NVIDIA GeForce RTX 4080 vs NVIDIA B300, AI & Machine Learning Comparison
NVIDIA B300 wins 12 of 12 benchmarks, averaging 474.6% faster.
Both cards were measured first-party on our bench, same suite, same test rig.
What the numbers say
The gap is widest in Z-Image Turbo, where NVIDIA B300 leads by 1456% (2.55 vs 39.675 images/min); the closest fight is Qwen3 4B (65% apart); VRAM decides part of this one: NVIDIA B300 runs 140 of our 12 AI workloads while the other card runs 6, models that don't fit score zero.
Benchmark results head-to-head
| Benchmark | NVIDIA GeForce RTX 4080 | NVIDIA B300 | Difference |
|---|---|---|---|
| Qwen3 4B tok/s | 201.76 | 333.34 | -39% |
| Llama 3.1 8B tok/s | 127.09 | 287.23 | -56% |
| Qwen2.5-Coder 14B tok/s | 69.93 | 158.49 | -56% |
| Qwen3 32B tok/s | 0 | 83.68 | n/a |
| Llama 3.3 70B tok/s | 0 | 47.97 | n/a |
| Stable Diffusion XL images/min | 10.16 | 29.2 | -65% |
| Z-Image Turbo images/min | 2.55 | 39.675 | -94% |
| FLUX.1 dev images/min | 0 | 20.807 | n/a |
| FLUX.1 Kontext dev images/min | 0 | 10.329 | n/a |
| Qwen-Image-Edit images/min | 0 | 8.14 | n/a |
| LTX-Video (distilled) frames/s | 3.23 | 31.87 | -90% |
| Wan 2.2 5B (720p) frames/s | 0 | 2.94 | n/a |
Whole-job comparison
How long each card takes to finish a complete pipeline, not just one model. NVIDIA GeForce RTX 4080 is faster on 0 of 1; NVIDIA B300 on 1.
| Workflow | NVIDIA GeForce RTX 4080 | NVIDIA B300 | Difference | Cost per run |
|---|---|---|---|---|
| Full codebase review | 14.3 min | 6.3 min | NVIDIA B300 2.27x faster | $0.026 vs $0.730 |
Renting by the hour, NVIDIA GeForce RTX 4080 finishes 1 of 1 cheaper. The quicker card is not automatically the cheaper way to get the work done.
Cost to rent
| Card | Per hour |
|---|---|
| NVIDIA GeForce RTX 4080 | $0.108 |
| NVIDIA B300 | $6.940 |
NVIDIA GeForce RTX 4080 is 64.26x cheaper per hour. Cheapest on-demand rate we see across RunPod and Vast.
Specifications compared
| NVIDIA GeForce RTX 4080 | NVIDIA B300 | |
|---|---|---|
| VRAM | 16GB | 288GB |
| Architecture | Ada Lovelace (AD103) | Blackwell Ultra |
| Memory bandwidth | 716.8 GB/s | 8 TB/s |
| Boost clock | 2,505 MHz | n/a |
| TDP | 320 W | 1400 W |
| Launch MSRP | $1,199 | $40,000 |
| Release | 2022-11-16 | 2025-11-01 |
FAQ
- Which is better for ai & machine learning: NVIDIA GeForce RTX 4080 or NVIDIA B300?
- NVIDIA B300 performs better for ai & machine learning, winning 12 of 12 benchmarks in our suite with an average 474.6% advantage.
- What are the main hardware differences between NVIDIA GeForce RTX 4080 and NVIDIA B300?
- NVIDIA GeForce RTX 4080 has 16GB VRAM and a 320W TDP, while NVIDIA B300 has 288GB VRAM and a 1400W TDP.
- Does VRAM matter more than speed between NVIDIA GeForce RTX 4080 and NVIDIA B300?
- For AI, yes, NVIDIA B300 fits 4 more of our 12 workloads than NVIDIA GeForce RTX 4080. A model that exceeds VRAM doesn't run slower, it doesn't run at all, so the card that fits the model wins that workload outright.
- Where is the biggest performance difference between NVIDIA GeForce RTX 4080 and NVIDIA B300?
- Z-Image Turbo: NVIDIA B300 leads by roughly 1456% (2.55 vs 39.675 images/min) in our testing.
NVIDIA GeForce RTX 4080 full review · NVIDIA B300 full review · All AI & Machine Learning rankings