NVIDIA · Ampere
Best AI Models for NVIDIA GeForce RTX 3050 6GB Laptop GPU
Runs only small models well; 7–9B only just fits.
6 GB GDDR6144 GB/s15 TFLOPS FP1680 WAmpere 2023
Separate laptop part (6 GB on a 96-bit bus, ~144 GB/s) - not the same as the older 4 GB RTX 3050 Laptop. Holds ~7B Q4 models with a small context; slower than its 6 GB size suggests.
| # | Model | Speed | llmrun Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Qwen3.5 4BAlibabaHow to run → Q4_K_M · 3.4 GB · 28.7 t/s | 28.7 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 33.0 t/s | 33.0 tok/s | Q4_K_M · 5.0 GB | |
| 3 | Gemma 4 E2B ITGoogle Q4_K_M · 3.5 GB · 27.3 t/s | 27.3 tok/s | Q4_K_M · 3.5 GB | |
| 4 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 31.6 t/s | 31.6 tok/s | Q4_K_M · 4.3 GB | |
| 5 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 49.3 t/s | 49.3 tok/s | Q4_K_M · 2.5 GB |
| # | Model | Speed | Reasoning Score | Quant · VRAM |
|---|---|---|---|---|
| 1 | Q4_K_M · 5.0 GB · 33.0 t/s | 33.0 tok/s | Q4_K_M · 5.0 GB | |
| 2 | Qwen3.5 4BAlibaba Q4_K_M · 3.4 GB · 28.7 t/s | 28.7 tok/s | overall | Q4_K_M · 3.4 GB |
| 3 | Gemma 4 E2B ITGoogle Q4_K_M · 3.5 GB · 27.3 t/s | 27.3 tok/s | Q4_K_M · 3.5 GB | |
| 4 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 31.6 t/s | 31.6 tok/s | Q4_K_M · 4.3 GB | |
| 5 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 49.3 t/s | 49.3 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 · 28.7 t/s | 28.7 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Gemma 4 E2B ITGoogle Q4_K_M · 3.5 GB · 27.3 t/s | 27.3 tok/s | Q4_K_M · 3.5 GB | |
| 3 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 31.6 t/s | 31.6 tok/s | Q4_K_M · 4.3 GB | |
| 4 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 49.3 t/s | 49.3 tok/s | Q4_K_M · 2.5 GB | |
| 5 | MiniCPM V 4.7 1BOpenBMB Q4_K_M · 1.6 GB · 73.1 t/s | 73.1 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 · 28.7 t/s | 28.7 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Ling 3.0 TinyInclusion AI Q4_K_M · 5.5 GB · 88.4 t/s | 88.4 tok/s | Q4_K_M · 5.5 GB | |
| 3 | MiniCPM5 2BOpenBMB Q4_K_M · 2.5 GB · 49.3 t/s | 49.3 tok/s | Q4_K_M · 2.5 GB | |
| 4 | Spark X2.6 4BXHToken Q4_K_M · 4.3 GB · 31.6 t/s | 31.6 tok/s | Q4_K_M · 4.3 GB | |
| 5 | Gemma 4 E2B ITGoogle Q4_K_M · 3.5 GB · 27.3 t/s | 27.3 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 · 28.7 t/s | 28.7 tok/s | Q4_K_M · 3.4 GB | |
| 2 | Gemma 3 4B ITGoogle Q4_K_M · 5.0 GB · 33.0 t/s | 33.0 tok/s | Q4_K_M · 5.0 GB | |
| 3 | MiniCPM V 4.7 1BOpenBMB Q4_K_M · 1.6 GB · 73.1 t/s | 73.1 tok/s | Q4_K_M · 1.6 GB | |
| 4 | LFM3 Omni 2BLiquid AI Q4_K_M · 2.4 GB · 55.1 t/s | 55.1 tok/s | Q4_K_M · 2.4 GB | |
| 5 | Cosmos Reason2 2BNVIDIA Q4_K_M · 3.5 GB · 58.1 t/s | 58.1 tok/s | Q4_K_M · 3.5 GB |
See all 193 models on the RTX 3050 6GB Laptop GPU →Best quant that fits · speeds estimated on this card
The RTX 3050 6GB Laptop GPU runs only small models well. Ampere generation, released 2023.
