GeForce RTX 3080 Laptop GPU vs GeForce RTX 3080 Ti Laptop GPU: specs and benchmark comparison
Short verdict
NVIDIA GeForce RTX 3080 Ti Laptop GPU leads in every scenario with comparable benchmarks: rendering and compute. This does not imply an advantage in tasks without benchmarks.
Compare with AIRendering and compute
B +20.4%NVIDIA GeForce RTX 3080 Ti Laptop GPU leads in this scenario (up to 20.4% in comparable benchmarks).
No comparable benchmarks yet: gaming: rasterization, gaming: ray tracing, power efficiency.
Advantages
Only measured and rated values: a noticeable benchmark gap and specs where more is better.
Where GeForce RTX 3080 Laptop GPU is better0
No advantages found in our data.
Where GeForce RTX 3080 Ti Laptop GPU is better2
Blender Benchmark 4.5.0 5.5% faster3,061 samples/min vs 2,903 samples/min
Shader units 1,280 more7,424 (CUDA cores) vs 6,144 (CUDA cores)
Benchmarks
Results are compared within one benchmark, one version and the same conditions. Laptop chip results depend on the laptop model: its maker sets the power limit and cooling.
- B ahead by 5.5%
Blender Benchmark 4.5.0
GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) · samples/min, higher is better
GeForce RTX 3080 Laptop GPU2,903 samples/minGeForce RTX 3080 Ti Laptop GPU3,061.5 samples/minPosition among tested models (67, OptiX)
A · 2,903B · 3,06105,00010,00015,000Each dot is one model’s median in this benchmark. The scale starts at zero, samples/min. NVIDIA GeForce RTX 3080 Ti Laptop GPU is ahead by 5.5% in this benchmark.
About the measurement and source
- A · NVIDIA GeForce RTX 3080 Laptop GPU
2,903 samples/min · community measurement, sample 46 · November 14, 2026
Blender Open Data (Blender Foundation)
Median of 46 submissions (7 outliers excluded), interquartile range 2826.16–3093.58; submissions 2025-07-19 to 2026-03-10; OPTIX backend. Snapshot 2026-11-14.
- B · NVIDIA GeForce RTX 3080 Ti Laptop GPU
3,061.5 samples/min · community measurement, sample 28 · November 14, 2026
Blender Open Data (Blender Foundation)
Median of 28 submissions (2 outliers excluded), interquartile range 2704.75–3350.88; submissions 2025-07-18 to 2026-08-05; OPTIX backend. Snapshot 2026-11-14.
difference = |A − B| ÷ the smaller value × 100%. The 5% noticeable threshold is a UX heuristic, not statistical significance.
Cycles render in Blender Benchmark. Median of the sum of samples per minute over three scenes after removing outliers.
Other comparable benchmarks (8)
| Benchmark | A | B | Difference |
|---|---|---|---|
| Blender Benchmark 4.2.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 2,896.3 | 3,317.7 | B +14.5% |
| Blender Benchmark 3.1.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 3,484.9 | 3,740.6 | B +7.3% |
| Blender Benchmark 3.2.1GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 3,366.6 | 3,425.5 | B +1.7% |
| Blender Benchmark 3.3.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 3,501.2 | 3,850.3 | B +10% |
| Blender Benchmark 3.4.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 3,431.4 | 3,521.4 | B +2.6% |
| Blender Benchmark 3.5.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 3,661.2 | 3,939 | B +7.6% |
| Blender Benchmark 3.6.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 3,353.3 | 4,038.1 | B +20.4% |
| Blender Benchmark 4.0.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 3,245.3 | 3,480.6 | B +7.2% |
Each benchmark version has its own scale: numbers are compared only within a row.
