NVIDIA · Ada Lovelace
Best AI Models for NVIDIA GeForce RTX 4050 Laptop GPU (6 GB)
Runs only small models well; 7–9B only just fits.
6 GB GDDR6192 GB/s24 TFLOPS FP16115 WAda Lovelace 2023
6 GB on a 96-bit bus (192 GB/s): fits ~7B Q4 with small context and decodes slowly for its generation. Speed varies with the chassis power limit.
| # | Model | Speed | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 38.3 t/s | 38.3 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 43.9 t/s | 43.9 tok/s | Q4_K_M · 5.0 GB | |
| 3 | Gemma 4 E2B ITGoogle Q4_K_M · 3.5 GB · 36.4 t/s | 36.4 tok/s | Q4_K_M · 3.5 GB | |
| 4 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 42.2 t/s | 42.2 tok/s | Q4_K_M · 4.3 GB | |
| 5 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 65.7 t/s | 65.7 tok/s | Q4_K_M · 2.5 GB |
| # | Model | Speed | Reasoning Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Q4_K_M · 5.0 GB · 43.9 t/s | 43.9 tok/s | Q4_K_M · 5.0 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 38.3 t/s | 38.3 tok/s | overall | Q4_K_M · 3.4 GB |
| 3 | Gemma 4 E2B ITGoogle Q4_K_M · 3.5 GB · 36.4 t/s | 36.4 tok/s | Q4_K_M · 3.5 GB | |
| 4 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 42.2 t/s | 42.2 tok/s | Q4_K_M · 4.3 GB | |
| 5 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 65.7 t/s | 65.7 tok/s | Q4_K_M · 2.5 GB |
| # | Model | Speed | Long context Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 38.3 t/s | 38.3 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Gemma 4 E2B ITGoogle Q4_K_M · 3.5 GB · 36.4 t/s | 36.4 tok/s | Q4_K_M · 3.5 GB | |
| 3 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 42.2 t/s | 42.2 tok/s | Q4_K_M · 4.3 GB | |
| 4 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 65.7 t/s | 65.7 tok/s | Q4_K_M · 2.5 GB | |
| 5 | MiniCPM V 4.7 1BOpenBMB Q4_K_M · 1.6 GB · 97.5 t/s | 97.5 tok/s | Q4_K_M · 1.6 GB |
| # | Model | Speed ↓ | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 38.3 t/s | 38.3 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 114 t/s | 114 tok/s | Q4_K_M · 5.5 GB | |
| 3 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 65.7 t/s | 65.7 tok/s | Q4_K_M · 2.5 GB | |
| 4 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 42.2 t/s | 42.2 tok/s | Q4_K_M · 4.3 GB | |
| 5 | Gemma 4 E2B ITGoogle Q4_K_M · 3.5 GB · 36.4 t/s | 36.4 tok/s | Q4_K_M · 3.5 GB |
| # | Model | Speed | Vision Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 38.3 t/s | 38.3 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 43.9 t/s | 43.9 tok/s | Q4_K_M · 5.0 GB | |
| 3 | MiniCPM V 4.7 1BOpenBMB Q4_K_M · 1.6 GB · 97.5 t/s | 97.5 tok/s | Q4_K_M · 1.6 GB | |
| 4 | LFM3 Omni 2BLiquid AI Q4_K_M · 2.4 GB · 73.4 t/s | 73.4 tok/s | Q4_K_M · 2.4 GB | |
| 5 | Cosmos Reason2 2BNVIDIA Q4_K_M · 3.5 GB · 77.5 t/s | 77.5 tok/s | Q4_K_M · 3.5 GB |
See all 193 models on the RTX 4050 Laptop GPU →Best quant that fits · speeds estimated on this card
The RTX 4050 Laptop GPU runs only small models well. Ada Lovelace generation, released 2023.
GenerationAda Lovelacereleased 2023
RTX 4050 Laptop GPU strengths and weaknesses
Strengths
- Runs 7–9B models: Qwen3.5 9B at 22.6 tok/s in 5.8 GB
- Low power draw: 115 W board power; a 250 W PSU is enough
Weaknesses
- 14B models don't fit: Qwen3 14B needs 11.9 GB at Q4 vs 6 GB here
- Little room for context: Qwen3.5 9B uses 5.8 of 6 GB, 0.2 GB left
Cards people weigh against the RTX 4050 Laptop GPU, each with the one reason it is worth a look.
