Meta Llama 3

Llama 3.1 8B Instruct hardware requirements

Fits on one Instinct MI350X OAM at BF16. For 1,000 tokens/s at 32k context you need 4 x H100 SXM5 80GB at $7.16/hr or 4 x RTX PRO 6000 Blackwell Max-Q Workstation Edition at $2.00/hr.

Parameters
8.0B
Active per token
All
dense model
KV cache per token
128 KB
16-bit cache
Native precision
BF16

Bare minimum

Fewest GPUs
1 x Instinct MI350X OAM
BF16, 4,096 tokens, one stream
Tokens/s
362
Per hour
$6.16
Per million tokens
$4.73
Memory used
6%
Rent on DigitalOcean
Cheapest per hour
1 x RTX A5000 24GB
BF16, 4,096 tokens, one stream, live price
Tokens/s
34.7
Per hour
$0.27
Per million tokens
$2.16
Memory used
75%
Rent on RunPod
Cheapest per million tokens
2 x RTX PRO 6000 Blackwell Max-Q Workstation Edition
BF16, 32,768 tokens, 32 streams
Tokens/s
532
Per hour
$1.00
Per million tokens
$0.52
Memory used
84%
Rent on RunPod

Configurations

Every datacenter GPU in the catalog, sized for these settings. Change precision, context and concurrency and the whole page follows. Each point is one replica: the smallest tensor-parallel group of that GPU that holds the model.

Vendor

1 x GB300 NVL72 GPU 288GB: 1.3k tokens/s per replica at $8.62/hr.1 x GB200 NVL72 GPU 186GB: 1.3k tokens/s per replica at $10.50/hr.1 x Instinct MI350X OAM: 1.3k tokens/s per replica at $6.16/hr.1 x B300 SXM 262GB: 1.3k tokens/s per replica at $7.40/hr.1 x B200 SXM 180GB: 1.2k tokens/s per replica at $4.09/hr.1 x Instinct MI325X OAM: 938 tokens/s per replica at $3.80/hr.1 x Instinct MI300X 192GB: 829 tokens/s per replica at $2.39/hr.2 x H200 SXM 141GB: 1.4k tokens/s per replica at $5.98/hr.4 x H100 SXM5 80GB: 1.9k tokens/s per replica at $7.16/hr.2 x H200 NVL 141GB: 1.4k tokens/s per replica at $7.58/hr.2 x H100 NVL 94GB: 1.2k tokens/s per replica at $6.38/hr.4 x H100 PCIe 80GB: 1.1k tokens/s per replica at $10.00/hr.2 x RTX PRO 6000 Blackwell Workstation Edition: 532 tokens/s per replica at $3.60/hr.2 x RTX PRO 6000 Blackwell Server Edition: 474 tokens/s per replica at $1.18/hr.2 x RTX PRO 6000 Blackwell Max-Q Workstation Edition: 532 tokens/s per replica at $1.00/hr.8 x GeForce RTX 5090 32GB: 1.9k tokens/s per replica at $7.92/hr.4 x RTX 6000 Ada 48GB: 540 tokens/s per replica at $3.36/hr.4 x L40S 48GB: 486 tokens/s per replica at $3.48/hr.4 x A100 PCIe 80GB: 1.1k tokens/s per replica at $5.40/hr.4 x A100 SXM4 80GB: 1.1k tokens/s per replica at $5.60/hr.8 x A100 SXM4 40GB: 1.7k tokens/s per replica at $10.32/hr.8 x RTX 5000 Ada 32GB: 612 tokens/s per replica at $6.64/hr.4 x RTX PRO 5000 Blackwell 48GB: 756 tokens/s per replica at $3.84/hr.8 x RTX PRO 4500 Blackwell 32GB: 953 tokens/s per replica at $5.76/hr.4 x L40 48GB: 486 tokens/s per replica at $3.28/hr.8 x GeForce RTX 4090 24GB: 1.1k tokens/s per replica at $4.80/hr.8 x A30 24GB: 992 tokens/s per replica at $5.86/hr.4 x RTX A6000 48GB: 432 tokens/s per replica at $2.00/hr.4 x A40 48GB: 392 tokens/s per replica at $1.96/hr.8 x RTX PRO 4000 Blackwell 24GB: 714 tokens/s per replica at $4.56/hr.8 x V100S PCIe 32GB: 1.2k tokens/s per replica at $7.04/hr.8 x A10 24GB: 638 tokens/s per replica at $10.32/hr.8 x L4 24GB: 319 tokens/s per replica at $3.92/hr.8 x GeForce RTX 3090 24GB: 995 tokens/s per replica at $4.00/hr.8 x GeForce RTX 3090 Ti 24GB: 1.1k tokens/s per replica at $3.68/hr.8 x RTX A5000 24GB: 817 tokens/s per replica at $2.16/hr.

Priced configurations only; 37 more fit without a live price and appear in the table. Marker size grows with the tensor-parallel width. Roofline estimates.