Reference results (62)
| Benchmark | A | B | Difference |
|---|---|---|---|
| Blender Benchmark 2.90GPU, bmw27 (CUDA) | 37.6 | — | no pair |
| Blender Benchmark 2.91.2GPU, bmw27 (CUDA) | 28.3 | — | no pair |
| Blender Benchmark 2.92GPU, bmw27 (CUDA) | 29.7 | — | no pair |
| Blender Benchmark 2.93.1GPU, bmw27 (CUDA) | 27.8 | 29.3 | reference |
| Blender Benchmark 2.90GPU, bmw27 (OPTIX) | 16.1 | — | no pair |
| Blender Benchmark 2.91.2GPU, bmw27 (OPTIX) | 15.4 | — | no pair |
| Blender Benchmark 2.92GPU, bmw27 (OPTIX) | 16.9 | — | no pair |
| Blender Benchmark 2.93.1GPU, bmw27 (OPTIX) | 16.2 | 15.9 | reference |
| Blender Benchmark 2.90GPU, classroom (CUDA) | 153.1 | — | no pair |
| Blender Benchmark 2.92GPU, classroom (CUDA) | 92.6 | — | no pair |
| Blender Benchmark 2.93.1GPU, classroom (CUDA) | 127.9 | 130.7 | reference |
| Blender Benchmark 2.90GPU, classroom (OPTIX) | 61.2 | — | no pair |
| Blender Benchmark 2.91.2GPU, classroom (OPTIX) | 56.4 | — | no pair |
| Blender Benchmark 2.92GPU, classroom (OPTIX) | 60.3 | — | no pair |
| Blender Benchmark 2.93.1GPU, classroom (OPTIX) | 55.8 | 58.6 | reference |
| Blender Benchmark 2.90GPU, fishy_cat (CUDA) | 73.1 | — | no pair |
| Blender Benchmark 2.91.2GPU, fishy_cat (CUDA) | 53.9 | — | no pair |
| Blender Benchmark 2.92GPU, fishy_cat (CUDA) | 60.8 | — | no pair |
| Blender Benchmark 2.93.1GPU, fishy_cat (CUDA) | 61.2 | 57.4 | reference |
| Blender Benchmark 2.90GPU, fishy_cat (OPTIX) | 34.2 | — | no pair |
| Blender Benchmark 2.91.2GPU, fishy_cat (OPTIX) | 30.2 | — | no pair |
| Blender Benchmark 2.92GPU, fishy_cat (OPTIX) | 37.5 | — | no pair |
| Blender Benchmark 2.93.1GPU, fishy_cat (OPTIX) | 33.8 | 31.2 | reference |
| Blender Benchmark 2.90GPU, koro (CUDA) | 114.2 | — | no pair |
| Blender Benchmark 2.92GPU, koro (CUDA) | 104.3 | — | no pair |
| Blender Benchmark 2.93.1GPU, koro (CUDA) | 100.2 | 101.2 | reference |
| Blender Benchmark 2.90GPU, koro (OPTIX) | 75.4 | — | no pair |
| Blender Benchmark 2.91.2GPU, koro (OPTIX) | 68 | — | no pair |
| Blender Benchmark 2.92GPU, koro (OPTIX) | 120.9 | — | no pair |
| Blender Benchmark 2.93.1GPU, koro (OPTIX) | 71.8 | 66.2 | reference |
| Blender Benchmark 2.90GPU, pavillon_barcelona (CUDA) | 213.1 | — | no pair |
| Blender Benchmark 2.92GPU, pavillon_barcelona (CUDA) | 192.5 | — | no pair |
| Blender Benchmark 2.93.1GPU, pavillon_barcelona (CUDA) | 171.9 | 164.7 | reference |
| Blender Benchmark 2.90GPU, pavillon_barcelona (OPTIX) | 84.1 | — | no pair |
| Blender Benchmark 2.91.2GPU, pavillon_barcelona (OPTIX) | 74 | — | no pair |
| Blender Benchmark 2.92GPU, pavillon_barcelona (OPTIX) | 83.2 | — | no pair |
| Blender Benchmark 2.93.1GPU, pavillon_barcelona (OPTIX) | 74.8 | 77 | reference |
| Blender Benchmark 2.90GPU, victor (CUDA) | 298.2 | — | no pair |
| Blender Benchmark 2.92GPU, victor (CUDA) | 290.7 | — | no pair |
| Blender Benchmark 2.93.1GPU, victor (CUDA) | 244.5 | 239.5 | reference |
| Blender Benchmark 2.90GPU, victor (OPTIX) | 98.9 | — | no pair |
| Blender Benchmark 2.91.2GPU, victor (OPTIX) | 86.4 | — | no pair |
| Blender Benchmark 2.92GPU, victor (OPTIX) | 124.7 | — | no pair |
| Blender Benchmark 2.93.1GPU, victor (OPTIX) | 106.2 | 101.8 | reference |
| Blender Benchmark 3.0.1GPU, sum of scenes monster + junkshop + classroom (CUDA) | 2,050.2 | — | no pair |
| Blender Benchmark 3.1.0GPU, sum of scenes monster + junkshop + classroom (CUDA) | 2,014.7 | — | no pair |
| Blender Benchmark 3.3.0GPU, sum of scenes monster + junkshop + classroom (CUDA) | 557.4 | — | no pair |
| Blender Benchmark 3.6.0GPU, sum of scenes monster + junkshop + classroom (CUDA) | 2,018.3 | — | no pair |
| Blender Benchmark 4.0.0GPU, sum of scenes monster + junkshop + classroom (CUDA) | 1,785 | — | no pair |
| Blender Benchmark 4.3.0GPU, sum of scenes monster + junkshop + classroom (CUDA) | 1,890.6 | — | no pair |
| Blender Benchmark 5.1.1GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 2,749.2 | 3,252.2 | reference |
| Blender Benchmark 5.2.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 2,746.4 | 3,260.9 | reference |
| Blender Benchmark 3.0.1GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 3,401.4 | 3,385.3 | reference |
| Blender Benchmark 3.2.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 3,508.4 | 3,819.8 | reference |
| Blender Benchmark 4.1.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 3,222.4 | 2,938.6 | reference |
| Blender Benchmark 4.3.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 3,039.6 | 3,360.4 | reference |
| Blender Benchmark 4.4.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 2,914.3 | 3,305.3 | reference |
| Blender Benchmark 5.0.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 2,970.5 | 3,166.3 | reference |
| Blender Benchmark 5.1.0GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | 3,234.9 | 2,561.3 | reference |
| Blender Benchmark 3.5.0GPU, sum of scenes monster + junkshop + classroom (CUDA) | — | 2,650.7 | no pair |
| Blender Benchmark 4.1.0GPU, sum of scenes monster + junkshop + classroom (CUDA) | — | 1,835.1 | no pair |
| Blender Benchmark 3.1.2GPU, sum of scenes monster + junkshop + classroom (OptiX / HIP / oneAPI / Metal) | — | 3,389.7 | no pair |
Each benchmark version has its own scale: numbers are compared only within a row.
