Can Hermes 4.3 36B run on RTX 4080 Super 16GB?

NO — Won't Fit

F0Won't run

Estimated from fit model

Hermes 4.3 36B needs ~29.0 GB but RTX 4080 Super 16GB only has 16.0 GB. Try a smaller quantization or lighter model.

Runtime: OllamaCapacity: No fitBandwidth: MediumStack: BasicBottleneck: Memory capacity

Operating mode

Choose the run profile you care about

Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.

Current mode

Balanced

Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.

Capabilities:

Select quantization to explore

Q4_K_M (Medium quality) — 29.0 GB, exceeds 16.0 GB available

29.0 GB required16.0 GB available

181% VRAM needed

13.0 GB over capacity — needs offload or smaller quantization

Fit status

Too heavy

Decode

6.0 tok/s

TTFT

32399 ms

Safe context

Memory

29.0 GB / 16.0 GB

Offload

40%

Memory breakdown

Weights22.0 GB

KV Cache4.2 GB

Runtime1.2 GB

Headroom1.6 GB

See how fast it feels

With memory offload — actual speed may be lower

See how fast it feelsHermes 4.3 36B on RTX 4080 Super 16GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.

Given information:
  - Speed = 60 mph (miles per hour)
  - Time  = 2.5 hours

Formula: Distance = Speed x Time

Calculation:
  Distance = 60 mph x 2.5 h
           = 150 miles

The train travels 150 miles.

Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.

Breakdown:
  - First half: 1.25 hours at 60 mph = 75 miles
  - Stop: 20 minutes (no distance)
  - Second half: 1.25 hours at 60 mph = 75 miles

Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph

The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 6.0 tok/s decode · 32.4s TTFT (warm) · 15 tok/s prefill

What limits this setup

Usable VRAM is the main blocker for this model.

Not enough usable memory

The model needs 29.0 GB, but this setup only exposes 16.0 GB of usable VRAM.

Best improvement path

Add more VRAM headroom

The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.

Performance by workload

Workload	Grade	Fit	Decode	TTFT	Context
Chat	F	Too heavy	7.0 tok/s	15073 ms	4K
Coding	F	Too heavy	6.0 tok/s	32399 ms	4K
Agentic Coding	F	Too heavy	4.5 tok/s	62734 ms	4K
Reasoning	F	Too heavy	6.0 tok/s	38289 ms	4K
RAG	F	Too heavy	4.5 tok/s	78417 ms	4K

Inference speed

Hermes 4.3 36B inference speed — tokens per second by GPU & Mac

Estimated decode speed (tokens/sec) for Hermes 4.3 36B at Q4_K_M across popular GPUs and Apple Silicon, including multi-GPU rigs, using the fastest local runtime per device. Fastest is RTX 5090 32GB at ~55 tok/s. Speed is memory-bandwidth bound, so cards that fit the whole model in VRAM run far faster than ones that offload to system RAM.

GPU / Mac	Memory	Quant	Speed (tok/s)	Fits?
RTX 5090 32GB	32 GB	Q4_K_M	54.7	Offloads
2× RX 7900 XTX 24GB	48 GB	Q4_K_M	53.5	Fits
2× RTX 4090 24GB	48 GB	Q4_K_M	28.1	Fits
MacBook Pro M4 Max 128GB	128 GB	Q4_K_M	27.3	Fits
MacBook Pro M4 Max 64GB	64 GB	Q4_K_M	27.3	Fits
2× RTX 3090 24GB	48 GB	Q4_K_M	25.8	Fits
Mac Studio M3 Ultra 256GB	256 GB	Q4_K_M	25.4	Fits
4× RTX 3060 12GB	48 GB	Q4_K_M	22.7	Fits
Mac Studio M2 Ultra 128GB	128 GB	Q4_K_M	21.1	Fits
Mac Studio M1 Ultra 128GB	128 GB	Q4_K_M	20.0	Fits
MacBook Pro M4 Pro 48GB	48 GB	Q4_K_M	17.2	Tight
RTX 4090 24GB	24 GB	Q4_K_M	16.6	Too big
RX 7900 XTX 24GB	24 GB	Q4_K_M	15.3	Too big
RTX 3090 24GB	24 GB	Q4_K_M	14.2	Too big
MacBook Pro M3 Max 64GB	64 GB	Q4_K_M	10.9	Fits
MacBook Pro M1 Max 64GB	64 GB	Q4_K_M	10.0	Fits
RTX 4080 Super 16GB	16 GB	Q4_K_M	6.0	Too big
RTX 4070 12GB	12 GB	Q4_K_M	2.6	Too big
RTX 3060 12GB	12 GB	Q4_K_M	2.0	Too big
RTX 4060 8GB	8 GB	Q4_K_M	2.0	Too big

