Can Command R+ 104B run on NVIDIA H800 80GB?

YES — Tight Fit

B69Good
Estimated from fit model

Command R+ 104B needs ~75.8 GB VRAM. NVIDIA H800 80GB has 80.0 GB. With Q4_K_M quantization, expect ~42 tok/s.

Runtime: llama.cppCapacity: TightBandwidth: HighStack: StandardBottleneck: Balanced
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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) 75.8 GB, 41.7 tok/s, Tight fit
75.8 GB required80.0 GB available
95% VRAM used

Fit status

Tight fit

Decode

41.7 tok/s

TTFT

4648 ms

Safe context

36K

Memory

75.8 GB / 80.0 GB

Memory breakdown

Weights63.4 GB
KV Cache3.4 GB
Runtime0.9 GB
Headroom8.0 GB

See how fast it feels

See how fast it feelsCommand R+ 104B on NVIDIA H800 80GB
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: 41.7 tok/s decode · 4.6s TTFT (warm) · 104 tok/s prefill

What limits this setup

This setup is broadly balanced for this model.

Very little memory headroom

You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.

Best improvement path

Buy headroom, not only minimum fit

A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

Performance by workload

WorkloadGradeFitDecodeTTFTContext
ChatBTight fit41.7 tok/s2535 ms36K
CodingBTight fit41.7 tok/s4648 ms36K
Agentic CodingBRuns with offload41.7 tok/s6760 ms36K
ReasoningBTight fit41.7 tok/s5493 ms36K
RAGBRuns with offload41.7 tok/s8450 ms36K

Quantization options

How Command R+ 104B (104B params) fits at each quantization level on NVIDIA H800 80GB (80.0 GB usable).

QuantBitsVRAMQualityFit
Q2_K
2
40.6 GB
LowB65
Q3_K_S
3
51.0 GB
LowB65
NVFP4
4
58.2 GB
MediumB65
Q4_K_MBest for your GPU
4
63.4 GB
MediumB65
Q5_K_M
5
74.9 GB
HighF0
Q6_K
6
85.3 GB
HighF0
Q8_0
8
111.3 GB
Very HighF0
F16
16
213.2 GB
MaximumF0

Get started

Copy-paste commands to run Command R+ 104B on your machine.

Run

ollama run command-r-plus

アップグレードオプション

Command R+ 104Bを快適に動かすハードウェア

Frequently asked questions

Can NVIDIA H800 80GB run Command R+ 104B?

Yes, NVIDIA H800 80GB can run Command R+ 104B with a B grade (Tight fit). Expected decode speed: 41.7 tok/s.

How much VRAM does Command R+ 104B need?

Command R+ 104B (104B parameters) requires approximately 75.8 GB of memory with Q4_K_M quantization.

What is the best quantization for Command R+ 104B?

The recommended quantization for Command R+ 104B is Q4_K_M, which balances quality and memory efficiency.

What speed will Command R+ 104B run at on NVIDIA H800 80GB?

On NVIDIA H800 80GB, Command R+ 104B achieves approximately 41.7 tokens per second decode speed with a time-to-first-token of 4648ms using Q4_K_M quantization.

Can NVIDIA H800 80GB run Command R+ 104B for coding?

For coding workloads, Command R+ 104B on NVIDIA H800 80GB receives a B grade with 41.7 tok/s and 36K context.

What context window can Command R+ 104B use on NVIDIA H800 80GB?

On NVIDIA H800 80GB, Command R+ 104B can safely use up to 36K tokens of context. The model's official context limit is 131K, but available memory constrains the safe maximum.

What should I upgrade first if Command R+ 104B feels slow on NVIDIA H800 80GB?

Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.

See all results for NVIDIA H800 80GBSee all hardware for Command R+ 104B
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