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All estimates are approximations based on mathematical models and public specifications. Actual performance may vary. Do not make purchasing decisions based solely on these estimates.

Data sourced from Hugging Face, Ollama, and official model documentation. Model names and logos are trademarks of their respective owners.

© 2026 Will It Run AI — Fase Consulting Ibiza, S.L. (NIF: B57969656)

Home/Hardware/GPUs/RTX 3050 Ti Laptop 4GB
NVIDIA

NVIDIA

RTX 3050 Ti Laptop 4GB

RTX 30ConsumerAmperePCIe 4CUDA
4GB
VRAM
192GB/s
Bandwidth
17TFLOPS
FP16 Compute
136TOPS
INT8 Inference
VRAM4 GBBandwidth192 GB/sCompute17 TFInference136 TOPS
RTX 3050 Ti Laptop 4GBCategory AvgIntel Arc A380 6GB

Specifications

Compute
FP1617 TFLOPS
INT8136 TOPS
ArchitectureAmpere
Memory
VRAM4 GB
Bandwidth192 GB/s
General
FamilyRTX 30
SegmentConsumer
InterconnectPCIe 4
Compute PlatformCUDA

Architecture

Ampere

Ampere is NVIDIA's second-generation RTX architecture, built on Samsung's 8nm process. It introduced 3rd-generation Tensor Cores with support for sparsity-accelerated INT8 operations and improved FP16 throughput over Turing.

AI Relevance

Sparsity-aware Tensor Cores can effectively double throughput for structured sparse workloads. However, the lack of FP8 support means quantized inference is less efficient than Ada Lovelace or Blackwell.

Process: Samsung 8nmPlatform: CUDATensor Cores: Gen 3Precisions: FP32, FP16, BF16, INT8, INT4

Recommendations by Workload

Agentic Coding

B

Qwen 2.5 Coder 1.5B

This model is still usable for agentic-coding, but it is not the most specialized pick. It sits in the middle of the current model mix. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 149.8 tok/s · 33K ctx · llama.cpp
3.0 GB / 4.0 GB VRAM

Chat

B

Qwen 3 1.7B

This model is a direct match for chat. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 144.4 tok/s · 10K ctx · llama.cpp
3.1 GB / 4.0 GB VRAM

Coding

B

Qwen 2.5 Coder 1.5B

This model is still usable for coding, but it is not the most specialized pick. It sits in the middle of the current model mix. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 149.8 tok/s · 21K ctx · llama.cpp
3.0 GB / 4.0 GB VRAM

RAG

B

Qwen 3 1.7B

This model is still usable for rag, but it is not the most specialized pick. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 144.4 tok/s · 33K ctx · llama.cpp
3.1 GB / 4.0 GB VRAM

Reasoning

B

DeepSeek R1 1.5B

This model is a direct match for reasoning. It sits in the middle of the current model mix. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.