Estimates for single-stream decoding at Q4_K_M; real tokens/sec varies with prompt length, context, batch size, and runtime build. Prompt processing (prefill) is faster than the decode figures shown here.

Quantization options

How Hermes 4.3 36B (36B params) fits at each quantization level on RTX 4080 Super 16GB (16.0 GB usable).

Quant	Bits	VRAM	Quality	Fit
Q2_K	2	14.0 GB	Low	F0
Q3_K_S	3	17.6 GB	Low	F0
NVFP4	4	20.2 GB	Medium	F0
Q4_K_M	4	22.0 GB	Medium	F0
Q5_K_M	5	25.9 GB	High	F0
Q6_K	6	29.5 GB	High	F0
Q8_0	8	38.5 GB	Very High	F0
F16	16	73.8 GB	Maximum	F0

Opciones de mejora

Hardware que ejecuta bien Hermes 4.3 36B

RTX 5090 32GBOpción económica

32 GB VRAM (+16)1792 GB/s (+1056)

Hace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.54.7 tok/s decodificación

Hace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.

Elimina el offload a memoria del sistema, que suele ser la mayor mejora individual en latencia y throughput.

~$1,999 MSRP

RTX PRO 4500 Blackwell 32GBMejor relación calidad-precio

32 GB VRAM (+16)896 GB/s (+160)

Hace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.34.3 tok/s decodificación

Hace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.

Elimina el offload a memoria del sistema, que suele ser la mayor mejora individual en latencia y throughput.

~$2,499 MSRP

RTX 5000 Ada 32GBMejora NVIDIA

32 GB VRAM (+16)

Hace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.21 tok/s decodificación

Hace que el modelo quepa en el acelerador en lugar de seguir fuera de alcance.

Elimina el offload a memoria del sistema, que suele ser la mayor mejora individual en latencia y throughput.

~$4,000 MSRP

Frequently asked questions

Can RTX 4080 Super 16GB run Hermes 4.3 36B?

No, Hermes 4.3 36B requires more memory than RTX 4080 Super 16GB provides.

How much VRAM does Hermes 4.3 36B need?

Hermes 4.3 36B (36B parameters) requires approximately 29.0 GB of memory with Q4_K_M quantization.

What is the best quantization for Hermes 4.3 36B?

The recommended quantization for Hermes 4.3 36B is Q4_K_M, which balances quality and memory efficiency.

What speed will Hermes 4.3 36B run at on RTX 4080 Super 16GB?

On RTX 4080 Super 16GB, Hermes 4.3 36B achieves approximately 6.0 tokens per second decode speed with a time-to-first-token of 32399ms using Q4_K_M quantization.

Can RTX 4080 Super 16GB run Hermes 4.3 36B for coding?

For coding workloads, Hermes 4.3 36B on RTX 4080 Super 16GB receives a F grade with 6.0 tok/s and 4K context.

What context window can Hermes 4.3 36B use on RTX 4080 Super 16GB?

On RTX 4080 Super 16GB, Hermes 4.3 36B can safely use up to 4K tokens of context. The model's official context limit is —, but available memory constrains the safe maximum.

What should I upgrade first if Hermes 4.3 36B feels slow on RTX 4080 Super 16GB?

Add more VRAM headroom. The first useful upgrade is more dedicated VRAM so you can fit the model without shrinking context or dropping to a much lower quant.

See all results for RTX 4080 Super 16GB See all hardware for Hermes 4.3 36B

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