GPUTPTokens/s
1 ~3.6k Specs
1 3.4k Specs
1 1.3k Specs
1 1.3k Rent
1 1.3k Rent
1 1.3k Rent
1 1.3k Rent
1 1.2k Rent
1 1.3k Specs
1 938 Rent
1 829 Rent
4 901 Specs
2 1.4k Rent
4 1.9k Rent
2 973 Specs
2 ~1.4k Rent
2 ~1.2k Rent
4 1.1k Rent
4 1.1k Specs
2 532 Rent
2 ~474 Rent
2 532 Rent
4 692 Specs
8 1.9k Rent
2 973 Specs
4 ~540 Rent
2 973 Specs
4 486 Rent
4 1.1k Specs
4 1.1k Rent
4 1.1k Rent
8 1.7k Specs
8 1.7k Rent
8 ~1.4k Specs
4 ~540 Specs
8 ~612 Rent
4 ~756 Rent
4 ~756 Specs
8 ~953 Rent
8 680 Specs
8 1.3k Specs
8 ~646 Specs
4 486 Rent
4 922 Specs
8 1.1k Rent
8 992 Rent
8 ~459 Specs
4 432 Rent
4 392 Rent
2 1.2k Specs
2 1.2k Specs
8 ~714 Rent
8 1.3k Specs
8 ~817 Specs
8 1.2k Rent
8 638 Rent
4 486 Specs
4 486 Specs
8 1.0k Specs
8 319 Rent
4 486 Specs
8 ~646 Specs
8 ~485 Specs
8 319 Specs
8 ~459 Specs
4 486 Specs
8 612 Specs
8 995 Rent
8 638 Specs
8 1.1k Rent
8 544 Specs
8 817 Rent
8 476 Specs

AMD vs NVIDIA

At BF16 the NVIDIA pick is 2 x RTX PRO 6000 Blackwell Max-Q Workstation Edition at about 532 tokens/s for $1.00/hr; the AMD pick is 1 x Instinct MI300X 192GB at about 829 tokens/s for $2.39/hr. Per rental dollar NVIDIA delivers 1.54x the tokens of AMD here.

NVIDIA: 532 tokens/s per dollar, 887 tokens/s per kW (2 x RTX PRO 6000 Blackwell Max-Q Workstation Edition).AMD: 347 tokens/s per dollar, 1.1k tokens/s per kW (1 x Instinct MI300X 192GB).Intel: no live price, 811 tokens/s per kW (2 x Data Center GPU Max 1550 128GB).Other: no live price, 409 tokens/s per kW (4 x BR100).

NVIDIA 49 parts fit
Best value: 2 x RTX PRO 6000 Blackwell Max-Q Workstation Edition, 532 tok/s for $1.00/hr
Fewest GPUs: 1 x Rubin SXM, 3.4k tok/s
AMD 17 parts fit
Best value: 1 x Instinct MI300X 192GB, 829 tok/s for $2.39/hr
Fewest GPUs: 1 x Instinct MI455X OAM, 3.6k tok/s
Intel 5 parts fit
Fewest GPUs: 2 x Data Center GPU Max 1550 128GB, 973 tok/s
Other 2 parts fit
Fewest GPUs: 4 x BR100, 901 tok/s

Fleet what-if

Compare whole fleets at these settings: a thousand of one part against a hundred of another. Each fleet splits into replicas of its tensor-parallel width; GPUs left over sit idle.

A
B
FleetReplicasTokens/s
A 1,000 x H200 SXM 141GB 500 x TP2 713k
B 100 x GB200 NVL72 GPU 186GB 100 x TP1 125k

1,000 x H200 SXM 141GB: 713k tokens/s, $2,990/hr, 700 kW.100 x GB200 NVL72 GPU 186GB: 125k tokens/s, $1,050/hr, no power figure.

H200 SXM 141GB: 713k tokens/s at 1000 GPUs.GB200 NVL72 GPU 186GB: 1.25M tokens/s at 1000 GPUs.

Size Llama 3.1 8B Instruct for a tokens per second target

The calculator starts from your traffic instead of a fleet: set a target rate and read the replica count for every GPU.

Frequently asked questions

How much GPU memory does Llama 3.1 8B Instruct need?

The weights take 16.1 GB at the native BF16 precision (16.1 GB at BF16, 8.0 GB at FP8, 4.5 GB at INT4). Each concurrent stream adds 128 KB of KV cache per token: 0.5 GB at 4,096 tokens and 4.3 GB at 32,768 tokens.

What is the bare minimum to run Llama 3.1 8B Instruct?

1 x Instinct MI350X OAM at BF16 with 4,096 tokens of context and one stream. The cheapest live rental for that footprint is 1 x RTX A5000 24GB at $0.27 per hour.

How many H100s do you need to run Llama 3.1 8B Instruct?

one H100 at BF16 for 4,096 tokens of context and one stream. For 32,768 tokens and 32 concurrent streams the tensor-parallel group is 4 H100s, and 1,000 tokens per second takes 4 H100s across 1 replicas.

How much does Llama 3.1 8B Instruct cost per million tokens on an H100?

About $1.05 per million output tokens at BF16, 32,768 tokens of context and 32 streams, using the cheapest live on-demand price of $1.79 per GPU-hour. The cheapest part per token is 2 x RTX PRO 6000 Blackwell Max-Q Workstation Edition at $0.52.

What precision does Llama 3.1 8B Instruct ship in?

The published checkpoint is BF16. FP8 and INT4 figures describe post-training quantisations that halve and quarter the footprint at a small accuracy cost.

All figures are roofline estimates from the model's config.json and each GPU's published memory, bandwidth and tensor-core peak, with fixed efficiency factors. Prices are the cheapest live on-demand listing per GPU when the site has one. They are a planning floor; a tuned serving stack can do better. The Meta repo is gated; geometry read from the unsloth mirror, which ships the same config.