Decode 149.8 tok/s · 21K ctx · llama.cpp
3.0 GB / 4.0 GB VRAM

Full Model Compatibility

Hugging-quantsHLlama 3.2 1B Instruct Q8 0
B57
1B2.9 GB157 tok/s22K ctx
dense
QwenQwen2.5 1.5B Instruct
B57
1.5B3.0 GB150 tok/s21K ctx
dense
TheBlokeTTinyLlama 1.1B Chat v1.0
B57
1.1B2.8 GB150 tok/s23K ctx
dense
Ggml-orgGSmolVLM 500M Instruct
B56
0.5B2.5 GB157 tok/s25K ctx
dense
Ggml-orgGembeddinggemma 300M
C54
0.3B2.3 GB157 tok/s27K ctx
dense
Googlegemma 2b
C54
2B3.3 GB123 tok/s19K ctx
dense
BartowskiBgemma 2 2b it
C54
2B3.7 GB96 tok/s17K ctx
dense
TheDrummerTGemmasutra Mini 2B v1
C54
2B3.3 GB123 tok/s19K ctx
dense
QwenQwen2.5 3B Instruct
C54
3B3.9 GB82 tok/s16K ctx
dense
BartowskiBLlama 3.2 3B Instruct
C43
3B4.3 GB67 tok/s15K ctx
dense
UnslothQwen3.5 4B
C43
4B4.5 GB55 tok/s14K ctx
dense
Lmstudio-communityLgemma 3 4b it
C42
4B4.5 GB55 tok/s14K ctx
dense
DeepSeekDeepSeek R1 671B
F0
671B416.4 GB2 tok/s4K ctx
moe
MistralDevstral 2 123B Instruct
F0
123B95.5 GB2 tok/s4K ctx
dense
Z.aiGLM-5
F0
744B461.4 GB2 tok/s4K ctx
moe
UnslothQwen3.5 27B
F0
27B22.0 GB9 tok/s4K ctx
dense
UnslothQwen3.5 35B A3B
F0
35B28.1 GB7 tok/s4K ctx
dense
UnslothQwen3.5 9B
F0
9B8.2 GB27 tok/s8K ctx
dense
Moonshot AIKimi K2.5
F0
1000B616.3 GB2 tok/s4K ctx
moe
MistralMistral Large 3
F0
675B419.5 GB2 tok/s4K ctx
+1moe
MistralMistral Small 4 119B
F0
119B74.9 GB6 tok/s4K ctx
moe
AlibabaQwen3-Coder 30B A3B Instruct
F0
30.5B20.7 GB21 tok/s4K ctx
moe
AlibabaQwen3-Coder 480B A35B Instruct
F0
480B299.6 GB2 tok/s4K ctx
moe
AlibabaQwen3-Coder-Next
F0
80B50.9 GB9 tok/s4K ctx
moe
HauhauCSHQwen3.5 9B Uncensored HauhauCS Aggressive
F0
9B8.2 GB27 tok/s8K ctx
dense
UnslothQwen3.5 122B A10B
F0
122B80.1 GB2 tok/s4K ctx
dense
BartowskiBMeta Llama 3.1 8B Instruct
F0
8B7.4 GB31 tok/s9K ctx
dense
DeepSeekDeepSeek V3 671B
F0
671B416.4 GB2 tok/s4K ctx
moe
MistralMixtral 8x22B
F0
141B93.4 GB3 tok/s4K ctx
moe
AlibabaQwen 2.5 72B
F0
72B56.5 GB3 tok/s4K ctx
dense
AlibabaQwen 3 235B A22B
F0
235B148.1 GB3 tok/s4K ctx
moe
AlibabaQwen3-VL 30B A3B Instruct
F0
30B20.4 GB22 tok/s4K ctx
moe
TheBlokeTLlama 2 7B Chat
F0
7B6.7 GB35 tok/s10K ctx
dense
XtunerXllava llama 3 8b v1 1
F0
8B7.4 GB31 tok/s9K ctx
dense
UnslothQwen3.5 397B A17B
F0
397B305.5 GB2 tok/s4K ctx
dense
MistralDevstral Small 2 24B Instruct
F0
24B19.7 GB10 tok/s4K ctx
dense
MetaLlama 3.3 70B
F0
70B54.9 GB4 tok/s4K ctx
dense
MetaLlama 4 Maverick 17B 128E
F0
400B248.0 GB2 tok/s4K ctx
moe
TheBlokeTMistral 7B Instruct v0.2
F0
7B6.7 GB35 tok/s10K ctx
dense
UnslothDeepSeek R1 0528 Qwen3 8B
F0
8B7.4 GB31 tok/s9K ctx
dense
CohereCommand A 111B
F0
111B86.4 GB2 tok/s4K ctx
dense
AlibabaQwen 2.5 Coder 32B
F0
32B25.8 GB8 tok/s4K ctx
dense
AlibabaQwen 2.5 VL 72B
F0
72B56.5 GB3 tok/s4K ctx
dense
Unslothgemma 3 27b it
F0
27B22.0 GB9 tok/s4K ctx
dense
Lmstudio-communityLQwen3.5 9B
F0
9B8.2 GB27 tok/s8K ctx
dense
MaziyarPanahiMMistral 7B Instruct v0.3
F0
7B6.7 GB35 tok/s10K ctx
dense
MaziyarPanahiMMeta Llama 3 8B Instruct
F0
8B7.4 GB31 tok/s9K ctx
dense
Lmstudio-communityLQwen3.5 35B A3B
F0
35B28.1 GB7 tok/s4K ctx
dense
MistralCodestral 2 25.08
F0
22B18.2 GB11 tok/s4K ctx
dense
MistralDevstral Small 1.1
F0
24B19.7 GB10 tok/s4K ctx
dense

Just out of reach

Models you could run with an upgrade

High-quality models that need a bit more memory

DeepSeekDeepSeek R1 671B
671BTier 5Needs ~422.2 GB
MistralDevstral 2 123B Instruct
123BTier 5Needs ~114.8 GB
Runs on Mac Studio M3 Ultra 256GB
Z.aiGLM-5
744BTier 5Needs ~467.6 GB
UnslothQwen3.5 27B
27BTier 5Needs ~26.2 GB
Runs on RTX 5090 32GB (~$1,999)
UnslothQwen3.5 35B A3B
35BTier 5Needs ~33.6 GB
Runs on Mac mini M4 64GB (~$1,099)

Upgrade paths

Upgrade from RTX 3050 Ti Laptop 4GB

See what you unlock with more powerful hardware

Upgrade options

Upgrade options

IntelIntel Arc A380 6GBNext step up
6 GB VRAM (+2)
A
Unlocks Qwen3.5 4B, gemma 3 4b it, gemma 3 4b it+14 more

 

NVIDIAGTX 1660 Super 6GBNVIDIA upgrade
6 GB VRAM (+2)336 GB/s (+144)
A
Unlocks Qwen3.5 4B, gemma 3 4b it, gemma 3 4b it+14 more · +7% faster avg

 

IntelIntel Arc B580 12GBBest value
12 GB VRAM (+8)456 GB/s (+264)
A
Unlocks Qwen3.5 9B, Qwen3.5 9B Uncensored HauhauCS Aggressive, Meta Llama 3.1 8B Instruct+150 more

~$249 MSRP

AMDAMD Instinct MI350X 288GBBiggest leap
288 GB VRAM (+284)8000 GB/s (+7808)
A
Unlocks Devstral 2 123B Instruct, Qwen3.5 27B, Qwen3.5 35B A3B+260 more · +1224% faster avg

~$8,000 MSRP

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