Qwen2.5-7B · 24 GPUs measured first-party · llama.cpp · Updated October 2026

What GPU Do You Need for Qwen2.5-7B?

Qwen2.5-7B on 24 GPUs, measured first-party: NVIDIA B300 leads at 293.6 tok/s, T4 trails at 39 tok/s, and it peaked at 6GB of VRAM.

Benchmarked weights: bartowski/Qwen2.5-7B-Instruct-GGUF

Fastest we measured

NVIDIA B300

293.6 tok/s on Qwen2.5-7B, the ceiling. Measured on our bench. 288GB of VRAM, $40,000 at launch.

Pros

• 293.6 tok/s on Qwen2.5-7B
• 288GB, clears the Qwen2.5-7B floor
• Rentable by the hour rather than bought

Cons

• 1400W board rating
• Datacenter or workstation hardware, not a retail purchase

Best consumer card

NVIDIA GeForce RTX 5090

284.6 tok/s on Qwen2.5-7B, fastest card you can buy at retail. Measured on our bench. 32GB of VRAM, $1,999 at launch.

Pros

• 284.6 tok/s on Qwen2.5-7B
• 32GB, clears the Qwen2.5-7B floor

Cons

• 575W board rating

Cheapest card that runs it

NVIDIA GeForce GTX 1660 Super

48.82 tok/s on Qwen2.5-7B, lowest launch price that still fits. Measured on our bench. 6GB of VRAM, $229 at launch.

Pros

• 48.82 tok/s on Qwen2.5-7B
• 6GB, clears the Qwen2.5-7B floor

Cons

• 125W board rating

Best value

NVIDIA GeForce RTX 5060

81.66 tok/s on Qwen2.5-7B, most speed per dollar. Measured on our bench. 8GB of VRAM, $249 at launch. That is 328.0 tok/s per $1,000 of launch price.

Pros

• 81.66 tok/s on Qwen2.5-7B
• 8GB, clears the Qwen2.5-7B floor

Cons

• 145W board rating

What the numbers show. Across 11 GPUs measured on our own bench, B300 is fastest at 294 tok/s. The slowest, T4, manages 39.0, so the spread is 7.5x from top to bottom. H200 is the most efficient, 265 tok/s at 233W. Per dollar of launch price, A10G gives the most (32.0 tok/s per $1,000). The fastest card with 16GB or less is T4 at 39.0 tok/s.

About Qwen2.5-7B. Qwen2.5-7B: from Qwen, 7.6B parameters, on Hugging Face since September 2024, Apache 2.0 licence. 12,218,131 downloads in the last 30 days and 5 community quantizations.

How it compares. H100 80GB HBM3: Qwen2.5-7B 264.2 tok/s, Qwen2.5-Coder 7B 263.9 (8B), Mistral-7B-Instruct-v0.2 276.7 (7B), Llama-3.1-8B 261.8 (8B), Llama 3 8B 264.4 (8B). 2 of 4 beat Qwen2.5-7B here.

Cost on a rented GPU. 1M generated tokens of Qwen2.5-7B: $0.15 on a RTX 3060 ($0.036/hr, 4.1 hours), $6.57 on a B300 ($6.94/hr, 57 min, 44.4x the cost).

Speed tiers for Qwen2.5-7B. 30+ tok/s: 24 (RTX 5090, RTX 4090, RTX 5080). 30 tok/s is roughly where replies outpace reading.

Reading your prompt. Before Qwen2.5-7B writes anything it reads the input: 15683.7 tok/s on the RTX 5090 (0.3s for a 4,000-token prompt), 12071.2 on the RTX 4090 (0.3s), 160.7 on the GTX 1660 Super (24.9s). Long documents and big code files feel this number more than the generation speed.

VRAM for Qwen2.5-7B. Measured peak 4.4GB, so 8GB is the smallest common card size; smallest card it ran on: GTX 1660 Super (6GB). With long context: Q4_K_M 6GB (tested), Q2_K 4GB, Q3_K_M 5GB, Q5_K_M 7GB, Q6_K 9GB.

Power on Qwen2.5-7B. Most efficient: H200, 233W, 0.24 kWh per 1M generated tokens. Hungriest: B200, 387W, 0.39 kWh. At $0.15/kWh: $0.037 per 1M generated tokens.

Our verdict

Fastest on Qwen2.5-7B: NVIDIA B300, 293.6 tok/s. Best desktop card: NVIDIA GeForce RTX 5090, 284.6 tok/s. Cheapest consumer card that ran it: NVIDIA GeForce GTX 1660 Super ($229, 48.82 tok/s). Cheapest to rent per job: NVIDIA GeForce RTX 3060, $0.15 per 1M generated tokens.

FAQ

What GPU do I need to run Qwen2.5-7B?

About 5GB. Cheapest consumer card that ran it: NVIDIA GeForce GTX 1660 Super (6GB, 48.82 tok/s).

How fast is Qwen2.5-7B on the NVIDIA GeForce RTX 5090?

284.6 tok/s at 301W, 97% of the NVIDIA B300.

How much does it cost to run Qwen2.5-7B in the cloud?

$0.15 per 1M generated tokens on a NVIDIA GeForce RTX 3060 at $0.036/hr, cheapest of 19 rentable cards we measured.

Can I run Qwen2.5-7B on a 12GB, 16GB or 24GB card?

It used 4.4GB at the precision we tested. 12GB: yes; 16GB: yes; 24GB: yes.

Is the RTX 4090 or the RTX 3090 faster for Qwen2.5-7B?

The RTX 4090: 183.7 vs 156.5 tok/s, 17% faster on our bench.

Should I buy or rent a RTX 5090 for Qwen2.5-7B?

Its $1,999 launch price buys 5,139 rented hours at $0.39/hr, enough for about 5,265x 1M generated tokens of Qwen2.5-7B. Buy only if you'll run more than that.

How we test

llama.cpp llama-bench at Q4_K_M, 512-token prompt and 128 generated tokens, three runs after a warmup, full GPU offload, with power and VRAM sampled throughout. Token generation is memory-bandwidth-bound, so the ranking tracks bandwidth closely, which makes it a fair guide to cards we haven't run yet.