x RTX 3090 / RTX 4090 (48GB combined VRAM) or Mac Studio 64GB when staying in the Dual Flagship GPU Setup tier, and keep 20–30% RAM free for the OS + browser.

Workload notes

For Nous Research's Hermes 4 70B, treat published parameter counts as the weight floor and add OS + KV + runtime overhead before shopping kits. At 70B, Hermes 4 70B sits in the large local-LLM band: Q4 on a strong GPU is realistic, FP16 usually is not on consumer cards. Release window noted as 2025/2026; always re-check the model card before buying hardware for a specific checkpoint.

Technical Specifications

Total Parameter Count70 Billion
Active Parameters Per TokenDense (All active)
Maximum Context Window131K tokens
Primary Framework SupportOllama, llama.cpp, ExLlamaV2, vLLM

GPU & VRAM Sizing Profile

Dual Flagship GPU Setup
Est. VRAM Required43.4 GB VRAM
Target GPU Hardware2x RTX 3090 / RTX 4090 (48GB combined VRAM) or Mac Studio 64GB

Hardware Profile: Requires running two flagship cards in parallel (PCIe slots) to pool VRAM. Highly standard setup for 70B models.

Hermes 4 70B Memory FAQs

How much RAM for Hermes 4 70B at Q4 vs FP16?

At Q4_K_M with an 8K context we estimate ~64GB system kits for Hermes 4 70B (weights ~39.4GB). FP16 jumps to roughly a 192GB kit class and often wants 43.4GB-class VRAM instead of host RAM alone β€” use the on-page calculator to retarget context and quant.

Does Hermes 4 70B need dual-channel RAM?

Yes for local inference. Dual-channel DDR4/DDR5 (or wide LPDDR/unified memory) keeps prompt eval and CPU offload from hitching. A single stick often halves bandwidth and feels like a slow model even when capacity looks sufficient.

What GPU tier fits Hermes 4 70B?

Dual Flagship GPU Setup: target about 43.4GB VRAM (2x RTX 3090 / RTX 4090 (48GB combined VRAM) or Mac Studio 64GB). Requires running two flagship cards in parallel (PCIe slots) to pool VRAM. Highly standard setup for 70B models.

Can I run Hermes 4 70B with less than 64GB if I lower context?

Yes β€” shorter context shrinks KV (~0.17GB at 8K). Dropping to 2K–4K context can fit smaller kits, but keep OS headroom; paging kills tokens/s more than a slightly larger kit costs.

Same VRAM tier

Models that land in the same hardware profile (Dual Flagship GPU Setup) at Q4 / 8K context.