NVIDIA · Blackwell · 24 GB VRAM tier
Best AI Models for NVIDIA RTX PRO 5000 Blackwell Generation Laptop GPU (24 GB)
Runs 27–31B and 35B MoE models well; 70B doesn't fit in 24 GB.
24 GB GDDR7896 GB/s228 TFLOPS FP16175 WBlackwell 2025
24 GB GDDR7 at 896 GB/s: ~30B-class Q4 models fit; the laptop part has 24 GB, not the 48-72 GB of the desktop RTX PRO 5000.
| # | Model | Speed | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 33.4 t/s | 33.4 tok/s | Q4_K_M · 17.9 GB | |
| 2 | Qwen3.6 27BAlibaba Q4_K_M · 17.9 GB · 33.4 t/s | 33.4 tok/s | Q4_K_M · 17.9 GB | |
| 3 | Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 28.6 t/s | 28.6 tok/s | Q4_K_M · 21.7 GB | |
| 4 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 157 t/s | 157 tok/s | Q4_K_M · 16.5 GB | |
| 5 | Q4_K_M · 19.3 GB · 187 t/s | 187 tok/s | Q4_K_M · 19.3 GB |
| # | Model | Speed | Coding Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 33.4 t/s | 33.4 tok/s | Q4_K_M · 17.9 GB | |
| 2 | Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 28.6 t/s | 28.6 tok/s | Q4_K_M · 21.7 GB | |
| 3 | Qwen3.6 35B A3BAlibaba Q4_K_M · 22.0 GB · 139 t/s | 139 tok/s | Q4_K_M · 22.0 GB | |
| 4 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 157 t/s | 157 tok/s | Q4_K_M · 16.5 GB | |
| 5 | Q4_K_M · 19.3 GB · 187 t/s | 187 tok/s | Q4_K_M · 19.3 GB |
| # | Model | Speed | Reasoning Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 33.4 t/s | 33.4 tok/s | Q4_K_M · 17.9 GB | |
| 2 | Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 28.6 t/s | 28.6 tok/s | Q4_K_M · 21.7 GB | |
| 3 | Qwen3.5 27BAlibaba Q4_K_M · 17.9 GB · 33.4 t/s | 33.4 tok/s | Q4_K_M · 17.9 GB | |
| 4 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 157 t/s | 157 tok/s | Q4_K_M · 16.5 GB | |
| 5 | Q4_K_M · 19.3 GB · 187 t/s | 187 tok/s | Q4_K_M · 19.3 GB |
| # | Model | Speed | Math Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 33.4 t/s | 33.4 tok/s | Q4_K_M · 17.9 GB | |
| 2 | Qwen3.6 27BAlibaba Q4_K_M · 17.9 GB · 33.4 t/s | 33.4 tok/s | Q4_K_M · 17.9 GB | |
| 3 | Qwen3.6 35B A3BAlibaba Q4_K_M · 22.0 GB · 139 t/s | 139 tok/s | Q4_K_M · 22.0 GB | |
| 4 | Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 28.6 t/s | 28.6 tok/s | overall | Q4_K_M · 21.7 GB |
| 5 | Q4_K_M · 19.3 GB · 187 t/s | 187 tok/s | Q4_K_M · 19.3 GB |
| # | Model | Speed | Long context Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 33.4 t/s | 33.4 tok/s | Q4_K_M · 17.9 GB | |
| 2 | Qwen3.6 27BAlibaba Q4_K_M · 17.9 GB · 33.4 t/s | 33.4 tok/s | Q4_K_M · 17.9 GB | |
| 3 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 157 t/s | 157 tok/s | Q4_K_M · 16.5 GB | |
| 4 | GPT OSS 20BOpenAI Q4_K_M · 13.1 GB · 173 t/s | 173 tok/s | Q4_K_M · 13.1 GB | |
| 5 | LFM2.5 24B A2BLiquid AI Q4_K_M · 15.0 GB · 208 t/s | 208 tok/s | Q4_K_M · 15.0 GB |
| # | Model | Speed ↓ | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 179 t/s | 179 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Q4_K_M · 19.3 GB · 187 t/s | 187 tok/s | Q4_K_M · 19.3 GB | |
| 3 | GPT OSS 20BOpenAI Q4_K_M · 13.1 GB · 173 t/s | 173 tok/s | Q4_K_M · 13.1 GB | |
| 4 | Qwen3 30B A3B Thinking 2507Alibaba Q4_K_M · 19.4 GB · 162 t/s | 162 tok/s | Q4_K_M · 19.4 GB | |
| 5 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 157 t/s | 157 tok/s | Q4_K_M · 16.5 GB |
| # | Model | Speed | Vision Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.8 27BAlibabaHow to run → Q4_K_M · 17.9 GB · 33.4 t/s | 33.4 tok/s | Q4_K_M · 17.9 GB | |
| 2 | Qwen3.6 27BAlibaba Q4_K_M · 17.9 GB · 33.4 t/s | 33.4 tok/s | Q4_K_M · 17.9 GB | |
| 3 | Gemma 4 31B ITGoogle Q4_K_M · 21.7 GB · 28.6 t/s | 28.6 tok/s | Q4_K_M · 21.7 GB | |
| 4 | Gemma 4 26B A4B ITGoogle Q4_K_M · 16.5 GB · 157 t/s | 157 tok/s | Q4_K_M · 16.5 GB | |
| 5 | Muse Glimmer 30BMeta Q4_K_M · 19.6 GB · 31.8 t/s | 31.8 tok/s | Q4_K_M · 19.6 GB |
See all 329 models on the RTX PRO 5000 Blackwell Generation Laptop GPU →Best quant that fits · speeds estimated on this card
The RTX PRO 5000 Blackwell Generation Laptop GPU runs 27–31B and 35B MoE models well. Blackwell generation, released 2025.
