Spec & Pricing Reference

NVIDIA RTX 3090 Cloud Pricing & Specs (2026)

The RTX 3090 pairs 24 GB of GDDR6X with 0.94 TB/s bandwidth at a 350W envelope. It remains a common second-hand and colo card for running 7B-13B models at INT4 and for QLoRA fine-tuning where datacenter GPUs are unnecessary.

Target workload: Local 7B-13B INT4 inference & QLoRA fine-tuning

Memory24GB GDDR6X
Bandwidth0.94 TB/s
FP8 TFLOPSNot supported
Observed rateNo tracked rows
24 GB VRAM
Provider PublishedHIGH
SourceOpenGPU Radar telemetry row (gpu-pricing.json id: rtx-3090)
VerifiedSep 30, 2026
Value
24 GB
Methodology

Spec fields mirrored from the verified telemetry row; board attributes per NVIDIA RTX 3090 specifications. No rate rows tracked.

Refreshed daily from provider APIs and market scrapingSep 30, 2026
0.94 TB/s
Manufacturer SpecHIGH
SourceNVIDIA specification
VerifiedSep 30, 2026
Value
0.94 TB/s GB/s
Methodology

Peak memory bandwidth from the manufacturer specification.

Refreshed daily from provider APIs and market scrapingSep 30, 2026
Methodology →

NVIDIA RTX 3090: Key Numbers at a Glance

Rental cost: no verified rate rows are tracked yet — this page asserts specifications only, never a price.

70B fit: Does not fit Llama 3.3 70B single-GPU — INT4 alone needs 40 GB vs 24 GB available. 7B-13B class is the single-GPU target.

Bottleneck: Memory-bandwidth bound — 0.94 TB/s GDDR6X limits real-time generation throughput

Specs Only — No Rate Rows Tracked
Pricing coverage for NVIDIA RTX 3090

OpenGPU Radar does not currently track this GPU rows in data/providers.json. No price is asserted on this page — the specifications below are manufacturer-sourced.

Compare GPUs with tracked rates →

Compatible Models for NVIDIA RTX 3090

Models from the VRAM registry whose minimum INT4 footprint (weights + KV-cache + runtime overhead) fits 24 GB. FP16 shows where full precision also fits single-GPU.

Browse all model VRAM pages →

Specifications

ArchitectureAmpere GA102 — 8nm Samsung
Memory24GB GDDR6X
Bandwidth0.94 TB/s
InterconnectPCIe 4.0 (64 GB/s)
TDP350W
FP16 TFLOPS71.6
FP8 TFLOPSN/A — no FP8 Tensor Cores (Ampere generation)
FP4 TFLOPSN/A
Recommended quantizationGGUF / AWQ / GPTQ — INT4 mandatory for 13B+
Best cluster topologyPCIe single node — no P2P, multi-GPU training impractical

The RTX 3090 is an Ampere consumer card without FP8 support and without NVLink P2P: multi-GPU workloads fall back to PCIe round-trips (2-way training yields well under 2x speedup). 24 GB fits 13B INT4 (≈7 GB) and 30B INT4 (≈16 GB) with KV-cache headroom; Llama 70B (≈38 GB INT4) does not fit at any practical quantization. At 0.94 TB/s, token generation is bandwidth-bound — larger batches increase throughput linearly until VRAM pressure, not compute, becomes the limit. No rate rows are tracked for the 3090 in OpenGPU Radar's provider table.

Next steps

Related GPUs

Frequently Asked Questions

How much does it cost to rent NVIDIA RTX 3090 per hour?▾
OpenGPU Radar does not currently track rate rows for NVIDIA RTX 3090. The specifications on this page are manufacturer-sourced; no price is asserted.
Can NVIDIA RTX 3090 run 70B parameter LLMs?▾
Does not fit Llama 3.3 70B single-GPU — INT4 alone needs 40 GB vs 24 GB available. 7B-13B class is the single-GPU target.
What is NVIDIA RTX 3090's memory bandwidth?▾
NVIDIA RTX 3090 has 0.94 TB/s of memory bandwidth across 24GB GDDR6X. Token generation is memory-bandwidth bound at batch size 1, so decode throughput scales with this figure — no tokens/sec value is claimed without a benchmark row.
Specifications only — no rate rows tracked for this GPU.Spec sources: OpenGPU Radar telemetry row (gpu-pricing.json id: rtx-3090).Methodology →