2 GB more for bigger modelsRTX 3060 8GBNVIDIA · 8 GB · Ampere
▲ 2 GBabout $32924.5 tok/s
2 GB more for bigger modelsRTX 4060NVIDIA · 8 GB · Ada Lovelace▲ 2 GBabout $520rent $0.08/hr27.8 tok/s
2 GB more for bigger modelsA750Intel · 8 GB · Alchemist▲ 2 GBabout $28940.3 tok/s
2 GB more for bigger modelsRTX 3070 TiNVIDIA · 8 GB · Ampere▲ 2 GBabout $599rent $0.18/hr62.2 tok/s
5 GB more for bigger modelsRTX 2080 TiNVIDIA · 11 GB · Turing▲ 5 GBabout $999rent $0.10/hr63.0 tok/s
6 GB more for bigger modelsRTX 5070 Ti Laptop GPUNVIDIA · 12 GB · Blackwell▲ 6 GB68.7 tok/s
Output speed depends on memory bandwidth (192 GB/s). Grey rows need more than 6 GB.
- 22.6tok/s
- 14BQwen3 14B · not at 4-bitneeds 11.9 GB
- 27–31BQwen3.8 27B · not at 4-bitneeds 17.9 GB
- 35B MoEQwen3.6 35B A3B · not at 4-bitneeds 22.0 GB
- 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 738 models on the RTX 4050 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 |
|---|---|---|---|---|---|---|
| BF16 | 3.4 GB | 62.7 t/s | — | A84, Runs well | ||
Qwen3 VL 4B InstructVisionFunctions | Q4_K_M | 4.5 GB | 39.6 t/s | 262K | A75, Runs well | |
Qwen3.5 2B Claude 4.6 Opus Reasoning DistilledChatReasoning | Q4_K_M | 1.9 GB | 70.5 t/s | 262K | S86, Runs great | |
Ministral 3 3B Reasoning 2512ReasoningFunctions | Q4_K_M | 3.9 GB | 45.1 t/s | 262K | A77, Runs well | |
Kimi K2.6 Eagle3Chat | Q4_K_M | 1.9 GB | 85.5 t/s | 262K | S88, Runs great | |
GPT OSS BF16ChatFunctions | Q4_K_M | 0.3 GB | 416.0 t/s | 131K | S100, Runs great | |
| Q4_K_M | 1.2 GB | 116.6 t/s | 128K | S94, Runs great | ||
Soren 1 SmallChatReasoningCodeMath | BF16 | 4.3 GB | 30.0 t/s | 1049K | A71, Runs well | |
Xiaomi OCR 0VisionFunctions | Q4_K_M | 0.9 GB | 143.4 t/s | 262K | S96, Runs great | |
| Q4_K_M | 3.7 GB | 44.7 t/s | 262K | A77, Runs well | ||
| Q4_K_M | 0.3 GB | 416.0 t/s | 8K | S100, Runs great | ||
| BF16 | 0.4 GB | 283.6 t/s | 1K | S100, Runs great | ||
LocoTrainer 4BChatCodeFunctions | Q4_K_M | 4.2 GB | 43.0 t/s | 262K | A77, Runs well | |
Hy MT2 1.8BTranslation | Q4_K_M | 2.6 GB | 75.2 t/s | 262K | S86, Runs great | |
LightOnOCR 3 0.8BVisionFunctions | Q4_K_M | 0.9 GB | 145.1 t/s | 262K | S97, Runs great |
Specs
- Architecture
- Ada Lovelace
- VRAM
- 6 GB GDDR6
- Memory bandwidth
- 192.0 GB/s
- FP16 (dense)
- 24.27 TFLOPS
- CUDA cores
- 2,560
- Tensor cores
- 80
- Compute capability
- 8.9
- TDP
- 115 W
- Released
- 2023-02-22
RTX 4050 Laptop GPU FAQ
What is the largest model the RTX 4050 Laptop GPU can run?
Qwen2.5 7B Instruct (7.6B) is the largest at 4-bit or better: at Q4_K_M it uses 5.8 GB of 6 GB, and runs at about 25.0 tok/s. At 3-bit, a bigger model fits too: Gemma 2 9B IT (9.2B) at IQ3_M, 5.7 GB.
Can the RTX 4050 Laptop GPU run Qwen3.5 4B?
Yes. Qwen3.5 4B fits at Q4_K_M, using 3.4 GB of 6 GB, and it is the best model that runs well on this card.
Can the RTX 4050 Laptop GPU run 14B models?
No. Qwen3 14B needs 11.9 GB at Q4, more than the 6 GB on this card.
How many tokens per second does the RTX 4050 Laptop GPU give?
About 38.3 tok/s on Qwen3.5 4B at Q4_K_M, with the first token after 3.5 s on a 4K-token prompt.
What power supply does the RTX 4050 Laptop GPU need?
Plan a 250 W PSU (2× the 115 W TDP).
Is renting cheaper than buying an RTX 4050 Laptop GPU?
An RTX 3080 (10 GB) rents from $0.11/hr. With regular daily use, owning pays off.