GenerationAmperereleased 2023
RTX 3050 6GB Laptop GPU strengths and weaknesses
Strengths
- Runs 7–9B models: Qwen3.5 9B at 17.0 tok/s in 5.8 GB
- Low power draw: 80 W board power; a 200 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
- Slow prompt reading: A 4K-token prompt on Qwen3.5 4B waits 5.6 s for the first token
- No FP8 or NVFP4: Ampere predates both; use GGUF, AWQ or GPTQ builds
Cards people weigh against the RTX 3050 6GB Laptop GPU, each with the one reason it is worth a look.
About as fast, same 6 GBGTX 1060 6GBNVIDIA · 6 GB · Pascal
same 6 GBabout $24922.6 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 (144 GB/s). Grey rows need more than 6 GB.
- 17.0tok/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 3050 6GB 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 |
|---|---|---|---|---|---|---|
Malaysian TTS 0.6B V1ChatFunctions | Q4_K_M | 1.6 GB | 117.0 t/s | 33K | S94, Runs great | |
SmolVLM2 2.2B InstructVision | Q4_K_M | 2.3 GB | 63.2 t/s | 8K | A84, Runs well | |
GPT OSS BF16ChatFunctions | Q4_K_M | 0.3 GB | 312.0 t/s | 131K | S100, Runs great | |
| Q4_K_M | 0.9 GB | 137.6 t/s | 41K | S96, Runs great | ||
Llama 3.2 3B InstructChatFunctions | Q4_K_M | 4.1 GB | 44.2 t/s | 131K | A77, Runs well | |
Qwen3 4B HereticChat | Q4_K_M | 4.2 GB | 32.3 t/s | 41K | A72, Runs well | |
| Q4_K_M | 0.3 GB | 312.0 t/s | 8K | S100, Runs great | ||
MedPsy 4BChat | Q4_K_M | 4.5 GB | 29.8 t/s | 262K | A71, Runs well | |
| BF16 | 0.4 GB | 212.7 t/s | 1K | S100, Runs great | ||
BaguettotronChat | Q4_K_M | 0.8 GB | 151.0 t/s | 4K | S97, Runs great | |
ErniePEUnleashedChat | Q4_K_M | 3.7 GB | 37.1 t/s | 262K | A74, Runs well | |
Qwen3 4B Gemini 3.1 Pro Reasoning DistilledChatReasoning | Q4_K_M | 4.2 GB | 32.4 t/s | 262K | A72, Runs well | |
MiniCPM OCR 1.0VisionFunctions | Q4_K_M | 1.5 GB | 82.8 t/s | 262K | S88, Runs great | |
Typhoon2.5 Qwen3 4BChatFunctions | Q4_K_M | 4.2 GB | 32.3 t/s | 262K | A72, Runs well | |
CyberSecQwen 4BChat | Q4_K_M | 4.2 GB | 32.3 t/s | 262K | A72, Runs well |
Specs
- Architecture
- Ampere
- VRAM
- 6 GB GDDR6
- Memory bandwidth
- 144.0 GB/s
- FP16 (dense)
- 15.28 TFLOPS
- CUDA cores
- 2,560
- Tensor cores
- 80
- Compute capability
- 8.6
- TDP
- 80 W
- Released
- 2023-01-06
RTX 3050 6GB Laptop GPU FAQ
What is the largest model the RTX 3050 6GB 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 18.8 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 3050 6GB 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 3050 6GB 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 3050 6GB Laptop GPU give?
About 28.7 tok/s on Qwen3.5 4B at Q4_K_M, with the first token after 5.6 s on a 4K-token prompt.
What power supply does the RTX 3050 6GB Laptop GPU need?
Plan a 200 W PSU (2× the 80 W TDP).
Is renting cheaper than buying an RTX 3050 6GB Laptop GPU?
An RTX 3080 (10 GB) rents from $0.11/hr. With regular daily use, owning pays off.