AI accelerator specs

Compare memory, bandwidth, power and dense compute; each precision stays separate.

29 accelerators · 6 manufacturers · Specifications reviewed October 24, 2026.

Hardware leaders

Cheapest compute to rent

$2.29/PFLOP-hr

Instinct MI300X · Dense BF16 at $2.99/hr on demand · Hot Aisle

Most memory

432 GB

Instinct MI455X · HBM · Ramping

Highest bandwidth

23.3 TB/s

Instinct MI455X · Memory bandwidth · Ramping

Newest shipping chip

Jan 2026

Maia 200 · First availability · Microsoft

Select 2–4 accelerators to compare specifications and tracked rental prices side by side.

Chips announced but not yet in this table, with each one’s stated availability, are on the accelerator roadmap.

Compare rental cost per unit of theoretical peak compute below, at BF16 and at FP8. Actual application speed also depends on memory, software, utilization and communication between chips.

What a BF16 PFLOP-hour rents for

Cheapest on-demand list price ÷ dense BF16 throughput

Source and methodology

Rental observations October 14, 2026–October 25, 2026. Cheapest on-demand list price for each chip from any tracked provider, hyperscaler or specialist, divided by its vendor-specification dense BF16 throughput (FP32 accumulation). Exact values below identify each plotted quote's provider, class and date. TPU prices are per chip-hour; GB200 uses per-GPU rack pricing. V100 has no BF16 format and is not plotted. Capacity Block and serverless prices are separate billing models and are not plotted.

Exact values for What a BF16 PFLOP-hour rents for
What a BF16 PFLOP-hour rents for — exact values in tabular form
Chip$/PFLOP·hrRental $/hrDense BF16ProviderClassObserved
MI300X$2.29$2.991,307 TFLOPSHot AisleSpecialist2026-10-25
B200$2.67$6.002,250 TFLOPSHyperstackSpecialist2026-10-25
TPU v6e$2.94$2.70918 TFLOPSGoogle CloudHyperscaler2026-10-14
H100$3.24$3.20989 TFLOPSHyperstackSpecialist2026-10-25
B300$3.29$7.402,250 TFLOPSHyperstackSpecialist2026-10-25
MI355X$3.44$8.602,500 TFLOPSOracle OCIHyperscaler2026-10-14
H200$4.03$3.99989 TFLOPSHyperstackSpecialist2026-10-25
L40S$4.28$1.55362.05 TFLOPSNebiusSpecialist2026-10-20
A100 80GB$4.33$1.35312 TFLOPSHyperstackSpecialist2026-10-25
TPU v5e$6.09$1.20197 TFLOPSGoogle CloudHyperscaler2026-10-14
GB200 NVL72$6.40$16.002,500 TFLOPSOracle OCIHyperscaler2026-10-14
TPU v5p$9.15$4.20459 TFLOPSGoogle CloudHyperscaler2026-10-14

MI300X has the lowest theoretical dense BF16 cost among the plotted quotes at $2.29/PFLOP·hr, from Hot Aisle.

What a FP8 PFLOP-hour rents for

Cheapest on-demand list price ÷ dense FP8 throughput

Source and methodology

Rental observations October 14, 2026–October 25, 2026. Cheapest on-demand list price for each chip from any tracked provider, hyperscaler or specialist, divided by its vendor-specification dense FP8 throughput (FP32 accumulation). Exact values below identify each plotted quote's provider, class and date. TPU prices are per chip-hour; GB200 uses per-GPU rack pricing. Chips without an FP8 tensor format (A100, V100) are not plotted. Capacity Block and serverless prices are separate billing models and are not plotted.

Exact values for What a FP8 PFLOP-hour rents for
What a FP8 PFLOP-hour rents for — exact values in tabular form
Chip$/PFLOP·hrRental $/hrDense FP8ProviderClassObserved
MI300X$1.14$2.992,614 TFLOPSHot AisleSpecialist2026-10-25
B200$1.33$6.004,500 TFLOPSHyperstackSpecialist2026-10-25
H100$1.62$3.201,979 TFLOPSHyperstackSpecialist2026-10-25
B300$1.64$7.404,500 TFLOPSHyperstackSpecialist2026-10-25
MI355X$1.72$8.605,000 TFLOPSOracle OCIHyperscaler2026-10-14
H200$2.02$3.991,979 TFLOPSHyperstackSpecialist2026-10-25
L40S$2.11$1.55733 TFLOPSNebiusSpecialist2026-10-20
TPU v6e$2.94$2.70918 TFLOPSGoogle CloudHyperscaler2026-10-14
GB200 NVL72$3.20$16.005,000 TFLOPSOracle OCIHyperscaler2026-10-14
TPU v5p$9.15$4.20459 TFLOPSGoogle CloudHyperscaler2026-10-14

MI300X has the lowest theoretical dense FP8 cost among the plotted quotes at $1.14/PFLOP·hr, from Hot Aisle.

Hardware research and cost assumptions

These broader charts provide historical specification and cost context. Memory capacity can limit which models fit on a chip; bandwidth can limit how quickly data reaches its compute units. The limiting factor varies by workload and software.

The memory-bandwidth race

HBM bandwidth by launch date

Source and methodology

Vendor spec sheets; HBM parts only (L4, L40S, GeForce RTX 4090, GeForce RTX 5090 and RTX PRO 6000 Blackwell Server use GDDR and are not plotted). Launch months are estimates of first availability.

Memory cost context

Public $/GB estimate points — memory estimates through Jun 2026

Source and methodology

Context estimates, not an index: sparse HBM3e contract-price points compiled from public analyst estimates — never interpolated, and blends of different periods.

Electricity at full chip power

Static estimate · EIA data through May 2026

≈$0.05/GPU·hr (estimated rate)B200 (HGX) · electricity scenario

≈$0.07/GPU·hr (estimated rate)Instinct MI355X · electricity scenario

Electricity estimate at full chip power: approximately $0.05/GPU·hr for B200 (HGX) and approximately $0.07/GPU·hr for Instinct MI355X — TDP (1 kW / 1.4 kW) × PUE 1.2 × $0.0445/kWh industrial power in New Mexico, the cheapest tracked-cluster state (EIA ELEC.PRICE.NM-IND.M, est). This scenario assumes full-TDP draw for the entire hour; actual electricity use depends on the workload. It excludes host-server power, capital, cooling capex, networking, and margin.

Compute figures use dense tensor rates with FP32 accumulation. Vendor sparsity assumptions and FP16-accumulation figures can produce different headline rates; this comparison keeps them separate.