Specifications
Chip maker values. The laptop maker sets the power limit and clocks in each laptop.
| Specification | A · GeForce RTX 3080 Laptop GPU | B · GeForce RTX 3080 Ti Laptop GPU | Difference |
|---|---|---|---|
| Chip | |||
| Architecture | Ampere | Ampere | equal |
| Shader unitsShader unit counts are comparable only within one architecture. | 6,144 (CUDA cores) | 7,424 (CUDA cores) | B: 1,280 more |
| Clocks | |||
| Boost clockClocks of different architectures do not reflect performance directly. For laptop chips, the clock depends on the laptop’s power limit. | 1,245–1,710 MHz | 1,125–1,590 MHz | not directly comparable |
| Memory | |||
| Video memory | no data | 16 GB | no data for A |
| Memory type | GDDR6 | GDDR6 | equal |
| Memory bus | 256 bit | 256 bit | equal |
Chip
Architecture
AAmpere
BAmpere
equalShader units
A6,144 (CUDA cores)
B7,424 (CUDA cores)
B: 1,280 moreShader unit counts are comparable only within one architecture.
Clocks
Boost clock
A1,245–1,710 MHz
B1,125–1,590 MHz
not directly comparableClocks of different architectures do not reflect performance directly. For laptop chips, the clock depends on the laptop’s power limit.
Memory
Video memory
Ano data
B16 GB
no data for AMemory type
AGDDR6
BGDDR6
equalMemory bus
A256 bit
B256 bit
equal
“More” does not always mean “better”: higher power draw or size is a system requirement, not an advantage (such bars are dimmed).
Compare with AI
An AI model reviews the specs and benchmarks of this pair and gives a plain-language verdict on who each model suits.
Questions and answers
Which is faster: NVIDIA GeForce RTX 3080 Laptop GPU or NVIDIA GeForce RTX 3080 Ti Laptop GPU?
NVIDIA GeForce RTX 3080 Ti Laptop GPU leads in every scenario with comparable benchmarks: rendering and compute. This does not imply an advantage in tasks without benchmarks.
See also
Data sources (3)
- NVIDIA — specifications of NVIDIA GeForce RTX 3080 Laptop GPU, specifications of NVIDIA GeForce RTX 3080 Ti Laptop GPUchecked November 7, 2026
- Blender Open Data (Blender Foundation) — benchmark Blender Benchmark 2.90, benchmark Blender Benchmark 2.91.2, benchmark Blender Benchmark 2.92, benchmark Blender Benchmark 2.93.1, benchmark Blender Benchmark 3.0.1, benchmark Blender Benchmark 3.1.0, benchmark Blender Benchmark 3.3.0, benchmark Blender Benchmark 3.6.0, benchmark Blender Benchmark 4.0.0, benchmark Blender Benchmark 4.3.0, benchmark Blender Benchmark 3.5.0, benchmark Blender Benchmark 4.1.0, benchmark Blender Benchmark 4.2.0, benchmark Blender Benchmark 4.5.0, benchmark Blender Benchmark 5.1.1, benchmark Blender Benchmark 5.2.0, benchmark Blender Benchmark 3.2.0, benchmark Blender Benchmark 3.2.1, benchmark Blender Benchmark 3.4.0, benchmark Blender Benchmark 4.4.0, benchmark Blender Benchmark 5.0.0, benchmark Blender Benchmark 5.1.0, benchmark Blender Benchmark 3.1.2checked November 14, 2026
- Wikipedia (English) — release date and launch pricechecked November 14, 2026
How we compare: methodology. Where the data comes from: sources.