GenerationBlackwellreleased 2025
RTX PRO 5000 Blackwell Generation Laptop GPU strengths and weaknesses
Strengths
- Runs 35B MoE models: Qwen3.6 35B A3B at 139 tok/s in 22 GB
- Room for long context: Qwen3.8 27B at Q4 uses 17.9 GB, leaving 6.1 GB free
- Reads long prompts fast: A 4K-token prompt on Qwen3.8 27B starts answering in 2.2 s
Weaknesses
- 70B models don't fit: Llama 3.3 70B Instruct needs 51.3 GB at Q4 vs 24 GB here
Output speed depends on memory bandwidth (896 GB/s). Grey rows need more than 24 GB.
- 9BQwen3.5 9B · Q4_K_M · 6.6 GB91.6tok/s
- 14BQwen3 14B · Q4_K_M · 11.9 GB61.3tok/s
- 27–31BQwen3.8 27B · Q4_K_M · 17.9 GB33.4tok/s
- 35B MoEQwen3.6 35B A3B · Q4_K_M · 22.0 GB139tok/s
- 70BLlama 3.3 70B Instruct · not at 4-bitneeds 51.3 GB
- 120B MoEGPT OSS 120B · not at 4-bitneeds 70.8 GB
Estimated speeds: Q4_K_M, 4K context, one user. How we estimate
All 1158 models on the RTX PRO 5000 Blackwell Generation Laptop GPU
Featured onlyBest quant that fits, ordered by llmrun Score. Fit grades how well it runs here, S best. How ranking works
| Model | Quant | VRAM | Speed | Context | Score | Fit |
|---|---|---|---|---|---|---|
Open Llama 7BChat | Q4_K_M | 4.6 GB | 126.1 t/s | 2K | S95, Runs great | |
| Q4_K_M | 6.8 GB | 118.6 t/s | 33K | S95, Runs great | ||
| Q4_K_M | 7.5 GB | 81.6 t/s | 4K | S88, Runs great | ||
| Q4_K_M | 7.7 GB | 250.5 t/s | 262K | S100, Runs great | ||
| Q4_K_M | 7.9 GB | 109.9 t/s | — | S93, Runs great | ||
| Q4_K_M | 10.4 GB | 76.3 t/s | 33K | S87, Runs great | ||
Phi 2ChatCode | Q4_K_M | 2.6 GB | 220.6 t/s | 2K | S100, Runs great | |
LFM2 350M ExtractChatFunctions | Q4_K_M | 0.8 GB | 1004.1 t/s | 128K | S100, Runs great | |
Olmo 3 1025 7BChat | Q4_K_M | 8.4 GB | 101.3 t/s | 66K | S92, Runs great | |
DeepSeek R1 Distill Llama 8BChatReasoningFunctions | Q4_K_M | 7.3 GB | 108.1 t/s | 131K | S93, Runs great | |
NextCoder 7BChatCode | Q4_K_M | 5.8 GB | 116.7 t/s | 33K | S94, Runs great | |
DeepSWE PreviewChat | Q4_K_M | 22.6 GB | 28.7 t/s | 41K | B48, Decent | |
| Q4_K_M | 13.8 GB | 236.4 t/s | 131K | S100, Runs great | ||
| Q4_K_M | 1.2 GB | 844.1 t/s | 16K | S100, Runs great | ||
T Pro IT 2.0Chat | Q4_K_M | 22.6 GB | 28.7 t/s | 41K | B48, Decent |
Specs
- Architecture
- Blackwell
- VRAM
- 24 GB GDDR7
- Memory bandwidth
- 896.0 GB/s
- FP16 (dense)
- 228.00 TFLOPS
- CUDA cores
- 10,496
- Tensor cores
- 328
- Compute capability
- 12.0
- TDP
- 175 W
- Released
- 2025-03-18
RTX PRO 5000 Blackwell Generation Laptop GPU FAQ
What is the largest model the RTX PRO 5000 Blackwell Generation Laptop GPU can run?
Qwen3.6 35B A3B (36.0B) is the largest at 4-bit or better: at Q4_K_M it uses 22.0 GB of 24 GB, and runs at about 139 tok/s.
Can the RTX PRO 5000 Blackwell Generation Laptop GPU run Qwen3.8 27B?
Yes. Qwen3.8 27B fits at Q4_K_M, using 17.9 GB of 24 GB, and it is the best model that runs well on this card.
Can the RTX PRO 5000 Blackwell Generation Laptop GPU run 70B models?
No. Llama 3.3 70B Instruct needs 51.3 GB at Q4, more than the 24 GB on this card.
How many tokens per second does the RTX PRO 5000 Blackwell Generation Laptop GPU give?
About 33.4 tok/s on Qwen3.8 27B at Q4_K_M, with the first token after 2.2 s on a 4K-token prompt.
What power supply does the RTX PRO 5000 Blackwell Generation Laptop GPU need?
Plan a 350 W PSU (2× the 175 W TDP).
Is 24 GB enough for coding and agents?
Yes for coding: Qwen3.8 27B, the best of the 9 coding models that fit, runs at about 33 tok/s. For agents, not yet: no agent-scored model fits in less than 96 GB.